From jfgf at cs.berkeley.edu Sat Dec 1 13:28:41 2001 From: jfgf at cs.berkeley.edu (Nando de Freitas) Date: Sat, 01 Dec 2001 10:28:41 -0800 Subject: Parallel Paper Submission Message-ID: Dear connectionists Some concerns: 1) Is our goal to publish as much as we can? Or is it to advance science and technology? May be less time writing and reviewing would leave us with more time for contributing to higher goals. 2) As someone who just entered the tenure track process, I honestly don't feel any pressure to write lots of papers - I do feel pressure to carry out good research. Is this a Berkeley/UBC phenomenon only? I suspect not. Where does this not hold? May be this is what needs to be fixed. 3) Whatever we do, let us remember that in most fields of science we encounter papers that weren't recognised for the first, say 50, years of existence and subsequently had a significant impact on science. How do we deal with this? 4) I love journals like "Journal of the Royal Statistical Society - B" because many of the papers include reviews at the end. It turns out that some of the reviews are very critical and really good. I often find myself reading the reviews before reading the paper! Of course, since the reviews get published and CITED, people make an effort to be constructive, soundly critical and not make fools of themselves. This is a great model - slow but good. Cheers! Nando From sfr at unipg.it Sun Dec 2 11:16:55 2001 From: sfr at unipg.it (Simone G.O. Fiori (Pg)) Date: Sun, 02 Dec 2001 17:16:55 +0100 Subject: Parallel Paper Submission Message-ID: <1.5.4.32.20011202161655.01ba4e1c@unipg.it> A problem that deserves attention deals with the interdisciplinary nature of connectionism, which plays a non negligible role in the determination of the difficulties related to the reviewing process. Connectionists come in fact from diverse research areas, ranging e.g. from electrical engineering to psychology, from neurobiology to mathematics and physics, and so on. This often makes papers result in a cross-fertilization of several research branches and, as a matter of fact, makes them difficult to be read from reviewers that do not possess such wide knowledge. Published broad-area papers are interesting to the Readers as well as specialized papers, but they may make severe difficulties arise in the review phase. In my opinion, part of the delay in the review processes arises when an Editor (or action or associate Editor) faces the problem of assigning a paper a proper set of reviewers: It is not infrequent that, after long time, the people simply return the papers unreviewed reporting they are unable to make any useful comments or reporting some sections, e.g. theoretical ones, appear unaccessible. This simply means that reviewers are not in late wrt the review deadline, but they provide a null report. This creates troubles to the Editors who, when this happens, usually take one of these two possible decisions: 1) Simply reject the paper suggesting the Author to submit it to another more suitable journal, or 2) Try to assign a new set of reviewers in the hope to have better luck, re-starting in fact the whole process again. In this situation, by taking a negative decision the Editor implicitly assumes the Author is responsible for the bad outcome -- and this might be not so wrong, actually -- while the second choice burdens the Editor's office or the Editor him/her-self and leave the Author the feeling that an embarrassing, unjustified, long review time is being taken for his/her paper, because he/she is unaware of the difficulties the hidden people are encountering. As someone else has already suggested, a possible solution to this problem is a semi-blind review process, where any Author can suggest a list of handy potential reviewers for the submitted paper; the Author knows they are potentially able to read and comment on the paper, and the longer the list an Editor can count on, the smaller the knowledge an Author has about to whom the paper will be actually sent for review to. To be realistic, I think that if we want our papers to be read by people that actually know the topic, the "conflict of interests" is intrinsic... but this is physiological to our scientific life. About the reviewers, I don't see drawbacks in asking PhD students or post-docs to perform reviews, provided that this is intended in the right way: This could be ultimately a good exercise for them -- striving to comment on an academic valuable paper, or to detect and comment on the weakness of a scientific proposal -- and a good source of high-level notes and observations for Authors. A pool of PhD students or post-docs (such as room-mates) with some research experience, can sometime exceed the knowledge-spread and knowledge-diversity of a single person. My last note concerns a ground-level proposal that I ask the opinion of colleagues on: Some conferences and journals have started managing submissions and reviews by email or, even better, by dedicated web-pages; I can report the great examples of the IEEE Trans. on Antennas and Propagation, the IEEE Trans. on Circuits and Systems - Part II, and Neural Processing Letters, just to cite three; they allow to submit electronic versions of the papers and the reviews electronically, without the need of printing, sending stuff by snail-mail, faxing, etc. with a non-negligible gain of time (and postage saving, of course...). I would suggest journals definitely move to electronic paper submission and review. All the best, Simon. =================================================== Dr Simone Fiori (EE, PhD)- Assistant Professor Dept. of Industrial Engineering (IED) University of Perugia (UNIPG) Via Pentima bassa, 21 - 05100 TERNI (Italy) eMail: sfr at unipg.it - Fax: +39 0744 492925 Web: http://www.unipg.it/~sfr/ =================================================== From bmg at mail.csse.monash.edu.au Sun Dec 2 22:59:08 2001 From: bmg at mail.csse.monash.edu.au (Bernadette Garner) Date: Mon, 3 Dec 2001 14:59:08 +1100 (EST) Subject: Parallel Paper Submission In-Reply-To: from "Nando de Freitas" at Dec 01, 2001 10:28:41 AM Message-ID: <200112030359.fB33x8w19102@nexus.csse.monash.edu.au> > 4) I love journals like "Journal of the Royal Statistical Society - B" > because many of the papers include reviews at the end. It turns out > that some of the reviews are very critical and really good. I often > find myself reading the reviews before reading the paper! Of course, > since the reviews get published and CITED, people make an effort to be > constructive, soundly critical and not make fools of themselves. This > is a great model - slow but good. I think this is a good idea. It will cut down the number of terrible reviews (where the reviewer didn't have a clue). But I am wondering if it could prevent people actually reading papers if they read the reviews first. I know people who won't see movies if the reviews are bad, and that may not be fair because occassionally editors/reviewers have their own agendas. Bernadette Garner From rid at ecs.soton.ac.uk Mon Dec 3 07:37:33 2001 From: rid at ecs.soton.ac.uk (Bob Damper) Date: Mon, 3 Dec 2001 12:37:33 +0000 (GMT) Subject: Parallel Paper Submission: Separate Refereeing and Editorial processes In-Reply-To: <004001c17761$c0941db0$17bcfea9@DBJH8M01> Message-ID: .. but it's not uncommon for journals to send submissions straight out to graduate students, short-circuiting the advisor/supervisor. Sometimes, graduate students will ask the advice of their supervisor about how to approach the review, but not always. The reason students get asked to do such an important task when they ``lack the knowledge and wisdom to provide a fair review of novel ideas'', to use Rob's words, is that journals are generally struggling to get enough reviewers. Editors and editorial assistants don't always know who is who in the field, especially if the journal has a wide remit. If a grad student has recently published something relevant and it comes to the attention of an editor seeking a reviewer, then they become fair game. This shortage of good qualified referees is going to continue all the time there is no tangible reward (other than a warm altruistic feeling) for the onerous task of reviewing. So, as many others have pointed out, parallel submissions will exacerbate this situation rather than improve it. Not a good idea! Bob. On Tue, 27 Nov 2001, rinkus wrote: > > > If people are genuinely interested in improving the scientific review > process you might want to consider making it unacceptable for the > graduate students of reviewers to do the actual reviewing. Graduate > students are just that...students...and lack the knowledge and wisdom to > provide a fair review of novel ideas. > > In many instances a particular student may have particular knowledge and > insight relevant to a particular submission but the proper model here is > for the advertised reviewer (i.e., whose name appears on the editorial > board of the publication) to consult with the student about the > submission (and this should probably be in an indirect fashion so as to > protect the author's identity and ideas) and then write the review from > scratch himself. The scientific review process is undoubtedly worse off > to the extent this kind of accountability is not ensured. We end up > seeing far too much rehashing of old ideas and not enough new ideas. > > Rod Rinkus > > > > From anand at speech.sri.com Mon Dec 3 21:15:43 2001 From: anand at speech.sri.com (Anand Venkataraman) Date: Mon, 3 Dec 2001 18:15:43 -0800 (PST) Subject: Parallel Paper Submission In-Reply-To: <200112030359.fB33x8w19102@nexus.csse.monash.edu.au> (message from Bernadette Garner on Mon, 3 Dec 2001 14:59:08 +1100 (EST)) Message-ID: <200112040215.SAA09737@stockholm> >> 4) I love journals like "Journal of the Royal Statistical Society - B" >> because many of the papers include reviews at the end. It turns out >> that some of the reviews are very critical and really good. I often >> find myself reading the reviews before reading the paper! Of course, >> since the reviews get published and CITED, people make an effort to be >> constructive, soundly critical and not make fools of themselves. This >> is a great model - slow but good. > > I think this is a good idea. It will cut down the number of terrible I too think this is a fantastic idea. It simultaneously solves two problems -- that of reviewer "remuneration" and that of "malicious/bad reviews". The problem, however, is the loss upon publication of anonymity of the reviewer. But why would a reviewer want to remain anonymous unless he/she gave in a malicious review? In my own case at least, I have wished on one occasion that one of four reviews a paper of mine received got published with the reviewer's name on it. I have also wished on more than one occasion that the author of a paper I had reviewed knew my identity when reading my review. The only other issue I see here is that "reviews written to be published" and those written to "improve the paper" tend to be quite different in character. But I guess this is a simple matter to address. The reviewer can simply be requested to relook at the final submission with instructions not to suggest more changes, but rather to submit the final review for publication. Isn't this how the JRSS handles it? & From kpfleger at cs.stanford.edu Mon Dec 3 17:39:49 2001 From: kpfleger at cs.stanford.edu (Karl Pfleger) Date: Mon, 3 Dec 2001 14:39:49 -0800 (PST) Subject: Parallel Paper Submission: Separate Refereeing and Editorial In-Reply-To: from "Bob Damper" at Dec 03, 2001 12:37:33 PM Message-ID: <200112032239.OAA04183@hpp-ss10-4.Stanford.EDU> From Lakhmi.Jain at unisa.edu.au Mon Dec 3 07:50:02 2001 From: Lakhmi.Jain at unisa.edu.au (Lakhmi Jain) Date: Mon, 3 Dec 2001 23:20:02 +1030 Subject: invitation Message-ID: <0402819922B44E4CA0860B3EB619862C2EF6A4@exstaffb.levels.unisa.edu.au> INVITATION SPRINGER-VERLAG Book Series on Advanced Information Processing (AIP) http://www.springer.de/comp/series/aip/index.html Book proposals are invited for a book series titled "Advanced Information Processing" published by Springer-Verlag. The following categories will be considered for publication: (1) Books (text books, reference books, hand books) (2) Coherently integrated multi-author edited books (3) Research monograms L.C. Jain , PhD, ME, BE(Hons), Fellow IE(Australia) Series Editor Director KES, SCT-Building University of South Australia, Adelaide The Mawson Lakes, SA 5095 Australia phone: +61 8 8302 3315 fax: +61 8 8302 3384 email: L.jain at unisa.edu.au (Sincere apologies for multiple copies) From alorincz at matavnet.hu Mon Dec 3 08:01:15 2001 From: alorincz at matavnet.hu (LORINCZ, Andras) Date: Mon, 03 Dec 2001 14:01:15 +0100 Subject: "parallel submission" -- software References: Message-ID: <3C0B779A.42D571@matavnet.hu> Information distributing software with ACCESS CONTROL is available. If you wish to solve the original problem of Gabriele Dorothea Scheler and Johann Martin Philipp Schumann, you need to decide ONLY about access control at connectionists mailing list. Connectionists mail list serves as an advertisement place for technical reportss and papers. anyway. It is then a good idea to start parallel submission at this single point. There is not too much controversy in this statement. Here is an initiating suggestion, which may need to be polished/ironed/confronted. The author uploads his/her paper to to connectionists. Notification goes to everybody who has subsrciption. Uploading and notification are unmoderated. (One can set a filter his/her email not to accept mails from connectionists with subject 'new paper'.) The paper is cached at connectionists and becomes available for downloading. Anybody can make a review of the paper. Reviews are automatically linked to the paper. Reviews are secretive -- the reviewer has an ssh-like communication with connectionists -- and there is a public part of his code. The list and "top acknowledged reviewers" together can reveal the names of "top acknowledged reviewers". If the opinion of the reviewer is considered by the author then he/she can write a revised version of the paper. During uploading this revised version he/she is supposed to acknowledge the reviewer's public code. This is clearly in sake of the author -- provided that he/she would like to promote the reviewer. In turn, works which need improvments and are improved by the reviewer will serve as the basis of selection. If a reviewer is acknowledged, then this reviewer receives a credit (impact) point (factor). There is a ranking of reviewers according to their impact factors. There is a list of the top $n$ most acknowledged reviewers. The names of these $n$ reviewers can be discovered for the public. This is a decision of the reviewer if he/she belongs to this top. These acknowledged reviewers decide (vote) if a paper becomes 'accepted' or not. A paper can be accepted without acknowledgment, for example, if it is perfect. Acceptance means qualification. Acceptance may also mean the opening a forum for discussion about the paper -- which is open reviewing written by people (alike to discussions at BBS). Open reviewing happens through connectionists -- this will be made by another notification list. Top $N>n$ acknowledged reviewers have the right for open reviewing. Their names are provided. In turn, $N$ acknowledged reviewers may be known to the public and $n$ top acknowledged reviewers may vote. Any journal can accept the paper. If an editorial board of a journal accepts the paper then it is a question to the author whether he would like to give the copyright to the journal or not -- he/she might be waiting for a better journal, or, alternatively, -- he/she might have submitted the paper to a journal at the very beginning and might have given the copyright to that journal to start with. If copyright is given to a journal, it should be noted for connectionists. It is the journals' problem how to deal with this challenge. The experienced shift of the editorial board of MLJ to JMLR provides a feeling about the possible outcome. Regards, Andras Lorincz http://people.inf.elte.hu/lorincz P.S. Anyone could build this software. There are freeware solutions, such as 'mailman'. We have also built one with intelligent search options. It has been thoroughly tested for Windows Explorer, but would not support Netscape. Any organization might decide to write/set up/buy a similar software. This seems to be a most probable step in the near future. In this case we shall experience a selective process similar to the evolution of electronic markets: Lots of attempts will start and only a few will survive. So, get started! P.P.S. I have put a paper onto the web. It is closely related to this topic It will appear in the Special Issue of IJFCS (International Journal of Foundations of Computer Science) on Mining the Web Title: "New Generation of the World Wide Web: Anticipating the birth of the 'hostess' race" http://people.inf.elte.hu/lorincz/ParallelSubmission/Lorincz_et_al_Intelligent_Crawler_revised.zip The paper is in a WinZipped postscript file. P.P.P.S. I like the idea of parallel submission. I have the feeling that some reviewers are negligent, may be lacking time, may be students (and lacking knowledge) of authorities on the field, and may be biased agaynszt non-nateave-Inglish-spieking autorz. :-) From mike at stats.gla.ac.uk Tue Dec 4 07:26:28 2001 From: mike at stats.gla.ac.uk (Mike Titterington) Date: Tue, 4 Dec 2001 12:26:28 +0000 (GMT) Subject: Parallel Paper Submission Message-ID: ------------- Begin Forwarded Message ------------- >> 4) I love journals like "Journal of the Royal Statistical Society - B" >> because many of the papers include reviews at the end. It turns out >> that some of the reviews are very critical and really good. I often >> find myself reading the reviews before reading the paper! Of course, >> since the reviews get published and CITED, people make an effort to be >> constructive, soundly critical and not make fools of themselves. This >> is a great model - slow but good. > > I think this is a good idea. It will cut down the number of terrible > The only other issue I see here is that "reviews written to be published" > and those written to "improve the paper" tend to be quite different in > character. But I guess this is a simple matter to address. The reviewer > can simply be requested to relook at the final submission with instructions > not to suggest more changes, but rather to submit the final review for > publication. Isn't this how the JRSS handles it? ------------- End Forwarded Message ------------- I think that it is worth clarifying the JRSS practice. It is not really true that the journal publishes referees' reviews of papers. What happens is that the RSS holds about 10 meetings per year at which certain papers are 'read' and discussed. Versions of the verbal discussions and any written contributions sent in soon after the meeting are lightly edited and are printed, followed by a rejoinder from the authors of the paper. It is very likely that some of the discussants are people who acted as referees, and possibly some of the points made in the referee reports are reiterated in the discussion, but not necessarily. Anyone at all is at liberty to submit a discussion contribution, whether or not they have reviewed the paper. These discussion papers are carefully selected with a view to their being likely to stimulate a lively discussion, as well as being 'scientifically important'. I'd agree with Nando that the discussion can be at least as interesting and stimulating as the paper itself! Maybe I can add one or two points, from the point of view of an editor. 1. I can't imagine coping with parallel submissions. Handling x incoming submissions per year is bad enough. The thought of 4x or even 2x is frightening. I have to side with Grace's original reaction to the proposal! 2. It is hard to envisage any easy alternative to the present system. It is important to have a strong, conscientious and knowledgeable group of associate editors, whose joint expertise covers the journal's range and who can express a cogent opinion on any paper they are sent; this means they either can act, in effect, as the sole referee (a practice that helps to speed things up) or can adjudicate reliably if multiple referees provide conflicting reports. 3. The issue of rewarding referees is difficult, although I believe some journals offer free issues as 'payment'. I think there's more to it than pure altruism. If one wants one's own work to be efficiently and promptly reviewed then it seems fair to repay this by contributing some time to refereeing other people's work. The journal I'm involved with does print an annual list of referees, as an acknowledgement, and this sort of practice does provide some small public recognition. Mike Titterington. =================================================================== D.M. Titterington, Department of Statistics, University of Glasgow, Glasgow G12 8QQ, Scotland, UK. mike at stats.gla.ac.uk Tel (44)-141-330-5022 Fax (44)-141-330-4814 http://www.stats.gla.ac.uk/~mike From jbower at bbb.caltech.edu Tue Dec 4 12:39:00 2001 From: jbower at bbb.caltech.edu (James M. Bower) Date: Tue, 4 Dec 2001 09:39:00 -0800 Subject: improving the review process Message-ID: I am currently writing a book on the state of modern biological research, comparing that state to the development of physics in the 16th and 17th centuries. In the book I am using examples from paper and grant reviews we have received to support the proposition that biology is essentially a folkloric pre-paradigmatic science that needs to develop a sold, quantitative foundation to move forward as a real science. For that reason, I have spent quite a bit of time recently looking through old reviews of our papers. The remarkable thing about those reviews is that there is typically very little criticism of the methods or results sections, but instead the focus is almost always on the discussion. My favorite quote from one of our reviews (and in fact, the source for the title of the forthcoming book), is "I have no more concerns about the methods or results, but I am deeply concerned about what would happen if a graduate student read the discussion". Accordingly, I think that the quality and usefulness of the review process would be greatly improved if the discussion section was excluded, and not even sent to reviewers. In my view, the discussion section should provide an author free reign to consider the implications of their work in their own words, unfettered by what is all to often a kind of thought censorship or, in effect, demand for patronage. Professional expertise is necessary to assure that a paper has no methodological flaws, and that the results are not overstated or overdrawn. But the discussion is the reward that an author should get for having pulled off the former two. How much more interesting and revealing would the scientific literature be if authors felt free to express their real opinions, and heavens forbid, even speculate once in a while? I should mention one other theme in the book that is relevant to much of this discussion. "Modern" scientific journal publishing was actually invented in the 17th century as a means of providing general communication between a new age of physicists. (it is also believed that Newton was interested in controlling who said what). The important point for this discussion is that a 10 page paper is sufficient space to describe a new approach to understanding planetary motion, but it is not, in my opinion, even close to sufficient to present a theory appropriate for understanding biology. Just at the Transactions of the Royal Society promoted the development of a common quantitative base for physics, a new form of publication is now necessary to establish such a base for biology and other complex systems. On that - stay tuned.... Jim Bower -- *************************************** James M. Bower Ph.D. Research Imaging Center University of Texas Health Science Center - San Antonio and Cajal Neuroscience Research Center University of Texas - San Antonio (626) 791-9615 (626) 791-9797 FAX (626) 484-3918 (cell worldwide) Temporary address for correspondence: 110 Taos Rd. Altadena, CA. 91001 WWW addresses for: laboratory (temp) http://www.bbb.caltech.edu/bowerlab GENESIS (temp) http://www.bbb.caltech.edu/GENESIS From ken at phy.ucsf.edu Tue Dec 4 19:14:57 2001 From: ken at phy.ucsf.edu (Ken Miller) Date: Tue, 4 Dec 2001 16:14:57 -0800 Subject: UCSF Postdoctoral/Graduate Fellowships in Theoretical Neurobiology Message-ID: <15373.26369.689037.567063@coltrane.ucsf.edu> FULL INFO: http://www.sloan.ucsf.edu/sloan/sloan-info.html PLEASE DO NOT USE 'REPLY'; FOR MORE INFO USE ABOVE WEB SITE OR CONTACT ADDRESSES GIVEN BELOW The Sloan Center for Theoretical Neurobiology at UCSF solicits applications for pre- and post-doctoral fellowships, with the goal of bringing theoretical approaches to bear on neuroscience. Applicants should have a strong background and education in mathematics, theoretical or experimental physics, or computer science, and commitment to a future research career in neuroscience. Prior biological or neuroscience training is not required. The Sloan Center offers opportunities to combine theoretical and experimental approaches to understanding the operation of the intact brain. Young scientists with strong theoretical backgrounds will receive scientific training in experimental approaches to understanding the operation of the intact brain. They will learn to integrate their theoretical abilities with these experimental approaches to form a mature research program in integrative neuroscience. The research undertaken by the trainees may be theoretical, experimental, or a combination. Resident Faculty of the Sloan Center and their research interests include: William Bialek (1/8 time): Information-theoretic and statistical characterization of, and physical limits to, neural coding and representation Allison Doupe: Development of song recognition and production in songbirds Stephen Lisberger: Learning and memory in a simple motor reflex, the vestibulo-ocular reflex, and visual guidance of smooth pursuit eye movements by the cerebral cortex Michael Merzenich: Experience-dependent plasticity underlying learning in the adult cerebral cortex, and the neurological bases of learning disabilities in children Kenneth Miller: Circuitry of the cerebral cortex: its structure, self-organization, and computational function (primarily using cat primary visual cortex as a model system) Philip Sabes: Sensorimotor coordination, adaptation and development of spatially guided behaviors, experience dependent cortical plasticity. Christoph Schreiner: Cortical mechanisms of perception of complex sounds such as speech in adults, and plasticity of speech recognition in children and adults Michael Stryker: Mechanisms that guide development of the visual cortex There are also a number of visiting faculty, including Larry Abbott, Brandeis University; Sebastian Seung, MIT; David Sparks, Baylor University; Steve Zucker, Yale University. TO APPLY for a POSTDOCTORAL position, please send a curriculum vitae, a statement of previous research and research goals, up to three relevant publications, and have two letters of recommendation sent to us. The application deadline is February 1, 2002. Send applications to: Sloan Center 2002 Admissions Sloan Center for Theoretical Neurobiology at UCSF Department of Physiology University of California 513 Parnassus Ave. San Francisco, CA 94143-0444 PRE-DOCTORAL applicants with strong theoretical training may seek admission into the UCSF Neuroscience Graduate Program as a first-year student. Applicants seeking such admission must apply by Jan. 5, 2002 to be considered for fall, 2002 admission. Application materials for the UCSF Neuroscience Program may be obtained from http://www.neuroscience.ucsf.edu/neuroscience/admission.html or from Pat Vietch Neuroscience Graduate Program Department of Physiology University of California San Francisco San Francisco, CA 94143-0444 neuroscience at phy.ucsf.edu Be sure to include your surface-mail address. The procedure is: make a normal application to the UCSF Neuroscience program; but also alert the Sloan Center of your application, by writing to sloan-info at phy.ucsf.edu. If you need more information: -- Consult the Sloan Center WWW Home Page: http://www.sloan.ucsf.edu/sloan -- Send e-mail to sloan-info at phy.ucsf.edu -- See also the home page for the W.M. Keck Foundation Center for Integrative Neuroscience, in which the Sloan Center is housed: http://www.keck.ucsf.edu/ From jaksa at neuron-ai.fei.tuke.sk Wed Dec 5 09:16:45 2001 From: jaksa at neuron-ai.fei.tuke.sk (Rudolf Jaksa) Date: Wed, 5 Dec 2001 15:16:45 +0100 Subject: publishing model Message-ID: <15374.11341.734421.130097@lada.aid.kyushu-id.ac.jp> I'm thinking how to apply free software development (publishing) model to scientific publishing... Present scientific publishing: 1. Article (for instance paper.pdf) is sent to journal or conference for review (it is in camera ready form). 2. If author will get some feedback from reviewers, she may improve this article. 3. Article is printed on paper (and presented in talk). 4. Other people may read this article and use ideas from it in their future work. Free software model applied to scientific publishing: 1. All the data useful for further work on problem are published in single "package". Instead of only camera ready paper, also source code for algorithms, pictures, sample data etc. are published. This "package" is displayed somewhere on the internet. 2. Availability of this work is announced in established mailing lists or internet forums. 3. Other people may download this "article" or read it directly on internet. 4. They also may download it, incorporate parts of it in their own future work, or publish improved version of this article. They may send their comments to the author and she can incorporate them into next version of article ("package"). Good thing about this model is that it is yet proved that it works, however it may not work for "scientific articles". But in my opinion working on paper or on program code is very similar. And many people seems think that free software itself is inspired by scientific publishing... I like on this model (as opposite to current scientific publishing model) also: * Less money are wasted in publishing process, and it means that more people are "allowed" to read article. And more people are allowed to publish too. * Continuation of work is better as they may be several versions of single "article". This is opposite to several articles spread across different journals and proceedings. * Exchange of ideas can by much faster. The loop author-reviewer-readers-author can be reduced to few days if the work is actually "hot topic". * More data and more types of data can be published, publishing is not restricted to 10 pages of text. Actually I know about one book published this way and few program packages with papers included, but I think this free software publishing approach may be more useful for scientific community. I can even imagine this as primary publishing method in science... R.Jaksa From ehildreth at wellesley.edu Wed Dec 5 09:17:46 2001 From: ehildreth at wellesley.edu (Ellen C. Hildreth) Date: Wed, 5 Dec 2001 15:17:46 +0100 Subject: computational neuroscience position Message-ID: Hi, Wellesley College is conducting a search for a tenure-track faculty position in computational neuroscience. If you are interested in this position, please contact us and submit an application as soon as possible, thanks, Ellen Hildreth --------------------------------------- Tenure-track position in Computational Neuroscience Wellesley College, a pre-eminent liberal arts college for women with a long tradition of excellence in the sciences, has a new tenure-track position available to teach in the expanding Neuroscience Program. The successful candidate will have teaching responsibilities in a home department-- Biological Sciences, Chemistry, Computer Science, or Physics --as well as in the Neuroscience Program. The teaching load would include courses at the introductory, intermediate and advanced undergraduate levels. The successful candidate will be expected to develop a strong research program in computational neuroscience that involves undergraduates. Qualifications include a Ph.D. in computational neuroscience or a related area. Post-doctoral training is preferred. Interested individuals should send curriculum vitae, statement of research and teaching interests, and three letters of recommendation to: Dr. Barbara S. Beltz, Chair, Neuroscience Search Committee, Wellesley College, Wellesley, MA 02481. Review of applications will begin December 1, 2001. Wellesley College is an Equal Opportunity/ Affirmative Action educational institution and employer; successful candidates must be able to work effectively in a culturally diverse environment. Applications from women, minorities, veterans, and candidates with disabilities are encouraged. From school at cogs.nbu.bg Thu Dec 6 09:51:06 2001 From: school at cogs.nbu.bg (CogSci Summer School) Date: Thu, 6 Dec 2001 16:51:06 +0200 Subject: CogSci 2002 Message-ID: 9th International Summer School in Cognitive Science Sofia, New Bulgarian University, July 8 - 28, 2002 Courses: Jeff Elman (University of California at San Diego, USA) - Connectionist Models of Learning and Development Michael Mozer (University of Colorado, USA) - Connectionist Models of Human Perception, Attention, and Awareness Eran Zaidel (University of California at Los Angeles, USA) - Hemispheric Specialization Barbara Knowlton (University of California at Los Angeles, USA) - Cognitive Neuroscience of Memory Markus Knauff (University of Freiburg, Germany) - Imagery and Reasoning: Cognitive and Cortical Models Stella Vosniadou (University of Athens, Greece) - Cognitive Development and Conceptual Change Peter van der Helm (University of Nijmegen, the Netherlands) - Structural Description of Visual Form Antonio Rizzo (University of Siena, Italy) - The Nature of Interactive Artifacts and Their Design Nick Chater (University of Warwick, UK) - Simplicity as a Fundamental Cognitive Principle Organised by the New Bulgarian University Endorsed by the Cognitive Science Society For more information look at: http://www.nbu.bg/cogs/events/ss2002.htm Central and East European Center for Cognitive Science New Bulgarian University 21 Montevideo Str. Sofia 1635 phone: 955-7518 From shultz at psych.mcgill.ca Thu Dec 6 10:43:03 2001 From: shultz at psych.mcgill.ca (Tom Shultz) Date: Thu, 6 Dec 2001 10:43:03 -0500 Subject: job ad Message-ID: <000501c17e6c$b1147440$b86ace84@psych.mcgill.ca> Readers of this list may be interested in the following job ad -------------------------- The Department of Psychology of McGill University seeks applicants for a tenure-track position at the Assistant or junior Associate Professor level in Human Cognitive Neuroscience or Human Cognitive Science. The deadline for receipt of completed applications is January 1, 2002, with an anticipated starting date of September 1, 2002. Applicants with interests in any area of human cognitive neuroscience or human cognitive science will be considered. The Department has excellent facilities for interdisciplinary research through its links with related academic departments at McGill and other universities in Montreal, research units in the McGill University Health Centre including the Montreal Neurological Institute, and McGill Cognitive Science. Applicants at the Assistant Professor level should present early evidence of the ability to establish a record of significant, externally funded research productivity, and applicants at the Associate Professor level should have such a record. All applicants are expected to have an aptitude for undergraduate and graduate teaching. Applicants should arrange for three confidential letters of recommendation to be sent to the address below. A curriculum vitae, description of current and proposed areas of research, selected reprints of published or in press research articles, a description of areas of teaching competency, interest, and approaches, and other relevant material, should also be sent to: Chair, Human Cognitive Neuroscience / Human Cognitive Science Search Committee Department of Psychology McGill University 1205 Penfield Avenue Montreal, QC, Canada H3A 1B1 ----------------------------------------------------------------- Thomas R. Shultz, Professor, Department of Psychology McGill University, 1205 Penfield Ave., Montreal, Quebec, Canada H3A 1B1. E-mail: shultz at psych.mcgill.ca Updated 14 November 2001: http://www.psych.mcgill.ca/perpg/fac/shultz/default.htm Phone: 514 398-6139 Fax: 514 398-4896 ----------------------------------------------------------------- From schmidler at stat.duke.edu Thu Dec 6 10:55:00 2001 From: schmidler at stat.duke.edu (Scott Schmidler) Date: Thu, 6 Dec 2001 10:55:00 -0500 (EST) Subject: Statistics Faculty Positions at Duke University Message-ID: <200112061555.fB6Ft0Q18350@bioinfo.isds.duke.edu> ============================================================== Duke University ISDS Faculty Positions The Institute of Statistics and Decision Sciences (ISDS) at Duke University invites applications and nominations for faculty positions to begin Fall 2002: Open Rank Tenured and Tenure-track Faculty Positions: Successful candidates will have demonstrated excellence in statistical research and teaching (or potential for excellence, for candidates for Assistant Professor) and an interest in participating actively in departmental and university life. Assistant Professor of the Practice of Statistics: Successful candidate will demonstrate excellence, and the potential for national recognition, in statistics with leadership potential to further develop the teaching and statistical practice activities of the Institute. The Institute seeks applicants who will participate enthusiastically in student life, promote standards of academic excellence in education, and provide leadership in service teaching. Visiting Positions: ISDS also offers positions as Visiting Professor of Statistics for periods of one to three years. Successful candidates will have strong skills and interests in teaching and research interests that contribute to the intellectual life of the Institute. Some postdoctoral research positions are also available. ISDS faculty and students are involved in research and education in the development and application of contemporary statistical methods, with particular emphasis on computationally-intensive methods and Bayesian analysis. The department stresses interdisciplinarity in research and teaching, with recent and ongoing projects in a wide range of scientific fields, and the Duke environment offers many opportunities for collaboration across disciplinary boundaries. The Institute currently has 16 regular-rank faculty, 10 visiting, adjunct and postdoctoral faculty, and 26 Ph.D. students. ISDS enrolls approximately 1200 undergraduate and 150 graduate students per year in service courses and approximately 100 graduate students per year in Ph.D. courses. For more information about ISDS and about these openings see the ISDS home page . Candidates must have a doctoral degree in statistics or a related field, and potential for success in an environment where education and collaborative research are valued. There is no application deadline, but screening began December 1, 2001 and is expected to be completed during December. All applicants should send a letter, curriculum vitae, and the names of three references by post to the address below (electronic applications are not accepted). Candidates for Assistant Professor should also send three or more letters of reference. Mail applications to: Faculty Search Committee Duke University ISDS, Box 90251 Durham, NC 27708-0251 or send inquiries by e-mail to: Applications from qualified women and minority candidates are particularly encouraged. Duke University is an Equal Opportunity/Affirmative Action Employer. From maggini at dii.unisi.it Thu Dec 6 11:42:55 2001 From: maggini at dii.unisi.it (Marco Maggini) Date: Thu, 06 Dec 2001 17:42:55 +0100 Subject: CfP: ACM TOIT Special Issue on Machine Learning for the Internet Message-ID: <3C0FA00F.6040203@dii.unisi.it> ------------------------------------------------------ We apologize, if you receive multiple copies. Please feel free to publicize. Thank you. ------------------------------------------------------ CALL FOR PAPERS ACM Transactions on Internet Technology Special Issue on Machine Learning for the Internet Machine learning methods are becoming increasingly important for the development of several internet related technologies. Tasks such as intelligent searching, organizing, retrieving, and filtering information on the Web are extremely challenging and still much too easy for humans than they are for computers, except that humans are unable to scale up with the enormous amount of available data. Explicit coding of rules in this domain is typically very hard, and even if possible, would require exceptional coordination efforts. In particular, the fast dynamics of the information available on the Internet requires new approaches for indexing. The organization of information in Internet portals is becoming hardly manageable by humans. The users' surfing of the Internet can be made easier by personalized tools like search engines optimized for a specific Web community or even for the single user. For example, finding relevant documents by querying a search engine with a set of keywords may be difficult unless a proper ranking scheme is used to order the results. In this case, techniques based on user profiles, on topic selection and on the use of the Web topology can help in defining authoritative sources of information with respect to the given query and interests. Searching, organizing and retrieving information from the Web poses new issues that can be effectively tackled by applying machine learning techniques. Learning algorithms can be used to devise new tools which improve the accessibility to the information available on the Web. Learning is particularly useful to automate those tasks in which it is quite easy to collect examples while coding a set of explicit rules is impractical. For example, the fast dynamics of the Internet can be faced by designing new specialized search tools which cover only the parts of the Web related to a given topic. These search tools focus their exploration only on the portion of the Web which contains the information relevant for this topic. Moreover, learning-based search tools can feature a very high precision in retrieving information and can reduce the need for human efforts for many repetitive tasks (like organizing documents in Web directories). Beside accessing information, understanding and characterizing web structure and usage is essential for future development and organization of new tools and services. In spite of several recent efforts in measuring and producing mathematical models of web connectivity, dynamics, and usage, no definitive answers have emerged and learning may play a fundamental role for advancing our understanding in this field. Papers are invited on applications of machine learning to all aspects of Internet technology. These include (but are not limited to): * Automated creation of web directories * Automatic extraction of information from Web pages * Automatic security management * Categorization of web pages * Design and improvement of web servers through prediction of request patterns * Focused crawling * Information retrieval for the design of thematic search engines * Models and laws that characterize the web structure * User modeling for the personalization of Web services Submissions Authors are requested to send an intention of submission (with authors, title and abstract) as an email message in plain text to acm-toit at dsi.unifi.it by May 1, 2002. Then, papers must be submitted in electronic format as an attachment to the same email address before May 15, 2002. Preferred formats are PDF and PostScript (compressed with gzip or zip). Manuscripts must not exceed 50 single-column, double-spaced pages (including figures and tables) and must be written in English and set in 10 or 11 point font. Please do not send papers directly to guest editors' email addresses. Important Dates Intention of submission: May 1, 2002 Submission deadline: May 15, 2002 Notification: August 1, 2002 Guest editors Gary William Flake NEC Research Institute 4 Independence Way Princeton, NJ 08540 (USA) flake at research.nj.nec.com Voice: +1 609-951-2795 http://www.neci.nj.nec.com/homepages/flake/ Paolo Frasconi Dept. of Systems and Computer Science University of Florence Via di Santa Marta 3, I-50139 Firenze (Italy) paolo at dsi.unifi.it Voice: +39 055 4796 362 http://www.dsi.unifi.it/~paolo/ C. Lee Giles School of Information Sciences and Technology The Pennsylvania State University 001 Thomas Building, University Park, PA, 16802 (USA) giles at ist.psu.edu Voice: +1 814 865 7884 http://ist.psu.edu/giles/ Marco Maggini Dept. of Information Engineering University of Siena Via Roma 56, I-53100 Siena (Italy) maggini at dii.unisi.it Voice: +39 0577 233696 http://www.dii.unisi.it/~maggini/ From bogus@does.not.exist.com Wed Dec 5 01:43:15 2001 From: bogus@does.not.exist.com () Date: Wed, 5 Dec 2001 14:43:15 +0800 Subject: ICONIP'02-SEAL'02-FSKD'02 First Call for Papers Message-ID: <5D138E82835F8143AC52E4899FAEFE38692ECC@EXCHANGE03.staff.main.ntu.edu.sg> [We apologize should you receive multiple copies of this CFP.] =================================== 9th International Conference on Neural Information Processing (ICONIP'02) 4th Asia-Pacific Conference on Simulated Evolution And Learning (SEAL'02) International Conference on Fuzzy Systems and Knowledge Discovery (FSKD'02) =================================== November 18 - 22, 2002, Singapore http://www.ntu.edu.sg/home/nef Organized by: School of Electrical and Electronic Engineering Nanyang Technological University, Singapore Sponsored by: Asia-Pacific Neural Network Assembly SEAL & FSKD Steering Committees Lee Foundation In Co-Operation with: IEEE Neural Network Council International Neural Network Society European Neural Network Society SPIE CALL FOR PAPERS ======= ICONIP'02, SEAL'02, and FSKD'02 will be jointly held in Singapore from November 18 to 22, 2002. The conferences will not only feature the most up-to-date research results in neural information processing, evolutionary computation, fuzzy systems, and knowledge discovery, but also promote cross-fertilization over these exciting and yet closely- related areas. Registration to any one of the conferences will entitle a participant to the technical sessions and the proceedings of all three conferences, as well as the conference banquet, buffet lunches, and a tour to one of the major attractions in Singapore. About Singapore =======Located at one of the most important crossroads of the world, Singapore is truly a place where East and West come together. Here you will find Chinese, Indian, and Malay communities living together, their long established cultures forming a unique backdrop to a clean and modern garden city. English is spoken everywhere and is the common business language of all. Few places on earth promise such a delight for the palate, with gourmet cuisine from over 30 countries. Exotic resorts of Malaysia and Indonesia are only a short bus/ferry ride away. Submission of Papers ========== Authors are invited to submit electronic files (postscript, pdf or Word format) through the conference home page. A selected number of accepted papers will be expanded and revised for possible inclusion in edited books and peer-reviewed journals, such as "Knowledge and Information Systems: An International Journal" by Springer-Verlag. Special Sessions ======== The conferences will feature special sessions on specialized topics to encourage in-depth discussions. One organizer of each successfully organized special session with at least 6 papers will enjoy a 50% discount on the conference registration fee. To propose a special session, email the session title, contact information of the organizer(s), and a short description on the theme and topics covered by the session to Xin Yao, Special Sessions Chair (x.yao at cs.bham.ac.uk), with a copy to Lipo Wang, General Chair (Cc: elpwang at ntu.edu.sg). Sponsorship =====The conferences will offer product vendors a sponsorship package and/or an opportunity to interact with conference participants. Product demonstration and exhibition can also be arranged. For more information, please visit the conference website or contact Tong Seng Quah, Sponsorship/Exhibition Chair (etsquah at ntu.edu.sg), with a copy to Lipo Wang, General Chair (Cc: elpwang at ntu.edu.sg). Keynote Speakers (more will be confirmed later) ======== Shun-ichi Amari, RIKEN Brain Science Institute, Japan David Fogel, Natural Selection, Inc., USA Xin Yao, The University of Birmingham, UK Lotfi A. Zadeh, University of California, USA Important Dates ======= Paper/Summary Deadline : April 30, 2002 Notification of Acceptance : July 15, 2002 Camera-Ready Copy Due : August 15, 2002 Honorary Conference Chairs ============= Shun-ichi Amari, Japan Hans-Paul Schwefel, Germany Lotfi A. Zadeh, USA International Advisory Board ============== Sung-Yang Bang, Korea Meng Hwa Er, Singapore David Fogel, USA Toshio Fukuda, Japan Tom Gedeon, Australia Zhenya He, China Mo Jamshidi, USA Nikola Kasabov, New Zealand Sun-Yuan Kung, USA Tong Heng Lee, Singapore Erkki Oja, Finland Nikhil R. Pal, India Enrique H. Ruspini,USA Harcharan Singh, Singapore Ah Chung Tsoi, Australia Shiro Usui, Toyohashi, Japan Lei Xu, China Benjamin W. Wah, USA Donald C. Wunsch II, USA Xindong Wu, USA Youshou Wu, China Yixin Zhong, China Jacek M. Zurada, USA Advisor === Alex C. Kot, Singapore General Chair ====== Lipo Wang, Singapore Program Co-Chairs ======== ICONIP'02: Kunihiko Fukushima, Japan Soo-Young Lee, Korea Jagath C. Rajapakse, Singapore SEAL'02: Takeshi Furuhashi, Japan Jong-Hwan Kim, Korea Kay Chen Tan, Singapore FSKD'02: Saman Halgamuge, Australia Special Sessions: Xin Yao, UK Finance Chair ====== Charoensak Charayaphan, Singapore Local Arrangement Chair =========== Meng Hiot Lim, Singapore Proceedings Chair ======== Farook Sattar, Singapore Publicity Chair ======= Chunru Wan, Singapore Sponsorship/Exhibition Chair ============== Tong Seng Quah, Singapore Tutorial Chair ======= P. N. Suganthan, Singapore For More Information ========== Please visit the conference home page or contact: Lipo Wang, ICONIP'02-SEAL'02-FSKD'02 General Chair School of Electrical and Electronic Engineering Nanyang Technological University Block S2, 50 Nanyang Avenue, Singapore 639798 Email: elpwang at ntu.edu.sg Phone: +65 790 6372 Conference Secretariat =========== ICONIP'02-SEAL'02-FSKD'02 Secretariat Conference Management Center/CCE, NTU Administration Annex Building #04-06 42 Nanyang Avenue, Singapore 639815 Email: nef at ntu.edu.sg Fax: +65 793 0997 From berthier at psych.umass.edu Fri Dec 7 06:00:23 2001 From: berthier at psych.umass.edu (Neil Berthier) Date: Fri, 07 Dec 2001 06:00:23 -0500 Subject: Assistant Professor position in Cognitive neuroscience Message-ID: <1007722823.8525.92.camel@arpeggio> Readers may be interested in the following job-- THE DEPARTMENT OF PSYCHOLOGY, UNIVERSITY OF MASSACHUSETTS -- AMHERST invites applications for a three year, non-tenure track, Assistant Professor position in Cognitive neuroscience beginning Fall, 2002. The ideal candidate will have research interests in human perception and/or action (although other areas of cognition will be considered), and will have training in one or more of the following areas: cognitive neuroscience, cognitive psychology, human neuropsychology, or neurophysiology. The successful applicant will become part of our growing emphasis in cognitive neuroscience and join existing faculty in strong graduate programs in cognitive and developmental psychology and neuroscience and behavior. This individual will have access to on-campus research facilities and expertise in fMRI study design and analysis, transcranial magnetic stimulation (TMS), kinematic and eye movement recording, and psychophysics. Off-campus resources for fMRI data collection are also available. Teaching responsibilities will include three undergraduate or graduate courses per year. Salary is dependent on experience and qualifications. Applicants should send a vita, a statement of research and teaching interests, reprints of recent publications, and at least three letters of recommendation to: Cognitive Neuroscience Search Committee, Department of Psychology, University of Massachusetts, Amherst, MA 01003-7710. We will begin reviewing application in January, 2002, and will continue until the position is filled. Hiring is contingent upon the availability of funds. The University of Massachusetts is an Affirmative Action/Equal Opportunity Employer. Women and members of minority groups are highly encouraged to apply. Contact Charles Clifton (cec at psych.umass.edu) for more information. From cindy at cns.bu.edu Fri Dec 7 14:00:18 2001 From: cindy at cns.bu.edu (Cynthia Bradford) Date: Fri, 7 Dec 2001 14:00:18 -0500 Subject: 6th ICCNS: Final Invited Program and Call for Abstracts Message-ID: <200112071900.OAA04466@retina.bu.edu> Apologies if you receive this more than once. ***** FINAL INVITED SPEAKER PROGRAM AND CALL FOR ABSTRACTS ***** SIXTH INTERNATIONAL CONFERENCE ON COGNITIVE AND NEURAL SYSTEMS Tutorials: May 29, 2002 Meeting: May 30 - June 1, 2002 Boston University http://www.cns.bu.edu/meetings/ This interdisciplinary conference focuses on two fundamental questions: How Does the Brain Control Behavior? How Can Technology Emulate Biological Intelligence? A single oral or poster session enables all presented work to be highly visible. Contributed talks will be presented on each of the three conference days. Three-hour poster sessions with no conflicting events will be held on two of the conference days. All posters will be up all day, and can also be viewed during breaks in the talk schedule. CONFIRMED INVITED SPEAKERS TUTORIAL SPEAKERS: Wednesday, May 29, 2002 Mark Gluck (Rutgers University) Neural networks in neurology and clinical neuropsychology: Alzheimer's disease, amnesia, and Parkinson's disease Gail A. Carpenter (Boston University) Adaptive resonance theory Ferdinando Mussa-Ivaldi (Northwestern University Medical School) Learning and adaptive control of arm movements Frank Guenther (Boston University) Neural modeling of speech INVITED SPEAKERS Thursday, May 30, 2002 CELL AND CIRCUIT DYNAMICS: Daniel Johnston (Baylor College of Medicine) Information processing and storage by neuronal dendrites Bard Ermentrout (University of Pittsburgh) Learning at a slug's pace: The role of oscillations in odor learning in the Limax John Rinzel (New York University) Cellular dynamics involved in sound localization VISION AND IMAGE PROCESSING: Rudiger von der Heydt (Johns Hopkins University School of Medicine) Visual cortex: Global structure in local feature maps David J. Field (Cornell University) Visual systems and the statistics of natural scenes: How far can we go? Philip J. Kellman (UCLA) From niebur at russell.mb.jhu.edu Fri Dec 7 14:46:03 2001 From: niebur at russell.mb.jhu.edu (niebur@russell.mb.jhu.edu) Date: Fri, 7 Dec 2001 14:46:03 -0500 Subject: Applications to the Johns Hopkins Neuroscience Graduate Program Message-ID: <200112071946.OAA16190@russell.mb.jhu.edu> The deadline is coming up for applications to the Johns Hopkins Neuroscience Graduate Program http://neuroscience.jhu.edu/gradprogram.asp DEADLINE: January 4, 2002 For the readers of this group, I should emphasize that applications from students interested in computational neuroscience and systems level neuroscience are particularly encouraged. Systems level research in the Program ranges from single unit recordings in behaving nonhuman primates to psychophysical and functional MRI studies in humans and is complemented by training in computational neuroscience. The Neuroscience Training Program at The Johns Hopkins University School of Medicine includes over sixty faculty members in the Departments of Neuroscience, Psychology, Cognitive Science, Molecular Biology and Genetics, Biological Chemistry, Physiology, Biomedical Engineering, Pharmacology and Molecular Sciences, Ophthalmology, Neurology, Psychiatry and Behavioral Sciences, Medicine, Otolaryngology, and Pathology. The Training Program addresses the broad areas encompassed by modern neuroscience. The purpose of the Program is to train doctoral students for independent research and teaching in neuroscience. It is the goal of the Program to ensure that candidates for the Ph.D. and M.D./Ph.D. degrees obtain a background covering molecular/cellular and systems/cognitive approaches to neuroscience, as well as receive training that brings them to the forefront of research in their particular area of interest. A series of core courses in neuroscience, along with advanced electives, seminar series, laboratory rotations and original independent dissertation research form the Neuroscience Graduate Training Program. The Neuroscience Training Program and the Neuroscience Department are among the oldest in the United States and date back to 1980. The faculty of the Neuroscience Training Program have trained about 250 Ph.D. and M.D./Ph.D. students and 500 postdoctoral fellows over the past ten years. All doctoral candidates receive full tuition remission and a stipend. Currently, about 90 doctoral candidates and 150 postdoctoral fellows work in the laboratories of faculty in the Neuroscience Program. For more information and contact information, see also neuroscience.jhu.edu. -- Ernst Niebur, PhD Krieger Mind/Brain Institute Assoc. Prof. of Neuroscience Johns Hopkins University niebur at jhu.edu 3400 N. Charles Street (410)516-8643, -8640 (secr), -8648 (fax), -3357 (lab) Baltimore, MD 21218 From miguel at giccs.georgetown.edu Mon Dec 10 21:13:17 2001 From: miguel at giccs.georgetown.edu (Miguel . Carreira-Perpin) Date: Mon, 10 Dec 2001 21:13:17 -0500 Subject: thesis: latent var. models, dim. reduction & missing data reconstr. Message-ID: <15381.27581.312558.417306@giccs.georgetown.edu> Dear connectionists, I am pleased to make my PhD thesis available online (abstract below): Continuous latent variable models for dimensionality reduction and sequential data reconstruction Miguel A. Carreira-Perpinan 333 pages, 130 figures, 24 tables, 445 references This thesis may be of interest to researchers working on probabilistic models for data analysis, in particular dimensionality reduction, inverse problems and missing data problems. Applications are given mainly for speech processing (electropalatography, acoustic-to-articulatory mapping). It also contains extensive surveys of all these areas. The thesis can be retrieved in PostScript and PDF formats from: http://www.dcs.shef.ac.uk/~miguel/papers/phd-thesis.html or http://www.giccs.georgetown.edu/~miguel/papers/phd-thesis.html Also available there are: - Matlab software for several of the models and algorithms discussed - A BibTeX file with the references Best regards, Miguel -- Miguel A Carreira-Perpinan Department of Neuroscience Tel. (202) 6878679 Georgetown University Medical Center Fax (202) 6870617 3900 Reservoir Road NW mailto:miguel at giccs.georgetown.edu Washington, DC 20007, USA http://www.giccs.georgetown.edu/~miguel ----------------------------------8<---------------------------------- CONTINUOUS LATENT VARIABLE MODELS FOR DIMENSIONALITY REDUCTION AND SEQUENTIAL DATA RECONSTRUCTION Miguel A. Carreira-Perpinan Dept. of Computer Science, University of Sheffield, UK February 2001 Abstract ======== Continuous latent variable models (cLVMs) are probabilistic models that represent a distribution in a high-dimensional Euclidean space using a small number of continuous, latent variables. This thesis explores, theoretically and practically, the ability of cLVMs for dimensionality reduction and sequential data reconstruction. The first part of the thesis reviews and extends the theory of cLVMs: definition in terms of a prior distribution in latent space, a mapping to data space and a noise model; maximum likelihood parameter estimation with an expectation-maximisation (EM) algorithm; specific cLVMs (factor analysis, principal component analysis (PCA), independent component analysis, independent factor analysis and the generative topographic mapping (GTM)); mixtures of cLVMs; identifiability, interpretability and visualisation; and derivation of mappings for dimensionality reduction and reconstruction and their properties, such as continuity, for each cLVM. We extend GTM to diagonal noise and give a corresponding EM algorithm. We also describe a discrete LVM for binary data, Bernoulli mixtures, widely used in practice. We show that their log-likelihood surface has no singularities, unlike other mixture models, which makes EM estimation practical; and that their theoretical non-identifiability is rarely realised in actual estimates, which makes them interpretable. The second part deals with dimensionality reduction. We define the problem and give an extensive, critical review of nonprobabilistic methods for it: linear methods (PCA, projection pursuit), nonlinear autoassociators, kernel methods, local dimensionality reduction, principal curves, vector quantisation methods (elastic net, self-organising map) and multidimensional scaling methods. We then empirically evaluate, in terms of reconstruction error, computation time and visualisation, several latent-variable methods for dimensionality reduction of binary electropalatographic (EPG) data: PCA, factor analysis, mixtures of factor analysers, GTM and Bernoulli mixtures. We compare these methods with earlier, nonadaptive EPG data reduction methods and derive 2D maps of EPG sequences for use in speech research and therapy. The last part of this thesis proposes a new method for missing data reconstruction of sequential data that includes as particular case the inversion of many-to-one mappings. We define the problem, distinguish it from inverse problems, and show when both coincide. The method is based on multiple pointwise reconstruction and constraint optimisation. Multiple pointwise reconstruction uses a Gaussian mixture joint density model for the data, conveniently implemented with a nonlinear cLVM (GTM). The modes of the conditional distribution of missing values given present values at each point in the sequence represent local candidate reconstructions. A global sequence reconstruction is obtained by efficiently optimising a constraint, such as continuity or smoothness, with dynamic programming. We give a probabilistic interpretation of the method. We derive two algorithms for exhaustive mode finding in Gaussian mixtures, based on gradient-quadratic search and fixed-point search, respectively; as well as estimates of error bars for each mode and a measure of distribution sparseness. We discuss the advantages of the method over previous work based on the conditional mean or on universal mapping approximators (including ensembles and recurrent networks), conditional distribution estimation, vector quantisation and statistical analysis of missing data. We study the performance of the method with synthetic data (a toy example and an inverse kinematics problem) and real data (mapping between EPG and acoustic data). We describe the possible application of the method to several well-known reconstruction or inversion problems: decoding of neural population activity for hippocampal place cells; wind field retrieval from scatterometer data; inverse kinematics and dynamics of a redundant manipulator; acoustic-to-articulatory mapping; audiovisual mappings for speech recognition; and recognition of occluded speech. Contents (abridged) =================== 1. Introduction 2. The continuous latent variable modelling formalism 3. Some properties of finite mixtures of multivariate Bernoulli distributions 4. Dimensionality reduction 5. Dimensionality reduction of electropalatographic (EPG) data 6. Inverse problems and mapping inversion 7. Sequential data reconstruction 8. Exhaustive mode finding in Gaussian mixtures 9. Experiments with synthetic data 10. Experiments with real-world data: the acoustic-to-articulatory mapping problem 11. Conclusions Appendices ----------------------------------8<---------------------------------- From qian at brahms.cpmc.columbia.edu Tue Dec 11 11:14:06 2001 From: qian at brahms.cpmc.columbia.edu (Ning Qian) Date: Tue, 11 Dec 2001 11:14:06 -0500 Subject: paper: stochastic resonance in sensory perception Message-ID: <200112111614.fBBGE6k31900@brahms.cpmc.columbia.edu> Dear colleagues, The following short paper (0.08 MB) is available online at: http://brahms.cpmc.columbia.edu/publications/sr.ps.gz A model for stochastic resonance-type behavior in sensory perception Yunfan Gong, Nestor Matthews, and Ning Qian Physical Review E, 2002 (in press). Abstract Recently it was found that noise could help improve human detection of sensory stimuli via stochastic resonance-type behavior. Specifically, the ability of an individual to detect a weak tactile stimulus could be enhanced by adding a certain amount of noise. Here we propose, from the perspective of classic signal detection theory, a simple and general model to elucidate the mechanism underlying this novel phenomenon. We demonstrate that noise-mediated enhancements and decrements in human sensation can be well reproduced by our model. The predicted upper bound of the performance improvement by adding noise is also consistent with the experimental data. We suggest additional experiments to further test the model. Best regards, Ning Qian ------------------------------------------------------------- http://brahms.cpmc.columbia.edu Ning Qian, Ph. D. qian at brahms.cpmc.columbia.edu Associate Professor nq6 at columbia.edu Ctr. Neurobiology & Behavior Columbia University 212-543-5213 (Office) NYSPI Annex Rm 730 212-543-5161 (Lab/fax) 1051 Riverside Drive 212-543-5410 (Center/fax) New York, NY 10032, USA ------------------------------------------------------------- From aslin at cvs.rochester.edu Tue Dec 11 13:10:15 2001 From: aslin at cvs.rochester.edu (Richard Aslin) Date: Tue, 11 Dec 2001 13:10:15 -0500 Subject: postdoc slots at University of Rochester Message-ID: THE UNIVERSITY OF ROCHESTER The University of Rochester seeks five or more outstanding postdoctoral fellows with research interests in several areas of the Cognitive Sciences, including language, learning, and development. Two NIH training grants provide support. (1) An NIH training grant is affiliated with the Center for the Sciences of Language. The Center brings together faculty and students with interests in spoken and signed languages from the Departments of Brain and Cognitive Sciences, Computer Science, Linguistics, and Philosophy, as well as the interdepartmental program in Neuroscience. We encourage applicants from any of these disciplines who have expertise in any area of natural language. We are particularly interested in postdoctoral fellows who want to contribute to an interdisciplinary community. (2) A second NIH training grant spans the disciplines of Learning and Developmental Plasticity. Applicants should have expertise in human or animal research on learning and developmental plasticity or in computational modeling. Contributing faculty are in the Departments of Brain and Cognitive Sciences, Computer Science, and the interdepartmental program in Neuroscience. All fellowships are open only to US citizens or permanent residents. Applicants should send a letter describing their graduate training and research interests, a curriculum vitae, and arrange to have three letters of recommendation sent to: Professor Richard N. Aslin Department of Brain and Cognitive Sciences Meliora Hall University of Rochester Rochester, NY 14627-0268. Review of applications will begin on January 15, 2002 and continue until all of the positions are filled, with expected start dates ranging from June 30 to September 1, 2002. Learn more about the community of faculty, students, and training facilities of the Center for Language Sciences (and affiliated departments and programs) and the Department of Brain and Cognitive Sciences by visiting our web sites: http://www.cls.rochester.edu and http://www.bcs.rochester.edu From Dave_Touretzky at cs.cmu.edu Mon Dec 17 03:22:36 2001 From: Dave_Touretzky at cs.cmu.edu (Dave_Touretzky@cs.cmu.edu) Date: Mon, 17 Dec 2001 03:22:36 -0500 Subject: Graduate training with the Center for the Neural Basis of Cognition Message-ID: <5378.1008577356@ammon.boltz.cs.cmu.edu> Note: application deadline January 1, 2002. Graduate Training with the Center for the Neural Basis of Cognition The Center for the Neural Basis of Cognition offers an interdisciplinary doctoral training program operated jointly with eight affiliated PhD programs at Carnegie Mellon University and the University of Pittsburgh. Detailed information about this program is available on our web site at http://www.cnbc.cmu.edu/Training. The Center is dedicated to the study of the neural basis of cognitive processes including learning and memory, language and thought, perception, attention, and planning; to the study of the development of the neural substrate of these processes; to the study of disorders of these processes and their underlying neuropathology; and to the promotion of applications of the results of these studies to artificial intelligence, robotics, and medicine. CNBC students have access to some of the finest facilities for cognitive neuroscience research in the world: Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) scanners for functional brain imaging, neurophysiology laboratories for recording from brain slices and from anesthetized or awake, behaving animals, electron and confocal microscopes for structural imaging, high performance computing facilities including an in-house supercomputer for neural modeling and image analysis, and patient populations for neuropsychological studies. Students are admitted jointly to a home department and the CNBC Training Program. Applications are encouraged from students with interests in biology, neuroscience, psychology, engineering, physics, mathematics, computer science, or robotics. For more information about the program, and to obtain application materials, visit our web site at www.cnbc.cmu.edu, or contact us at the following address: Center for the Neural Basis of Cognition 115 Mellon Institute 4400 Fifth Avenue Pittsburgh, PA 15213 Tel. (412) 268-4000. Fax: (412) 268-5060 email: cnbc-admissions at cnbc.cmu.edu The affiliated PhD programs at the two universities are: Carnegie Mellon University of Pittsburgh Biological Sciences Mathematics Computer Science Neuroscience Psychology Psychology Robotics Statistics The CNBC training faculty includes: Eric Ahrens (CMU Biology): MRI studies of the vertebtate nervous system John Anderson (CMU Psychology): models of human cognition German Barrionuevo (Pitt Neuroscience): LTP in hippocampal slice Alison Barth (CMU Biology): molecular basis of plasticity in neocortex Marlene Behrmann (CMU Psychology): spatial representations in parietal cortex Pat Carpenter (CMU Psychology): mental imagery, language, and problem solving Cameron S. Carter (Pitt Psychology/Neuroscience): fMRI and PET attention studies Carson Chow (Pitt Mathematics): spatiotemporal dynamics in neural networks Carol Colby (Pitt Neuroscience): spatial reps. in primate parietal cortex Steve DeKosky (Pitt Neurobiology): neurodegenerative human disease William Eddy (CMU Statistics): analysis of fMRI data Bard Ermentrout (Pitt Mathematics): oscillations in neural systems Julie Fiez (Pitt Psychology): fMRI studies of language Chris Genovese (CMU Statistics): making inferences from scientific data Lori Holt (CMU Psychology): mechanisms of auditory and speech perception John Horn (Pitt Neurobiology): synaptic plasticity in autonomic ganglia Allen Humphrey (Pitt Neurobiology): motion processing in primary visual cortex Satish Iyengar (Pitt Statistics): spike train data analsysis Marcel Just (CMU Psychology): visual thinking, language comprehension Robert Kass (CMU Statistics): transmission of info. by collections of neurons Roberta Klatzky (CMU Psychology): human perception and cognition Richard Koerber (Pitt Neurobiology): devel. and plasticity of spinal networks Tai Sing Lee (CMU Comp. Sci.): primate visual cortex; computer vision Michael Lewicki (CMU Comp. Sci.): learning and representation David Lewis (Pitt Neuroscience): anatomy of frontal cortex Brian MacWhinney (CMU Psychology): models of language acquisition Yoky Matsuoka (CMU Robotics): human motor control and motor learning James McClelland (CMU Psychology): connectionist models of cognition Paula Monaghan Nichols (Pitt Neurobiology): vertebrate CNS development Carl Olson (CNBC): spatial representations in primate frontal cortex Charles Perfetti (Pitt Psychology): language and reading processes David Plaut (CMU Psychology): connectionist models of reading Michael Pogue-Geile (Pitt Psychology): development of schizophrenia Lynne Reder (CMU Psychology): models of memory and cognitive processing Erik Reichle (Pitt Psychology): attention and eye movements in reading Jonathan Rubin (Pitt Mathematics): analysis of systems of coupled neurons Walter Schneider (Pitt Psych.): fMRI, models of attention & skill acquisition Charles Scudder (Pitt Neurobiology): motor learning in cerebellum Susan Sesack (Pitt Neuroscience): anatomy of the dopaminergic system Dan Simons (Pitt Neurobiology): sensory physiology of the cerebral cortex Peter Strick (Pitt Neurobiology): motor control; basal ganglia and cerebellum Flo Thiels (Pitt Neurosicence): LTP and LTD in hippocampus David Touretzky (CMU Comp. Sci.): hippocampus, rat navigation, animal learning Nathan Urban (CMU Bioogy): circuitry of the olfactory bulb Valerie Ventura (CMU Statistics): structure of neural firing patterns See http://www.cnbc.cmu.edu for further details. From dayan at gatsby.ucl.ac.uk Mon Dec 17 15:22:27 2001 From: dayan at gatsby.ucl.ac.uk (Peter Dayan) Date: Mon, 17 Dec 2001 20:22:27 +0000 (GMT) Subject: New Book : Theoretical Neuroscience Message-ID: <200112172022.UAA32375@flies.gatsby.ucl.ac.uk> Larry Abbott and I would like to announce our new book: Theoretical Neuroscience Computational and Mathematical Modeling of Neural Systems Peter Dayan and L. F. Abbott For more information, please visit http://people.brandeis.edu/~abbott/book Theoretical neuroscience provides a quantitative basis for describing what nervous systems do, determining how they function, and uncovering the general principles by which they operate. This text introduces the basic mathematical and computational methods of theoretical neuroscience and presents applications in a variety of areas including vision, sensory-motor integration, development, learning, and memory. The book is divided into three parts. Part I discusses the relationship between sensory stimuli and neural responses, focusing on the representation of information by the spiking activity of neurons. Part II discusses the modeling of neurons and neural circuits on the basis of cellular and synaptic biophysics. Part III analyzes the role of plasticity in development and learning. An appendix covers the mathematical methods used, and exercises are available on the book's Web site. Peter Dayan is on the faculty of the Gatsby Computational Neuroscience Unit at University College London. L. F. Abbott is the Nancy Lurie Marks Professor of Neuroscience and Director of the Volen Center for Complex Systems at Brandeis University. He is the coeditor of Neural Codes and Distributed Representations (MIT Press, 1999). 7 x 9, 476 pp., 165 illus. cloth ISBN 0-262-04199-5 From ftrjin at mail.ipm.net Thu Dec 13 04:47:12 2001 From: ftrjin at mail.ipm.net (Yaochu Jin) Date: Thu, 13 Dec 2001 10:47:12 +0100 (MET) Subject: CFP: Workshop on Approximation and Learning in EC Message-ID: <200112130908.KAA29306@mail.ipm.net> Call for Papers A workshop on ``Approximation and Learning in Evolutionary Computation'' is to be organized within the Genetic and Evolutionary Computation Conference (GECCO) from July 9 to July 13, 2002, New York City, USA. See further details at http://www.cs.unr.edu/~sushil/workshop/ . 1. Workshop Description In real-world applications, it is often necessary to build approximate models for fitness evaluation. One essential difficulty in applying evolutionary algorithms to the optimization of complex systems is the high time complexity of each fitness evaluation. Besides, in some applications, no explicit mathematical functions are available for fitness evaluation. Further more, approximate fitness models have also been proved useful in dealing with noisy and multi-modal fitness functions. This workshop aims to get together researchers coming from different research areas to see the state-of-art, to discuss the main problems and future work in this area. 2. Topics of Interests Submissions are invited in, but not limited to, any of the following areas: * Off-line and on-line learning for approximate model construction * Off-line and on-line learning for performance improvement * Evolution control and model management in evolutionary computation * Multi-level evolutionary optimization * Learning in multi-objective evolutionary optimization * Fitness estimation in noisy environment * Comparison of different modeling methods, such as neural networks, response surface and least squares methods, and probabilistic models for evolutionary computation * Comparison of different sampling techniques for on-line and off-linelearning 3. Submission Details Please follow the main conference guidelines with regards to the format of the paper. We expect submissions to be short papers or extended abstracts upto four (4) pages in length. Please send an electronic copy of the paper in PDF or postscript to yaochu_jin at de.hrdeu.com with subject ``GECCO workshop submission'' no later than March 4, 2002. Workshop proceedings will be published and will be available at the conference. Important dates: Paper submission deadline: March 4, 2002 Notification of acceptance: April 5, 2002 Final manuscript: April 25, 2002 4. Conferences Organizers Yaochu Jin Future Technology Research Honda R&D Europe Carl-Legien-Str. 30 63073 Offenbach/Main Germany Phone: +49-69-89011735 Fax: +49-69-89011749 Email: yaochu_jin at de.hrdeu.com yaochu.jin at hre-ftr.f.rd.honda.co.jp Sushil J. Louis University of Nevada, Reno Reno, NV 89557 U.S.A. Phone:(775)784-4315 Fax:(775)784-1877 Email: sushil at cs.unr.edu Khaled M. Rasheed Computer Science Department The University of Georgia Athens, GA 30602 U.S.A. Phone:(706)542-3444 Fax:(706)542-2966 Email: khaled at cs.uga.edu ------------------------------------------------------------------- Yaochu Jin Future Technology Research Honda R&D Europe (D) Carl-Legien-Str. 30 63073 Offenbach/Main GERMANY Tel: +49 69 89011735 Fax: +49 69 89011749 Email: yaochu.jin at hre-ftr.f.rd.honda.co.jp yaochu_jin at de.hrdeu.com Alias: yaochu.jin at ieee.org From juergen at idsia.ch Fri Dec 14 04:03:36 2001 From: juergen at idsia.ch (Juergen Schmidhuber) Date: Fri, 14 Dec 2001 10:03:36 +0100 Subject: reviewing Message-ID: <3C19C068.DF68B70@idsia.ch> A few comments on the recent discussion. The situation in theoretical physics heralds the things to come in other fields such as ours. In the early 1990s they were the first to institutionalize electronic publishing - astonishingly, computer science itself is a late-comer in this area. In theoretical physics, priority in the digital public archive has become pretty much the only thing that counts. Leading journals were forced to shorten the subsequent peer review process down to 2-3 months (!), otherwise most citations would go to digital preprints instead of journal papers. To a certain extent the "bidding-for-papers process" suggested by various contributors to this list is already evolving. More and more frequently, journal editors are approaching authors of interesting preprints, encouraging them to submit a version to their journal, listing rapid review among the incentives. How important is the peer review system anyway? Rustum Roy & James R. Ashburn (co-author of the 1:2:3 superconductor paper) recently wrote (Nature 414:6862, p394, Nov 2001): >>>...many leaders [...] such as Nobel laureates [...] regard peer review as a great hindrance to good science [...] An enormous amount of the best science has been and is run without the benefit of this rubric, as is the worldwide patent system [...] Everyone except the true believers know that it is your nearest competitors who often `peer' review your paper [...] The enormous waste of scientists' time, and the absolute, ineluctable bias against innovation, are its worst offences. `Review by competitors' is an all-too-accurate description of this system, wreaking devastation on papers and proposals [...] ... should not repeat the old canards such as:" despite the problems thrown up by peer review, no serious alternative has yet been proposed." Nonsense. They have not only been proposed but have been in regular use worldwide for a very long time. The users include the world's largest research agency [...] and industrial research worldwide.<<< I omitted many statements - do read the full letter. Fortunately, none of this criticism applies to connectionism and machine learning, where all reviewers are completely objective and unbiased :-) ------------------------------------------------- Juergen Schmidhuber director IDSIA, Galleria 2, 6928 Manno-Lugano, Switzerland juergen at idsia.ch http://www.idsia.ch/~juergen From bruns at cs.tu-berlin.de Fri Dec 14 06:05:32 2001 From: bruns at cs.tu-berlin.de (Camilla Bruns) Date: Fri, 14 Dec 2001 12:05:32 +0100 Subject: EU Advanced Course in Computational Neuroscience Message-ID: <200112141103.MAA17434@mail.cs.tu-berlin.de> EU ADVANCED COURSE IN COMPUTATIONAL NEUROSCIENCE (AN I.B.R.O. NEUROSCIENCE SCHOOL) August 19th - September 13th, 2002, OBIDOS, PORTUGAL DIRECTORS: Klaus Obermayer (Technical University Berlin, Germany) Alessandro Treves (SISSA, Trieste, Italy) Eilon Vaadia (Hebrew University, Jerusalem, Israel) Alain Destexhe (CNRS, Gif-sur-Yvette, France) LOCAL ORGANIZER: Vasco Galhardo (University of Porto, Portugal) The EU Advanced Course in Computational Neuroscience introduces students to the panoply of problems and methods of computational neuroscience, simultaneously addressing several levels of neural organisation, from sub-cellular processes to operations of the entire brain. The course consists of two complementary parts. A distinguished international faculty gives morning lectures on topics in experimental and computational neuroscience. The rest of the day is devoted to practical training, including learning how to use simulation software and how to implement a model of the system the student wishes to study on individual unix workstations. The course gradually introduces students to essential neuroscience concepts and to the most important techniques in modelling single cells, networks and neural systems. Students learn how to apply software packages like GENESIS, MATLAB, NEURON, XPP, etc. to the solution of their problems. The lectures will cover specific brain functions, each week topics ranging from modelling single cells and their biophysical properties to the simulation of simple circuits, large neuronal networks and system level models of the brain. The course ends with a presentation of the students' projects. The EU Advanced Course in Computational Neuroscience is designed for advanced graduate students and postdoctoral fellows in a variety of disciplines, including neuroscience, physics, electrical engineering, computer science and psychology. Students are expected to have a basic background in neurobiology as well as some computer experience. Students of any nationality can apply. A total of 30 students will be accepted. About 20 students will be from the European Union and affiliated countries (Iceland, Israel, Liechtenstein and Norway plus all countries which are negotiating future membership with the EU). These students are supported by the European Commission and we specifically encourage applications from researchers who work in less-favoured regions of the EU and women. There will be no tuition fee but students are expected to pay for travel and part of their subsidence costs. A limited number of fellowships will be available, further informations are on the course website under 'fellowships'. More information and application forms can be obtained: http://www.neuroinf.org/courses Please apply electronically only, using a web browser. Contact address: - mail: Camilla Bruns, Technical University Berlin Faculty of Computer Science, FR 2-1 Franklinstr. 28/29 10587 Berlin, Germany Phone: +49-(0)30-314-73442 Fax: +49-(0)30-314-73121 - e-mail: bruns at cs.tu-berlin.de APPLICATION DEADLINE: April 3, 2002 Applicants will be notified of the results of the selection procedures by May 20, 2002. From Steven_Sloman at brown.edu Fri Dec 14 14:21:34 2001 From: Steven_Sloman at brown.edu (Steven Sloman) Date: Fri, 14 Dec 2001 14:21:34 -0500 Subject: Post-doc at Brown Message-ID: <3C1A5138.33FDC0BF@brown.edu> BROWN UNIVERSITY. Post-doctoral positions available for cognitive or computational scientist. As part of an NSF award to Brown University through the IGERT program, the Departments of Cognitive and Linguistic Sciences, Computer Science, and Applied Mathematics are hiring research associates. The associates should be scholars who have displayed interest and ability in conducting collaborative interdisciplinary research involving a combination of computational and empirical approaches to one of the content areas of the program: cognition, language, or vision. As well as participating in collaborative research, responsibilities will include helping to coordinate cross-departmental events as well as some graduate teaching. Applicants must hold a PhD in Psychology, Linguistics, Cognitive Science, Computer Science, Mathematics, Applied Mathematics, or a related discipline, or show evidence that the PhD will be completed before the start of the position. Applicants should send a vita, a short research statement, three letters of reference, and other supporting material (e.g., representative publications if available), to IGERT Post-doc Search, Department of Cognitive and Linguistic Sciences, Brown University, Box 1978, Providence, RI 02912. Special consideration will be given to those applicants whose research is relevant to at least two of the participating departments. The positions are open immediately for one year, renewable upon satisfactory completion of duties. Salaries will be between $35,000 and $45,000 per year. All materials must be received by Feb. 15, 2002, for full consideration. Like all NSF-funded programs, this opportunity is available only to American citizens and permanent residents. Brown University is an Equal Opportunity/Affirmative Action Employer. For additional information about the program and ongoing research initiatives please visit our website at: http://www.cog.brown.edu/IGERT From marcus at idsia.ch Fri Dec 14 13:35:08 2001 From: marcus at idsia.ch (Marcus Hutter) Date: Fri, 14 Dec 2001 19:35:08 +0100 Subject: Review Time Page Message-ID: <016201c184ce$0f420980$65bfb0c3@idsia.ch> Dear connectionists and other computer scientists, following the discussion on reviewing process in general and reviewing time in particular, I created a page intended to provide a list of average reviewing/revision/publication time of computer science journals. Reviewing time is definitely not the only important measure. Other quantifiable information may be added to the page in time. Still, before deciding to submit something to a particular journal, authors may be interested in the expected waiting time until publication of their submission. And journal editors may be interested whether their journals occupy the top or flop positions regarding reviewing time. Currently the page is virtually empty. Its success relies on your contribution. Please use the form on the web page http://www.idsia.ch/~marcus/journals.htm to submit your own recent experiences with various journals. Suggestions for improvement are welcome. Thanks in advance for your help! Marcus Hutter -------------------------------- Dr. Marcus Hutter, IDSIA Istituto Dalle Molle di Studi sull'Intelligenza Artificiale Galleria 2 CH-6928 Manno(Lugano) - Switzerland Phone: +41-91-6108668 Fax: +41-91-6108661 E-mail marcus at idsia.ch http://www.idsia.ch/~marcus From sfr at unipg.it Sun Dec 16 12:43:00 2001 From: sfr at unipg.it (Simone G.O. Fiori (Pg)) Date: Sun, 16 Dec 2001 18:43:00 +0100 Subject: New papers on neural blind signal processing. Message-ID: <1.5.4.32.20011216174300.01ba5050@unipg.it> Dear Colleagues, I would like to announce three new papers on blind signal processing by neural networks, which might be of interest to people working on principal/independent component analysis, blind system deconvolution, learning on Stiefel-manifold, and probability structure identification. Best wishes for the incoming new year! Kind regards, Simon. =========================================================================== "Blind Deconvolution by Simple Adaptive Activation Function Neuron", S. Fiori, Neurocomputing (full paper) The `Bussgang' algorithm is one among the most known blind deconvolution techniques in the adaptive signal processing literature. It relies on a Bayesian estimator of the source signal that requires the prior knowledge of the source statistics as well as the deconvolution noise characteristics. In this paper we propose to implement the estimator with a simple adaptive activation function neuron, whose activation function is endowed with one learnable parameter; in this way the algorithm does not require to hypothesize deconvolution noise level. Neuron's weights adapt through an unsupervised learning rule that closely recalls non-linear minor component analysis. In order to assess the effectiveness of the proposed method, computer simulations are presented and discussed. Downloadable at: http://www.unipg.it/~sfr/publications/NEUCOM2001.ps ============================================================================ "Probability Density Function Learning by Unsupervised Neurons", S. Fiori, Int. Journal of Neural Systems (full paper) In a recent work we introduced the concept of pseudo-polynomial adaptive activation function neuron (FAN) and presented an unsupervised information- theoretic learning theory for such structure. The learning model is based on entropy optimization and provides a way of learning probability distributions from incomplete data. The aim of the present paper is to illustrate some theoretical features of the FAN neuron, to extend its learning theory to asymmetrical density function approximation, and to provide an analytical and numerical comparison with other known density function estimation methods, with special emphasis to the universal approximation ability. The paper also provides a large survey of PDF approximation via functional expansion on orthogonal bases wrt weighting kernels, which lead to eg the Gram-Charlier expansion, and of PDF learning from incomplete data, as well as results of several experiments performed on real-world problems and signals. One of the experiment presents preliminary results about statistical characterization of the macro- mechanical properties of polypropylene composites reinforced with natural fibers. Downloadable at: http://www.unipg.it/~sfr/publications/IJNS2001.zip ============================================================================ "A Theory for Learning Based on Rigid-Bodies Dynamics", S. Fiori, IEEE Transactions on Neural Networks (full paper) A new learning theory derived from the study of the dynamics of an abstract system of masses, rigidly constrained over mutually-orthogonal immaterial axes and moving in a multidimensional space under an external force field, is presented. The set of rational-kinematic equations describing system's dynamics may be directly interpreted as a learning algorithm for neural layers which preserve the ortho-normality of the connection matrices; as a consequence, the proposed learning theory belongs to the class of strongly-constrained learning paradigms that allow a neural network to learn connection patterns over orthogonal group. Relevant properties of the proposed learning theory are discussed within the paper, along with results of computer simulations performed in order to assess its effectiveness in applied fields. The connections with the general theory of Stiefel-flow learning and the Riemannian gradient theory are also discussed, and the experiments concern optimal data compression by the PCA and signal separation by the ICA. This paper summarizes the work done by the Author on this topic during the last five years. Downloadable at: http://www.unipg.it/~sfr/publications/TNN2001.zip =================================================== Dr Simone Fiori (EE, PhD)- Assistant Professor Dept. of Industrial Engineering (IED) University of Perugia (UNIPG) Via Pentima bassa, 21 - 05100 TERNI (Italy) eMail: sfr at unipg.it - Fax: +39 0744 492925 Web: http://www.unipg.it/~sfr/ =================================================== From John.Carney at PredictionDynamics.com Tue Dec 18 10:50:34 2001 From: John.Carney at PredictionDynamics.com (Dr. John Carney) Date: Tue, 18 Dec 2001 15:50:34 +0000 Subject: JOB ANNOUNCEMENT: Machine Learning Researchers Message-ID: <5.1.0.14.0.20011218143844.02c49908@192.168.2.1> MACHINE LEARNING RESEARCHERS ============================= Prediction Dynamics is a rapidly growing and well-funded software company based in Dublin, Ireland. Our technology leverages the power of machine learning and computational statistics techniques to build powerful non-parametric multi-factor models of financial markets. See www.PredictionDynamics.com for more details. The Product Innovation Group at Prediction Dynamics is currently seeking to recruit a number of researchers with demonstrated expertise in machine learning. Working in the Product Innovation Group, you will be part of a team that is responsible for driving innovation in our core modeling technology. You must be a creative thinker with strong software development and written communication skills. The key responsibilities of this role include: * Researching ground-breaking new approaches to financial time-series modeling using machine learning methods * Implementing these techniques in code and testing them using live financial market data * Publishing technical articles and providing thought leadership Background and experience: * Ph.D. in Machine Learning, Statistics, Computer Science, or a related quantitative discipline * Broad knowledge of most of the following and a specialist knowledge of any one of the following: - Rule extraction - Neural network ensembles - Feature selection - Computational statistics - Time-series modeling - Other machine learning methods e.g. decision trees, k-nearest neighbour * Strong software engineering skills are desirable, especially in C/C++ * Creative thinker, strong written communication skills and a team player A range of experience levels will be considered including those who recently completed a Ph.D./Postdoc and Ph.D.s with several years academic or commercial experience. Prediction Dynamics will offer suitable candidates excellent packages including a competitive salary, stock options, health insurance and pension benefits. The Product Innovation Group is located at our headquarters in Dublin, Ireland. Applicants are asked to send a Resume/CV by e-mail to John.Carney at PredictionDynamics.com. __________________________________ Dr. John Carney Prediction Dynamics 7-8 Mount Street Crescent Dublin 2 Ireland Tel: +353 (1) 439 5000 Fax: +353 (1) 439 5050 Web: www.PredictionDynamics.com ___________________________________ From tgd at cs.orst.edu Mon Dec 17 23:55:24 2001 From: tgd at cs.orst.edu (Thomas G. Dietterich) Date: Mon, 17 Dec 2001 20:55:24 -0800 Subject: reviewing In-Reply-To: <3C19C068.DF68B70@idsia.ch> (message from Juergen Schmidhuber on Fri, 14 Dec 2001 10:03:36 +0100) References: <3C19C068.DF68B70@idsia.ch> Message-ID: <9601-Mon17Dec2001205524-0800-tgd@cs.orst.edu> Hi Juergen, It may be that Nobel prize winners don't benefit from peer review, but I know that many of my papers have been improved as a result of peer review. If you read the acknowledgements sections of the papers published in Machine Learning, Neural Computation, and JMLR, you will often see the authors thanking the referees. I know of several cases where the referees not only identified bugs in proofs, but helped strengthen theorems and simplify proofs. Why is there this difference between machine learning and other discplines? Perhaps because in our young discipline research is not nearly as competitive as it is in mature fields such as physics and biology. A difficulty with physics and biology is that you and your competitors are studying the *same system* and trying to answer exactly the *same questions*. It is a race to publish, "priority" matters, and unscrupulous reviewers can delay a paper unfairly. But in computer science, perhaps because it is a "Science of the Artificial", most work involves developing frameworks, perspectives, analytical techniques, and models, and these rarely compete directly. For all of these, peer review can play an important role in checking the proofs, clarifying the ideas, and improving the presentation. In this way, I think peer review advances the field rather than holding it back. --Tom -- Thomas G. Dietterich Voice: 541-737-5559 Department of Computer Science FAX: 541-737-3014 Dearborn Hall 102 URL: http://www.cs.orst.edu/~tgd Oregon State University Corvallis, OR 97331-3102 From ken at phy.ucsf.edu Tue Dec 18 01:19:57 2001 From: ken at phy.ucsf.edu (Ken Miller) Date: Mon, 17 Dec 2001 22:19:57 -0800 Subject: Paper available: Coding in the cat LGN Message-ID: <15390.57357.976039.276607@coltrane.ucsf.edu> The following paper is available from ftp://ftp.keck.ucsf.edu/pub/ken/LGNPaper.pdf or from http://www.keck.ucsf.edu/~ken (click on 'Publications', then on 'Experimental Results') Liu, R.C., S. Tzonev, S. Rebrik and K.D. Miller (2001). "Variability and information in a neural code of the cat lateral geniculate nucleus." This is a final draft of a paper that has now appeared as Journal of Neurophysiology 86, 2789-2806. Abstract: A central theme in neural coding concerns the role of response variability and noise in determining the information transmission of neurons. This issue was investigated in single cells of the lateral geniculate nucleus of barbiturate anesthetized cats by quantifying the degree of precision in and the information transmission properties of individual spike train responses to full field, binary (bright or dark), flashing stimuli. We found that neuronal responses could be highly reproducible in their spike timing (about 1-2 ms standard deviation) and spike count (about 0.3 ratio of variance/mean, compared to 1.0 expected for a Poisson process). This degree of precision only became apparent when an adequate length of the stimulus sequence was specified to determine the neural response, emphasizing that the variables relevant to a cell's response must be controlled in order to observe the cell's intrinsic response precision. Responses could carry as much as 3.5 bits/spike of information about the stimulus, a rate that was within a factor of two of the limit the spike train can transmit. Moreover, there appeared to be little sign of redundancy in coding: on average, longer response sequences carried at least as much information about the stimulus as would be obtained by adding together the information carried by shorter response sequences considered independently. There also was no direct evidence found for synergy between response sequences. These results could largely, but not entirely, be explained by a simple model of the response in which one filters the stimulus by the cell's impulse response kernel, thresholds the result at a fairly high level, and incorporates a post-spike refractory period. Ken Kenneth D. Miller telephone: (415) 476-8217 Associate Professor fax: (415) 476-4929 Dept. of Physiology, UCSF internet: ken at phy.ucsf.edu 513 Parnassus www: http://www.keck.ucsf.edu/~ken San Francisco, CA 94143-0444 From robtag at unisa.it Wed Dec 19 11:40:36 2001 From: robtag at unisa.it (Roberto) Date: Wed, 19 Dec 2001 17:40:36 +0100 Subject: Call for paper WIRN 2002 Message-ID: <3C20C304.8070101@unisa.it> The 13-th Italian Workshop on Neural Nets WIRN VIETRI-2002 May 30 - June 1, 2002,Vietri Sul Mare, Salerno ITALY CALL FOR PAPERS - FIRST ANNOUNCEMENT Organizing - Scientific Committee B. Apolloni (Univ. Milano), A. Bertoni (Univ. Milano), N. A. Borghese (CNR Milano), D. D. Caviglia (Univ. Genova), P. Campadelli (Univ. Milano), A. Chella (Univ. Palermo), A. Colla (ELSAG Genova), A. Esposito (I.I.A.S.S.), M. Frixione (Univ. Salerno), C. Furlanello (ITC-IRST Trento), G. M. Guazzo (I.I.A.S.S.), M. Gori (Univ. Siena), F. Lauria (Univ. Napoli), M. Marinaro (Univ. Salerno), F. Masulli (Univ. Pisa), C. Morabito (Univ. Reggio Calabria), P. Morasso (Univ. Genova), G. Orlandi (Univ. Roma), T. Parisini (Politecnico Milano), E. Pasero (Politecnico Torino), A. Petrosino (CNR Napoli), V. Piuri (Politecnico Milano), R. Serra (CRA Montecatini Ravenna), F. Sorbello (Univ. Palermo), A. Sperduti (Univ. Pisa), R. Tagliaferri (Univ. Salerno) Topics Mathematical Models, Architectures and Algorithms, Hardware and Software Design, Hybrid Systems, Pattern Recognition and Signal Processing, Industrial and Commercial Applications, Fuzzy Tecniques for Neural Networks Schedule Papers Due: February 15, 2002 Replies to Authors: April 15, 2002 Revised Papers Due: June 1, 2002 Sponsors International Institute for Advanced Scientific Studies (IIASS) "E.R. Caianiello" Dept. of Scienze Fisiche "E.R. Caianiello", University of Salerno Dept. of Matematica ed Informatica, University of Salerno Dept. of Scienze dell'Informazione, University of Milano Societa' Italiana Reti Neuroniche (SIREN) IEEE Neural Network Council INNS/SIG Italy Istituto Italiano per gli Studi Filosofici, Napoli The three-day conference, to be held in the I.I.A.S.S., will feature both introductory tutorials and original, refereed papers, to be published by an International Publishing Company (?) . Official languages are Italian and English, while papers must be in English. Papers should be 6 pages, including title, figures, tables, and bibliography. The accompanying letter should give keywords, postal and electronic mailing addresses, telephone and FAX numbers, indicating oral or poster presentation. Submit 3 copies and a 1 page abstract (containing keywords, postal and electronic mailing addresses, telephone, and FAX numbers with no more than 300 words) to the address shown (WIRN 2002 c/o IIASS). An electronic copy of the abstract should be sent to the E-mail address below. During the Workshop the "Premio E.R. Caianiello" will be assigned to the best Ph.D. thesis in the area of Neural Nets and related fields of Italian researchers. The amount is of 1.000 Euros. The interested researchers (with the Ph.D degree obtained after January 1, 1999 and before March 31 2002) must send 3 copies of a c.v. and of the thesis to "Premio Caianiello" WIRN 2002 c/o IIASS before April 10,2002. A candidate can submit his Ph. D. thesis at most twice. Only SIREN associated are admitted (subscription forms can be downloaded from the SIREN site). For more information, contact the Secretary of I.I.A.S.S. "E.R. Caianiello", Via G.Pellegrino, 19, 84019 Vietri Sul Mare (SA), ITALY Tel. +39 89 761167 Fax +39 89 761189 E-Mail robtag at unisa.it or the SIREN www pages at: http://www-dsi.ing.unifi.it/neural From jose.dorronsoro at iic.uam.es Thu Dec 20 02:39:58 2001 From: jose.dorronsoro at iic.uam.es (Jose Dorronsoro) Date: Thu, 20 Dec 2001 08:39:58 +0100 Subject: ICANN 2002 Final Call for Papers Message-ID: <1.5.4.32.20011220073958.00bf2e48@iic.uam.es> Note: efforts have been made to avoid duplicate postings of this message. Apologies if, nevertheless, you are getting them. ICANN 2002 Second and Final Call for Papers The 12th International Conference on Artificial Neural Networks, ICANN 2002, will be held from August 27 to August 30 2002 at the Universidad Autnoma de Madrid, Spain. ICANN 2002 welcomes contributions on Theory, Algorithms, Applications and Implementations on the following broad Areas: Computational Neuroscience Data Analysis and Pattern Recognition Vision and Image Processing Robotics and Control Signal and Time Series Processing Connectionist Cognitive Science Selforganization. An independent Call for Tutorials, Workshops and Special Sessions has also been issued. You can find more details on this and other ICANN 2002 matters at its web site, www.ii.uam.es/icann2002. ICANN Proceedings will be published in the "Lecture Notes in Computer Science" series of Springer-Verlag. Paper length is restricted to a maximum of 6 pages, including figures. Detailed author instructions are also available at the web site. Submissions will be possible by file uploading or e-mail attach of postscript or pdf files, and also surface mail. All submissions will require to fill out electronically a paper information page. The web pages for this and for file uploads will open in January 7 2002 at the ICANN 2002 site. More details on these matters can also be found in the author instructions. Important deadlines are End of submission receptions: February 15, 2002. Notification of acceptance/rejection: April 15, 2002. Final papers due (in hardcopy and electronically): May 15, 2002. The Conference Calendar will be: August 27, 2002: Tutorials and Workshops August 28-31, 2002: ICANN 2002 Conference For further information and/or contacts, send inquiries to icann2002 at ii.uam.es or to ICANN 2002 Conference Secretariat Mrs. Juana Calle Escuela Tcnica Superior de Informtica Universidad Autnoma de Madrid 28049 Madrid, Spain Jos Dorronsoro ICANN 2002 Chairman jose.dorronsoro at iic.uam.es From S.M.Bohte at cwi.nl Thu Dec 20 03:29:58 2001 From: S.M.Bohte at cwi.nl (Sander Bohte) Date: Thu, 20 Dec 2001 09:29:58 +0100 Subject: Paper available: hebbian learning with time spikes Message-ID: <000201c18930$83d38ec0$81f4a8c0@cwi.nl> The following paper, on computing with precisely times spiking neurons, is available from http://www.cwi.nl/~sbohte/publication/usnnrep.pdf or from http://www.cwi.nl/~sbohte/pub_usnn2k2.htm S.M. Bohte, H. La Poutre and J.N. Kok (2002). "Unsupervised Clustering with Spiking Neurons by Sparse Temporal Coding and Multi-Layer RBF Networks." This is a final draft of a paper that will appear in IEEE Transactions on Neural Networks (2002). Abstract: We demonstrate that spiking neural networks encoding information in the timing of single spikes are capable of computing and learning clusters from realistic data. We show how a spiking neural network based on spike-time coding and Hebbian learning can successfully perform unsupervised clustering on real-world data, and we demonstrate how temporal synchrony in a multi-layer network can induce hierarchical clustering. We develop a temporal encoding of continuously valued data to obtain adjustable clustering capacity and precision with an efficient use of neurons: input variables are encoded in a population code by neurons with graded and overlapping sensitivity profiles. We also discuss methods for enhancing scale-sensitivity of the network and show how the induced synchronization of neurons within early RBF layers allows for the subsequent detection of complex clusters. Keywords: Spiking neurons, unsupervised learning, high-dimensional clustering, complex clusters, Hebbian-learning, synchronous firing, sparse coding, temporal coding, coarse coding. Sander ===================================== Sander Bohte The Netherlands Center for Mathematics and Computer Science (CWI) Dept SEN4 tel: +31-20 592 4926 Kruislaan 413 fax: +31-20 592 4199 NL-1098 SJ Amsterdam www: http://www.cwi.nl/~sbohte The Netherlands mail: sbohte at cwi.nl From erik at bbf.uia.ac.be Thu Dec 20 08:57:38 2001 From: erik at bbf.uia.ac.be (Erik De Schutter) Date: Thu, 20 Dec 2001 14:57:38 +0100 Subject: CNS*2002: Call for papers Message-ID: CALL FOR PAPERS: APPLICATION DEADLINE: February 8, 2002 midnight GMT Eleventh Annual Computational Neuroscience Meeting CNS*2002 July 21 - July 25, 2002 Chicago, Illinois USA http://www.neuroinf.org/CNS.shtml Info at cp at bbf.uia.ac.be CNS*2002 will be held in Chicago from Sunday, July 21, 2002 to Thursday, July 25 in the Congress Plaza Hotel & Convention Center. This is a historic hotel located on Lake Michigan in downtown Chicago. General sessions will be Sunday-Wednesday, Thursday will be a full day of workshops. The conference dinner will be Wednesday night, followed by the rock-n-roll jam session. Papers can include experimental, model-based, as well as more abstract theoretical approaches to understanding neurobiological computation. We especially encourage papers that mix experimental and theoretical studies. We also accept papers that describe new technical approaches to theoretical and experimental issues in computational neuroscience or relevant software packages. The paper submission procedure is new this year: it is at a different web site and makes use of a preprint server. This allows everybody to view papers before the actual meeting and to engage in discussions about submitted papers. PAPER SUBMISSION Papers for the meeting can be submitted ONLY through the web site at http://www.neuroinf.org/CNS.shtml. Papers can be submitted either old style (a 100 word abstract followed by a 1000 word summary) or as a full paper (max 6 typeset pages). In both cases the abstract (100 words max) will be published in the conference program. Submission will occur through a preprint server run by Elsevier, more information can be found on the submission web site. Authors have the option of declaring their submission restricted access, not making it publicly visible. All submissions will be acknowledged by email. It is important to note that this notice, as well as all other communication related to the paper will be sent to the designated correspondence author only. THE REVIEW PROCESS All submitted papers will be first reviewed by the program committee. Papers will be judged and accepted for the meeting based on the clarity with which the work is described and the biological relevance of the research. For this reason authors should be careful to make the connection to biology clear. We reject only a small fraction of the papers (~ 5%) and this usually based on absence of biological relevance (e.g. pure artificial neural networks). We expect to notify authors of meeting acceptance before end of March. The second stage of review involves evaluation of each submission by two independent referees. The primary objective of this round of review will be to select papers for oral and featured oral presentation. In addition to perceived quality as an oral presentation, the novelty of the research and the diversity and coherence of the overall program will be considered. To ensure diversity, those who have given talks in the recent past will not be selected and multiple oral presentations from the same lab will be discouraged. A second objective of the review is to rank papers for inclusion in the conference proceedings. All accepted papers not selected for oral talks as well as papers explicitly submitted as poster presentations will be included in one of three evening poster sessions. Authors will be notified of the presentation format of their papers by end of April. CONFERENCE PROCEEDINGS The proceedings volume is published each year as a special supplement to the journal Neurocomputing. In addition the proceedings are published in a hardbound edition by Elsevier Press. Only papers which are made publicly available on the preprint server, which are presented at the CNS meeting and which are not longer than 6 typeset pages will be eligible for inclusion in the proceedings. Authors who only submitted a 1000 word symmary will be required to submit a full paper to the preprint server. The proceedings size is limited to 1200 pages (about 200 papers). In case more papers are eligible the lowest ranked papers will not be included in the proceedings but will remain available on the preprint server. Authors will be advised of the status of their papers immediately after the CNS meeting. Submission of final papers will be through the preprint server with a deadline early October. For reference, papers presented at CNS*99 can be found in volumes 32-33 of Neurocomputing (2000) and those of CNS*00 in volumes 38-40 (2001). INVITED SPEAKERS: Ad Aertsen (Albert-Ludwigs-University, Germany) Leah Keshet (University British Columbia, Canada) Alex Thomson (University College London, UK) ORGANIZING COMMITTEE: Program chair: Erik De Schutter (University of Antwerp, Belgium) Local organizer: Philip Ulinski (University of Chicago, USA) Workshop organizer: Maneesh Sahani (Gatsby Computational Neuroscience Unit, UK) Government Liaison: Dennis Glanzman (NIMH/NIH, USA) Program Committee: Upinder Bhalla (National Centre for Biological Sciences, India) Avrama Blackwell (George Mason University, USA) Victoria Booth (New Jersey Institute of Technology, USA) Alain Destexhe (CNRS Gif-sur-Yvette, France) John Hertz (Nordita, Denmark) David Horn (University of Tel Aviv, Israel) Barry Richmond (NIMH, USA) Steven Schiff (George Mason University, USA) Todd Troyer (University of Maryland, USA) From Johan.Suykens at esat.kuleuven.ac.be Thu Dec 20 10:12:05 2001 From: Johan.Suykens at esat.kuleuven.ac.be (Johan Suykens) Date: Thu, 20 Dec 2001 16:12:05 +0100 (MET) Subject: NATO-ASI on Learning Theory and Practice Message-ID: <200112201512.QAA10354@euler.esat.kuleuven.ac.be> ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ NATO Advanced Study Institute on Learning Theory and Practice (LTP 2002) July 8-19 2002 - K.U. Leuven Belgium http://www.esat.kuleuven.ac.be/sista/natoasi/ltp2002.html ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ -General Objective- This NATO Advanced Study Institute on Learning Theory and Practice aims at creating a fascinating interplay between advanced fundamental theory and several application areas such as bioinformatics, multimedia/computer vision, e-commerce finance, internet search, textmining and others. It offers an interdisciplinary forum for presenting recent progress and breakthroughs in learning theory with respect to several areas as neural networks, machine learning, mathematics and statistics. -Invited Lecturers- Peter Bartlett (Australian National University Canberra, AUS) Kristin Bennett (Rensselaer Polytechnic Institute New York, USA) Chris Bishop (Microsoft Research Cambridge, UK) Nello Cristianini (Royal Holloway London, UK) Luc Devroye (McGill University Montreal, CAN) Lazlo Gyorfi (T.U. Budapest, HUN) Gabor Horvath (T.U. Budapest, HUN) Rudolf Kulhavy (Honeywell Prague Laboratory, CZ) Vera Kurkova (Academy of Sciences of the Czech Republic, CZ) Joerg Lemm (University of Muenster, GER) Charles Micchelli (IBM T.J. Watson, USA) Tomaso Poggio (MIT, USA) Massimiliano Pontil (University of Siena, IT) Bernhard Schoelkopf (Max-Planck-Institute Tuebingen, GER) Yoram Singer (Hebrew University Jerusalem, IS) Steve Smale (U.C. Berkeley, USA) Johan Suykens (K.U. Leuven, BEL) Vladimir Vapnik (AT&T Labs Research, USA) Mathukumalli Vidyasagar (Tata Consultancy Services, IND) -Organizing committee- Johan Suykens (K.U. Leuven, BEL), Director Gabor Horvath (T.U. Budapest, HUN), Co-director partner country Joos Vandewalle (K.U. Leuven, BEL) Sankar Basu (IBM T.J. Watson, USA) Charles Micchelli (IBM T.J. Watson, USA) -Program and participation- According to the NATO rules http://www.nato.int/science the number of ASI students will be limited to 80. All participants will obtain a *free* registration (including welcome reception, lunches, banquets, refreshments and a NATO-ASI Science Series book to be published with IOS Press). Limited additional funding will be available to cover attendance costs. All interested participants should fill out an application form, taking into account the NATO restrictions. Application form and preliminary program are available at http://www.esat.kuleuven.ac.be/sista/natoasi/ltp2002.html -Venue- The Advanced Study Institute will take place in the Arenberg Castle of the K.U. Leuven Heverlee. The place is surrounded by several restaurants/cafes and parks where one may have a relaxing walk. The historical town of Leuven is within walking distance from the meeting site. Leuven is also well-known for its pleasant atmosphere, pubs and restaurants. -Housing- In addition to hotels rooms, blocks of low cost student rooms are reserved for the ASI students. The student rooms and hotels are located within walking distance from the Arenberg castle meeting site. In order to stimulate the interaction among the participants the option of student rooms will be recommended to all ASI students. -Important Dates- Deadline submission of application form: March 18, 2002 Notification of acceptance: April 30, 2002 NATO-ASI LTP 2002 meeting: July 8-19, 2002 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ From bard at math.pitt.edu Thu Dec 20 13:50:49 2001 From: bard at math.pitt.edu (G. Bard Ermentrout) Date: Thu, 20 Dec 2001 13:50:49 -0500 (EST) Subject: Electronic submission for JCNS Message-ID: Announcing electronic manuscript submission and review for The Journal of Computational Neuroscience Kluwer Academic Publishers is very pleased to announce an agreement with Aries Systems Inc for making use of their fully customized, web-enabled manuscript submission, review and tracking system. Starting December 17, 2001, The Journal of Computational Neuroscience will start to accept online submissions and provide online review services. Authors, editors and reviewers can make use of this system via a special click-able button - My Manuscripts - on the journal's home page http://www.wkap.nl/journals/jcns Processing of manuscripts and communications with authors, editors and reviewers will be entirely electronic. This will reduce the review time substantially as no time is lost in the mail. Authors can submit manuscripts using computer programs they are familiar with, as the system automatically converts, on the fly, submission source files from Word, WordPerfect, .RTF, LaTeX2e, text files, Adobe Postscript files, PDF files, GIF, TIFF, JPEG, PICT graphic files into a single PDF for review distribution. Authors are also entitled to download this PDF file for their own use. Authors can check the status of their manuscripts 24 hours a day, 7 days per week. Role-based (author, editor, reviewer, publisher) security and confidentially is ensured by requiring a user name and password. (The system automatically generates a password when submitting a new manuscript and people can select their own user name). This role-based configuration limits access to a person's role and enables a single- or double-blind review system. Journal of Computational Neuroscience will consider manuscripts either sent by mail or electronically. Manuscripts sent by mail should contain a floppy disk with the electronic file so that the Editorial Office staff can enter the manuscript into the review system and handle it by proxy. Should you have any queries or encounter any problems, please do not hesitate to contact Ms Karen Cullen e-mail: karen.cullen at wkap.com tel: +1 781 871 6600 After extensive internal and external testing of this online submission, review and tracking system we are confident that the service to our authors, editors and reviewers is considerably improved. Your support and cooperation is very much appreciated. Bard Ermentrout Barry Richmond Editors From meesad at okstate.edu Thu Dec 20 10:37:23 2001 From: meesad at okstate.edu (Phayung Meesad) Date: Thu, 20 Dec 2001 09:37:23 -0600 Subject: Extended Call for Papers: IJCNN 2002 (Deadline Dec 24, 2001) Message-ID: <006501c1896c$3821d860$fa384e8b@okstate.edu> Extended Call for Papers: IJCNN 2002 *** Submission Deadline is December 24, 2001. ****** The deadlines for WCCI submissions have been revised in consideration of the recently held FUZZ-IEEE01 meeting (December 2-5, 2001, Melbourne, Australia). Please take advantage of the new December 24, 2001 deadline for submissions to IJCNN. ************************************************************************* * CALL FOR PAPERS 2002 International Joint Conference on Neural Networks (IJCNN2002) May 12-17, 2002 Hilton Hawaiian Village, Honolulu, HI Held as part of the World Congress on Computational Intelligence (http://www.wcci2002.org) The annual IEEE/INNS International Joint Conference on Neural Networks (IJCNN), is one of the premier international conferences in the field. It covers all topics in neural networks, including but not limited to: - supervised, unsupervised and reinforcement learning, - hardware implementation, - time series analysis, - neurooptimization, - neurocontrol, - hybrid architectures, - bioinformatics, - neurobiology and neural modeling, - embedded neural systems, - intelligent agents, - image processing, - rule extraction, - statistics, - chaos, - learning theory, - and a huge variety of applications. The emphasis of the Congress will be on original theories and novel applications of neural networks. The Congress welcomes paper submissions from researchers, practitioners, and students worldwide. IJCNN 2002 will be held in conjunction with the Congress on Evolutionary Computation (CEC) and the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) as part of the World Congress on Computational Intelligence (WCCI). Crossfertilization of the three fields will be strongly encouraged. The Congress will feature keynote speeches and tutorials by world-leading researchers. It also will include a number of special sessions and workshops on the latest hot topics. Your registration admits you to all events and includes the World Congress proceedings and banquet. The new deadline for 6-page paper review submissions is December 24, 2001. The submissions page: https://commerce9.pair.com/nnc/conferences/wcci2002/ijcnn/review/upload.phps Look for more details at http://www.wcci2002.org.=20 From cns at cns.bu.edu Thu Dec 20 14:01:51 2001 From: cns at cns.bu.edu (Boston University CNS Department) Date: Thu, 20 Dec 2001 14:01:51 -0500 Subject: No subject Message-ID: <3C22359F.6050100@cns.bu.edu> PLEASE POST ******************************************************************* GRADUATE TRAINING IN THE DEPARTMENT OF COGNITIVE AND NEURAL SYSTEMS (CNS) AT BOSTON UNIVERSITY ******************************************************************* The Boston University Department of Cognitive and Neural Systems offers comprehensive graduate training in the neural and computational principles, mechanisms, and architectures that underlie human and animal behavior, and the application of neural network architectures to the solution of technological problems. The brochure may also be viewed on line at: http://www.cns.bu.edu/brochure/ and application forms at: http://www.bu.edu/cas/graduate/application. html Applications for Fall 2002 admission and financial aid are now being accepted for both the MA and PhD degree programs. To obtain a brochure describing the CNS Program and a set of application materials, write, telephone, or fax: DEPARTMENT OF COGNITIVE AND NEURAL SYSTEMS Boston University 677 Beacon Street Boston, MA 02215 617/353-9481 (phone) 617/353-7755 (fax) or send via email your full name and mailing address to the attention of Mr. Robin Amos at: amos at cns.bu.edu Applications for admission and financial aid should be received by the Graduate School Admissions Office no later than January 15. Late applications will be considered until May 1; after that date applications will be considered only as special cases. Applicants are required to submit undergraduate (and, if applicable, graduate) transcripts, three letters of recommendation, and Graduate Record Examination (GRE) scores. The Advanced Test should be in the candidate's area of departmental specialization. GRE scores may be waived for MA candidates and, in exceptional cases, for PhD candidates, but absence of these scores will decrease an applicant's chances for admission and financial aid. Non-degree students may also enroll in CNS courses on a part-time basis. ******************************************************************* Description of the CNS Department: The Department of Cognitive and Neural Systems (CNS) provides advanced training and research experience for graduate students and qualified undergraduates interested in the neural and computational principles, mechanisms, and architectures that underlie human and animal behavior, and the application of neural network architectures to the solution of technological problems. The department's training and research focus on two broad questions. The first question is: How does the brain control behavior? This is a modern form of the Mind/Body Problem. The second question is: How can technology emulate biological intelligence? This question needs to be answered to develop intelligent technologies that are well suited to human societies. These goals are symbiotic because brains are unparalleled in their ability to intelligently adapt on their own to complex and novel environments. Models of how the brain accomplishes this are developed through systematic empirical, mathematical, and computational analysis in the department. Autonomous adaptation to a changing world is also needed to solve many of the outstanding problems in technology, and the biological models have inspired qualitatively new designs for applications. During the past decade, CNS has led the way in developing biological models that can quantitatively simulate the dynamics of identified brain cells in identified neural circuits, and the behaviors that they control. This new level of understanding is leading to comparable advances in intelligent technology. CNS is a graduate department that is devoted to the interdisciplinary training of graduate students. The department awards MA, PhD, and BA/MA degrees. Its students are trained in a broad range of areas concerning computational neuroscience, cognitive science, and neuromorphic systems. The biological training includes study of the brain mechanisms of vision and visual object recognition; audition, speech, and language understanding; recognition learning, categorization, and long-term memory; cognitive information processing; self-organization and development, navigation, planning, and spatial orientation; cooperative and competitive network dynamics and short-term memory; reinforcement and motivation; attention; adaptive sensory-motor planning, control, and robotics; biological rhythms; consciousness; mental disorders; and the mathematical and computational methods needed to support advanced modeling research and applications. Technological training includes methods and applications in image processing, multiple types of signal processing, adaptive pattern recognition and prediction, information fusion, and intelligent control and robotics. The foundation of this broad training is the unique interdisciplinary curriculum of seventeen interdisciplinary graduate courses that have been developed at CNS. Each of these courses integrates the psychological, neurobiological, mathematical, and computational information needed to theoretically investigate fundamental issues concerning mind and brain processes and the applications of artificial neural networks and hybrid systems to technology. A student's curriculum is tailored to his or her career goals with an academic and a research adviser. In addition to taking interdisciplinary courses within CNS, students develop important disciplinary expertise by also taking courses in departments such as biology, computer science, engineering, mathematics, and psychology. In addition to these formal courses, students work individually with one or more research advisors to learn how to do advanced interdisciplinary research in their chosen research areas. As a result of this breadth and depth of training, CNS students have succeeded in finding excellent jobs in both academic and technological areas after graduation. The CNS Department interacts with colleagues in several Boston University research centers or groups, and with Boston-area scientists collaborating with these centers. The units most closely linked to the department are the Center for Adaptive Systems and the CNS Technology Laboratory. Students interested in neural network hardware can work with researchers in CNS and at the College of Engineering. Other research resources include the campus-wide Program in Neuroscience, which includes distinguished research groups in cognitive neuroscience, neurophysiology, neuroanatomy, neuropharmacology, and neural modeling across the Charles River Campus and the Medical School; in sensory robotics, biomedical engineering, computer and systems engineering, and neuromuscular research within the College of Engineering; in dynamical systems within the Mathematics Department; in theoretical computer science within the Computer Science Department ; and in biophysics and computational physics within the Physics Department. Key colleagues in these units hold joint appointments in CNS in order to expedite training and research interactions with CNS core faculty and students. In addition to its basic research and training program, the department organizes an active colloquium series, various research and seminar series, and international conferences and symposia, to bring distinguished scientists from experimental, theoretical, and technological disciplines to the department. The department is housed in its own four-story building, which includes ample space for faculty and student offices and laboratories (computational neuroscience, visual psychophysics, psychoacoustics, speech and language, sensory-motor control, neurobotics, computer vision), as well as an auditorium, classroom, seminar rooms, a library, and a faculty-student lounge. The department has a powerful computer network for carrying out large-scale simulations of behavioral and brain models and applications. Below are listed departmental faculty, courses and labs. FACULTY AND STAFF OF THE DEPARTMENT OF COGNITIVE AND NEURAL SYSTEMS AND CENTER FOR ADAPTIVE SYSTEMS Jelle Atema Professor of Biology Director, Boston University Marine Program (BUMP) PhD, University of Michigan Sensory physiology and behavior Helen Barbas Professor, Department of Health Sciences, Sargent College PhD, Physiology/Neurophysiology, McGill University Organization of the prefrontal cortex, evolution of the neocortex Jacob Beck Research Professor of Cognitive and Neural Systems PhD, Psychology, Cornell University Visual perception, psychophysics, computational models of vision Neil Bomberger Research Associate, CNS Technology Laboratory, Department of Cognitive and Neural Systems PhD, Cognitive and Neural Systems, Boston University Daniel H. Bullock Associate Professor of Cognitive and Neural Systems, and Psychology PhD, Experimental Psychology, Stanford University Sensory-motor performance and learning, voluntary control of action, serial order and timing, cognitive development Val Bykoski Research Associate, CNS Technology Laboratory, Department of Cognitive and Neural Systems PhD, Applied Mathematics and Physics, The Russian Academy, Moscow, Russia Gail A. Carpenter Professor of Cognitive and Neural Systems and Mathematics Director of Graduate Studies, Department of Cognitive and Neural Systems PhD, Mathematics, University of Wisconsin, Madison Learning and memory, synaptic processes, pattern recognition, remote sensing, medical database analysis, machine learning, differential equati= ons Michael A. Cohen Associate Professor of Cognitive and Neural Systems and Computer Science PhD, Psychology, Harvard University Speech and language processing, measurement theory, neural modeling, dynamical systems, cardiovascular oscillations physiology and time series H. Steven Colburn Professor of Biomedical Engineering PhD, Electrical Engineering, Massachusetts Institute of Technology Audition, binaural interaction, auditory virtual environments, signal processing models of hearing Howard Eichenbaum Professor of Psychology PhD, Psychology, University of Michigan Neurophysiological studies of how the hippocampal system mediates declarative memory William D. Eldred III Professor of Biology PhD, University of Colorado, Health Science Center Visual neuralbiology David Fay Research Associate, Department of Cognitive and Neural Systems Assistant Director, CNS Technology Laboratory MA, Cognitive and Neural Systems, Boston University John C. Fiala Research Assistant Professor of Biology PhD, Cognitive and Neural Systems, Boston University Synaptic plasticity, dendrite anatomy and pathology, motor learning, robotics, neuroinformatics Jean Berko Gleason Professor of Psychology PhD, Harvard University Psycholinguistics Sucharita Gopal Associate Professor of Geography PhD, University of California at Santa Barbara Neural networks, computational modeling of behavior, geographical information systems, fuzzy sets, and spatial cognition Stephen Grossberg Wang Professor of Cognitive and Neural Systems Professor of Mathematics, Psychology, and Biomedical Engineering Chairman, Department of Cognitive and Neural Systems Director, Center for Adaptive Systems PhD, Mathematics, Rockefeller University Vision, audition, language, learning and memory, reward and motivation, cognition, development, sensory-motor control, mental disorders, applications Frank Guenther Associate Professor of Cognitive and Neural Systems PhD, Cognitive and Neural Systems, Boston University MSE, Electrical Engineering, Princeton University Speech production, speech perception, biological sensory-motor control and functional brain imaging Catherine L. Harris Assistant Professor of Psychology PhD, Cognitive Science and Psychology, University of California at San Di= ego Visual word recognition, psycholinguistics, cognitive semantics, second language acquisition, computational models of cognition Michael E. Hasselmo Associate Professor of Psychology Director of Graduate Studies, Psychology Department PhD, Experimental Psychology, Oxford University Computational modeling and experimental testing of neuromodulatory mechanisms involved in encoding, retrieval and consolidation Allyn Hubbard Associate Professor of Electrical and Computer Engineering PhD, Electrical Engineering, University of Wisconsin Peripheral auditory system (experimental and modeling), chip design spanning the range from straightforward digital applications to exotic sub-threshold analog circuits that emulate the functionality of the visual and auditory periphery, BCS/FCS, the mammalian cochlea in silicon and MEMS, and drug discovery on silicon Richard Ivey Research Associate, CNS Technology Laboratory, Department of Cognitive and Neural Systems MA, Cognitive and Neural Systems, Boston University Thomas G. Kincaid Professor of Electrical, Computer and Systems Engineering, College of Engineering PhD, Electrical Engineering, Massachusetts Institute of Technology Signal and image processing, neural networks, non-destructive testing Mark Kon Professor of Mathematics PhD, Massachusetts Institute of Technology Neural network theory, complexity theory, wavelet theory, mathematical physics Nancy Kopell Professor of Mathematics PhD, Mathematics, University of California at Berkeley Dynamics of networks of neurons Jacqueline A. Liederman Associate Professor of Psychology PhD, Psychology, University of Rochester Dynamics of interhemispheric cooperation; prenatal correlates of neurodevelopmental disorders Ennio Mingolla Professor of Cognitive and Neural Systems and Psychology PhD, Psychology, University of Connecticut Visual perception, mathematical modeling of visual processes Joseph Perkell Adjunct Professor of Cognitive and Neural Systems Senior Research Scientist, Research Lab of Electronics and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology PhD, Massachusetts Institute of Technology Motor control of speech production Adam Reeves Adjunct Professor of Cognitive and Neural Systems Professor of Psychology, Northeastern University PhD, Psychology, City University of New York Psychophysics, cognitive psychology, vision Michele Rucci Assistant Professor of Cognitive and Neural Systems PhD, Scuola Superiore S.-Anna, Pisa, Italy Vision, sensory-motor control and learning, and computational neuroscienc= e Elliot Saltzman Associate Professor of Physical Therapy, Sargent College Research Scientist, Haskins Laboratories, New Haven, CT Assistant Professor in Residence, Department of Psychology and Center for the Ecological Study of Perception and Action, University of Connecticut, Storrs, CT PhD, Developmental Psychology, University of Minnesota Modeling and experimental studies of human sensorimotor control and coordination of the limbs and speech articulators, focusing on issues of timing in skilled activities Robert Savoy Adjunct Associate Professor of Cognitive and Neural Systems Scientist, Rowland Institute for Science Experimental Psychologist, Massachusetts General Hospital PhD, Experimental Psychology, Harvard University Computational neuroscience; visual psychophysics of color, form, and motion perception Teaching about functional MRI and other brain mapping methods Eric Schwartz Professor of Cognitive and Neural Systems; Electrical, Computer and Systems Engineering; and Anatomy and Neurobiology PhD, High Energy Physics, Columbia University Computational neuroscience, machine vision, neuroanatomy, neural modeling Robert Sekuler Adjunct Professor of Cognitive and Neural Systems Research Professor of Biomedical Engineering, College of Engineering, BioMolecular Engineering Research Center Frances and Louis H. Salvage Professor of Psychology, Brandeis University Consultant in neurosurgery, Boston Children's Hospital PhD, Psychology, Brown University Visual motion, brain imaging, relation of visual perception, memory, and movement Barbara Shinn-Cunningham Assistant Professor of Cognitive and Neural Systems and Biomedical Engineering PhD, Electrical Engineering and Computer Science, Massachusetts Institute of Technology Psychoacoustics, audition, auditory localization, binaural hearing, sensorimotor adaptation, mathematical models of human performance David Somers Assistant Professor of Psychology PhD, Cognitive and Neural Systems, Boston University Functional MRI, psychophysical, and computational investigations of visual perception and attention Chantal E. Stern Assistant Professor of Psychology and Program in Neuroscience, Boston University Assistant in Neuroscience, MGH-NMR Center and Harvard Medical School PhD, Experimental Psychology, Oxford University Functional neuroimaging studies (fMRI and MEG) of learning and memory Malvin C. Teich Professor of Electrical and Computer Engineering, Biomedical Engineering, and Physics PhD, Cornell University Quantum optics and imaging, photonics, wavelets and fractal stochastic processes, biological signal processing and information transmission Lucia Vaina Professor of Biomedical Engineering Research Professor of Neurology, School of Medicine PhD, Sorbonne (France); Dres Science, National Politechnique Institute, Toulouse (France) Computational visual neuroscience, biological and computational learning, functional and structural neuroimaging Takeo Watanabe Associate Professor of Psychology PhD, Behavioral Sciences, University of Tokyo Perception of objects and motion and effects of attention on perception using psychophysics and brain imaging (f-MRI) Allen Waxman Research Professor of Cognitive and Neural Systems Director, CNS Technology Laboratory Senior Staff Scientist, MIT Lincoln Laboratory PhD, Astrophysics, University of Chicago Visual system modeling, multisensor fusion, image mining, parallel computing, and advanced visualization Jeremy Wolfe Adjunct Associate Professor of Cognitive and Neural Systems Associate Professor of Ophthalmology, Harvard Medical School Psychophysicist, Brigham & Women's Hospital, Surgery Department Director of Psychophysical Studies, Center for Clinical Cataract Research PhD, Massachusetts Institute of Technology Visual attention, pre-attentive and attentive object representation Curtis Woodcock Professor of Geography Chairman, Department of Geography Director, Geographic Applications, Center for Remote Sensing PhD, University of California, Santa Barbara Biophysical remote sensing, particularly of forests and natural vegetation, canopy reflectance models and their inversion, spatial modeling, and change detection; biogeography; spatial analysis; geographic information systems; digital image processing CNS DEPARTMENT COURSE OFFERINGS CAS CN500 Computational Methods in Cognitive and Neural Systems CAS CN510 Principles and Methods of Cognitive and Neural Modeling I CAS CN520 Principles and Methods of Cognitive and Neural Modeling II CAS CN530 Neural and Computational Models of Vision CAS CN540 Neural and Computational Models of Adaptive Movement Planning and Control CAS CN550 Neural and Computational Models of Recognition, Memory and Attention CAS CN560 Neural and Computational Models of Speech Perception and Production CAS CN570 Neural and Computational Models of Conditioning, Reinforcement= , Motivation and Rhythm CAS CN580 Introduction to Computational Neuroscience GRS CN700 Computational and Mathematical Methods in Neural Modeling GRS CN720 Neural and Computational Models of Planning and Temporal Structure in Behavior GRS CN730 Models of Visual Perception GRS CN740 Topics in Sensory-Motor Control GRS CN760 Topics in Speech Perception and Recognition GRS CN780 Topics in Computational Neuroscience GRS CN810 Topics in Cognitive and Neural Systems: Visual Event Perceptio= n GRS CN811 Topics in Cognitive and Neural Systems: Visual Perception GRS CN911,912 Research in Neural Networks for Adaptive Pattern Recognition GRS CN915,916 Research in Neural Networks for Vision and Image Processing GRS CN921,922 Research in Neural Networks for Speech and Language Processing GRS CN925,926 Research in Neural Networks for Adaptive Sensory-Motor Planning and Control GRS CN931,932 Research in Neural Networks for Conditioning and Reinforcement Learning GRS CN935,936 Research in Neural Networks for Cognitive Information Processing GRS CN941,942 Research in Nonlinear Dynamics of Neural Networks GRS CN945,946 Research in Technological Applications of Neural Networks GRS CN951,952 Research in Hardware Implementations of Neural Networks CNS students also take a wide variety of courses in related departments. In addition, students participate in a weekly colloquium series, an informal lecture series, and student-run special interest groups, and attend lectures and meetings throughout the Boston area; and advanced students work in small research groups. LABORATORY AND COMPUTER FACILITIES The department is funded by fellowships, grants, and contracts from federal agencies and private foundations that support research in life sciences, mathematics, artificial intelligence, and engineering. Facilities include laboratories for experimental research and computational modeling in visual perception; audition, speech and language processing; and sensory-motor control and robotics. Data analysis and numerical simulations are carried out on a state-of-the-art computer network comprised of Sun workstations, Silicon Graphics workstations, Macintoshes, and PCs. A PC farm running Linux operating systems is available as a distributed computational environment. All students have access to X-terminals or UNIX workstation consoles, a selection of color systems and PCs, a network of SGI machines, and standard modeling and mathematical simulation packages such as Mathematica, VisSim, Khoros, and Matlab. The department maintains a core collection of books and journals, and has access both to the Boston University libraries and to the many other collections of the Boston Library Consortium. In addition, several specialized facilities and software are available for use. These include: Active Perception Laboratory The Active Perception Laboratory is dedicated to the investigation of the interactions between perception and behavior. Research focuses on the theoretical and computational analyses of the effects of motor behavior on sensory perception and on the design of psychophysical experiments with human subjects. The Active Perception Laboratory includes extensive computational facilities that allow the execution of large-scale simulations of neural systems. Additional facilities will soon include instruments for the psychophysical investigation of eye movements during visual analysis, including an accurate and non-invasive eye tracker, and robotic systems for the simulation of different types of behavior. Computer Vision/Computational Neuroscience Laboratory The Computer Vision/Computational Neuroscience Laboratory is comprised of an electronics workshop, including a surface-mount workstation, PCD fabrication tools, and an Alterra EPLD design system; a light machine shop; an active vision laboratory including actuators and video hardware; and systems for computer aided neuroanatomy and application of computer graphics and image processing to brain sections and MRI images. The laboratory supports research in the areas of neural modeling, computational neuroscience, computer vision and robotics. The major question being address is the nature of representation of the visual world in the brain, in terms of observable neural architectures such as topographic mapping and columnar architecture. The application of novel architectures for image processing for computer vision and robotics is also a major topic of interest. Recent work in this area has included the design and patenting of novel actuators for robotic active vision systems, the design of real-time algorithms for use in mobile robotic applications, and the design and construction of miniature autonomous vehicles using space-variant active vision design principles. Recently one such vehicle has successfully driven itself on the streets of Boston. Neurobotics Laboratory The Neurobotics Laboratory utilizes wheeled mobile robots to study potential applications of neural networks in several areas, including adaptive dynamics and kinematics, obstacle avoidance, path planning and navigation, visual object recognition, and conditioning and motivation. The laboratory currently has three Pioneer robots equipped with sonar and visual sensors; one B-14 robot with a moveable camera, sonars, infrared, and bump sensors; and two Khepera miniature robots with infrared proximity detectors. Other platforms may be investigated in the future. Psychoacoustics Laboratory The Psychoacoustics Laboratory in the Department of Cognitive and Neural Systems (CNS) is equipped to perform both traditional psychoacoustic experiments as well as experiments using interactive auditory virtual-reality stimuli. The laboratory contains approximately eight PCs (running Windows 98 and/or Linux), used both as workstations for students and to control laboratory equipment and run experiments. The other major equipment in the laboratory includes special-purpose signal processing and sound generating equipment from Tucker-Davis Technologies, electromagnetic head tracking systems, a two-channel spectrum analyzer, and other miscellaneous equipment for producing, measuring, analyzing, and monitoring auditory stimuli. The Psychoacoustics Laboratory consists of three adjacent rooms in the basement of 677 Beacon St. (the home of the CNS Department). One room houses an 8 ft. =B4 8 ft. single-walled sound-treated booth as well as space for students. The second room is primarily used as student workspace for developing and debugging experiments. The third space houses a robotic arm, capable of automatically positioning a small acoustic speaker anywhere on the surface of a sphere of adjustable radius, allowing automatic measurement of the signals reaching the ears of a listener for a sound source from different positions in space, including the effects of room reverberation. Sensory-Motor Control Laboratory The Sensory-Motor Control Laboratory supports experimental and computational studies of sensory-motor control. A computer controlled infrared WatSmart system allows measurement of large-scale (e.g. reaching) movements, and a pressure-sensitive graphics tablet allows studies of handwriting and other fine-scale movements. A second major component is a helmet-mounted, video-based, eye-head tracking system (ISCAN Corp, 1997). The latter's camera samples eye position at 240Hz and also allows reconstruction of what subjects are attending to as they freely scan a scene under normal lighting. Thus the system affords a wide range of visuo-motor studies. The laboratory is connected to the department's extensive network of Linux and Windows workstations and Linux computational servers. Speech and Language Laboratory The Speech Laboratory includes facilities for analog-to-digital and digital-to-analog software conversion. Ariel equipment allows reliable synthesis and playback of speech waveforms. An Entropic signal-processing package provides facilities for detailed analysis, filtering, spectral construction, and formant tracking of the speech waveform. Various large databases, such as TIMIT and TIdigits, are available for testing algorithms of speech recognition. The laboratory also contains a network of Windows-based PC computers equipped with software for the analysis of functional magnetic resonance imaging (fMRI) data, including region-of-interest (ROI) based analyses involving software for the parcellation of cortical and subcortical brain regions in structural MRI images. Technology Laboratory The Technology Laboratory fosters the development of neural network models derived from basic scientific research and facilitates the transition of the resulting technologies to software and applications. The Technology Laboratory was established in July 2001, with a five-year $2,500,000 grant from the Air Force Office of Scientific Research (AFOSR), "Information Fusion for Image Analysis: Neural Models and Technology Development." Initial applied research projects are developing methods for multi-sensor data and information fusion, utilizing multi-spectral and high-resolution stereo imagery from satellites, in conjunction with simulated ELINT (emitter locator intelligence) and GMTI (ground moving target indicator) data and contextual terrain data. Fusion and data mining methods are being developed in a geospatial context, building on models of opponent-color visual processing, boundary contour system (BCS) and texture processing, Adaptive Resonance Theory (ART) pattern learning and recognition, and other models of associative learning and prediction. Multi-modality presentation of fused sensor data and information to human operators is studied in the context of a Common Operating Picture. A related defense application is real-time 3D fusion of low-light visible, thermal infrared, and ladar imagery, for advanced night vision systems incorporating target learning and search. Other research topics include multi-pass search by incorporation of feedback in the classification-to-search pathway for fused image mining, thereby treating classification decisions as context for further search, and multi-spectral MRI and multi-modality medical image fusion. Associated basic research projects are conducted within the joint context of scientific data and technological constraints. The laboratory effort also includes collaborative technology transfer to government laboratories and commercial industry. Under the sponsorship of the National Imagery and Mapping Agency (NIMA), software for multi-sensor image fusion and data mining is being incorporated into the commercial software suite Imagine by ERDAS Corporation. Related efforts aim to create a Matlab toolbox for interactive neural processing of imagery, signals, and patterns, and technology transfer into RSI/Kodak's ENVI software and the geospatial information software ArcGIS from ESRI Corporation. The Director of the Technology Laboratory, Professor Allen Waxman, and the Assistant Director, David Fay, recently joined the CNS Department after collaborating for twelve years at MIT Lincoln Laboratory. The laboratory continues to grow rapidly, with three research associates, one postdoctoral fellow, and four graduate students, as well as faculty from CNS and the Center for Remote Sensing, currently associated with application, implementation, and basic and applied research projects. Dedicated equipment includes six high-end graphics PCs with dual-headed stereo monitors, two SGI O2 workstations, a Sun UltraSparc 10 workstation, a wall-sized stereo projection display system, a large Cybermation mobile robot, and CCD video cameras with real-time image acquisition and processing using Genesis DSP boards from Matrox. The Technology Laboratory occupies 1000 square feet in the CNS building, including a "dark room" for night vision research and a well-equipped conference room. Visual Psychophysics Laboratory The Visual Psychophysics Laboratory occupies an 800-square-foot suite, including three dedicated rooms for data collection, and houses a variety of computer controlled display platforms, including Macintosh, Windows and Linux workstations. Ancillary resources for visual psychophysics include a computer-controlled video camera, stereo viewing devices, a photometer, and a variety of display-generation, data-collection, and data-analysis software. Affiliated Laboratories Affiliated CAS/CNS faculty members have additional laboratories ranging from visual and auditory psychophysics and neurophysiology, anatomy, and neuropsychology to engineering and chip design. These facilities are used in the context of faculty/student collaborations. ******************************************************************* DEPARTMENT OF COGNITIVE AND NEURAL SYSTEMS GRADUATE TRAINING ANNOUNCEMENT Boston University 677 Beacon Street Boston, MA 02215 Phone: 617/353-9481 Fax: 617/353-7755 Email: inquiries at cns.bu.edu Web: http://www.cns.bu.edu/ ******************************************************************* From Henry.Markram at weizmann.ac.il Thu Dec 20 05:29:33 2001 From: Henry.Markram at weizmann.ac.il (bnmark) Date: Thu, 20 Dec 2001 12:29:33 +0200 Subject: new Brain Mind Institute at the EPFL/ETH/Swiss Federal Institute of Technology Message-ID: <3C21BD8D.BBD2D5CB@weizmann.ac.il> Dear Friends and Colleagues, I am moving my lab to the new Brain Mind Institute at the EPFL/ETH/Swiss Federal Institute of Technology in Lausanne in 2002 and would like to draw your attention to this new Institute and to positions being offered. It is a rare opportunity to start a Brain Mind Institute that is unconstrained by tradition, in the form of a network of closely related labs, on a foundation of futuristic technology, in a manner that can be recurrently interconnected with labs around the world and a vision to go beyond established concepts to explore the emergence of the mind. We would like to invite your participation in letting outstanding new thinkers know about positions available at the BMI and invite you to join programs and initiate new collaborations, as the BMI takes shape over the next few years. Vision of the Brain Mind Institute: - a network of labs addressing the emergence of higher brain function across key levels - each with a focus at a particular level, but with extensive overlapping levels, interests and techniques. We believe this structure is important to form a maximally catalytic environment =96 a recurrent environment for individual groups and a concerted team effort for the Institute. - Multidisciplinary groups that employ a spectrum of techniques ranging from molecular biology, protein chemistry, biophysics, electrophysiology, imaging, psychophysics, fMRI to computational modeling. - Establish groups that can capitalize on the immense technological playground that the EPFL offers to develop new techniques that go beyond the frontiers of Neuroscience. (Sticking wires in the brain will probably be seen as archaic technology in the near future!) Special funding will be available for visionary and exploratory research and development of new technologies to explore emergence of higher brain function. - The physical, psychological, and intellectual borders between labs will be reduced to a minimum with an emphasis on shared technology, equipment, approaches, students etc. - Groups will be able to address their questions staring from their level of expertise all the way down to the genetic level and all the way up to fMRI level and to theories of mind. - The BMI will also be composed of scientists in key labs throughout Switzerland and will form a network of collaborations with the University of Lausanne, Geneva, ETH Zurich, The Institute for Neuroinformatics in Zurich and many labs around Europe, the USA and Japan. - We will offer students and postdocs a comprehensive Neuroscience Program from genes to mind which will be integrated with the latest experimental, technological, mathematical, physical, and computational methods. - An extensive visiting scientist and student exchange program will be in place to facilitate world-wide interaction and collaboration. - We hope to have as many revolutionary ideas participate in the adventure as possible! Multilevel and Recurrent Structure of the BMI: 1. Dynamics of Gene Expression: a. Develop new approaches to understand, modulate, and repair genes in the nervous system. b. Isolate key genes underlying structure and function. c. Dynamics of gene networks d. How gene network activity is controlled by the biochemical and electrical activity of neurons. 2. Behavioral Genetics, Models of Disease & Gene Therapy: a. A focus on gene alterations in disease and new approaches in gene therapy. b. A focus on gene modulation as a function of behavioral experience. c. Development of sensory surgical therapies to detour genetic expression around critical stages (using virtual reality environments). 3. Protein Expression, Targeting, and Localization: a. Spatial and temporal dynamics of protein expression, targeting, and localization in neurons =96 axon, somata, dendrites and synapses b. Algorithms to construct and maintain neuronal structure and function. 4. Biochemical Dynamics of Neurons: a. Dynamics of biochemical pathways as well as cross-cellular orchestration of biochemical networks in response to genetic and electrical activity (multi-protein imaging & protein-protein interactions in single and networks of neurons etc). 5. Molecular Biology and Biophysics of Ion Channels and Receptors: a. A focus on isolating the different genetic expression patterns of ion channels and receptors in different types of neurons and determining their biophysical and computational functions. 6. Synaptic Integration: a. A focus on voltage and electrical dynamics in neurons where principles of morphology, ion channel constellations, their spatial distributions, and synaptic input organization underlie neural computation. 7. Neural Microcircuitry: a. Principles of microcircuit design (gene expression, synapses, neurons & connectivity). b. Information processing, representation, and transformation in microcircuits. c. Plasticity of the microcircuitry as a function of genetic predisposition, experience, and behavior. 8. Neural Network Dynamics, Systems: a. Orchestrated activity in networks of neurons (mega multiunit recordings in vivo, multi-neuron patch clamp in vivo, in vivo intrinsic and voltage imaging etc) in the exploration of the neural code and integration of sensory modalities. 9. Behavioral Neuroscience: a. A focus on integrative perception (integration across sensory modalities), attention and memory using behavioral paradigms, psychophysical techniques, and fMRI. 10. Computational Neuroscience: a. Explore the computational power of neural structure and function. b. Reconstruct neural structure and function (The first comprehensive (genes, physiology, morphology, microcircuitry) database of a reconstruction of a several thousand neuron rodent neocortical microcircuit will be located at the BMI). c. Models from genes to behavior simulating the emergence of function. d. Genetic, molecular, physiological, anatomical, and learning algorithms to automatically synthesize realistic neural microcircuits and networks. e. Hardware implementation of neural microcircuits and models. f. Robotics. g. Neuroinformatics. 11. Theories of Mind: a. History and Philosophy of Neuroscience. b. Theories of information representation, transformation, and propagation. c. Theories of consciousness. d. Exploring the physical basis of Mind. e. The Mind-Body Problem. The BMI will develop in several phases: In the first phase, we are considering applications for all the levels above and around March, 2002 we will decide on the sequence and development of the groups at the BMI based on the research proposals received. There is an emphasis on tenure track, but several full professor tenured positions are also being considered. Over the next 4 years, we plan to fill up to 16 faculty positions. Groups sizes may reach up to 30 people. Generous startup and permanent basic annual funding is offered. Extra support for collaborations with the Math, Computer Science, Robotics, and Virtual Reality Institutes at the EPFL. The criteria for evaluating research proposals and applications: Our goal is to explore the emergence of higher brain function from multiplex perspectives and across multiple levels. 1. Identify the key issue(s) at your particular level of expertise and argue how this issue may be pivotal in opening a new door to understanding higher brain function. The BMI will further invite those strong proposals that are exciting, revolutionary, and even high risk. The BMI is not aiming to compete with traditional research around the world. 2. Describe how addressing the isolated issue(s) requires a multilevel approach and interdisciplinary collaborations. 3. Describe how the proposed research could capitalize on the EPFL=92s strength in engineering, mathematics, computer sciences, and physics to create new technologies and approaches to exploring the emergence of higher brain function. Please send this email to anyone you think may be interested in applying: Please send Proposals and Applications to: School of Life Sciences AA-B 1.07 CH-1015 Lausanne E-mail: life.sciences at epfl.ch Tel: ++41 21 693 53 61 FAX: ++41 21 693 53 69 Indicate 3-7 potential referees that may provide letters of recommendation. My lab in the BMI will focus on neocortical microcircuitry and will be composed of 4 related parts: A: Genetic and molecular basis of the structure and function of the microcircuit; B: Synaptic, cellular and network physiology of the microcircuit; C: Synaptic, cellular and microcircuit anatomy; D: Computation in microcircuits (reconstructing microcircuits; theory, simulations, virtual reality microcircuits, hardware implementations). Techniques and approaches used to address these questions will span all the levels indicated above. Please let any bright stars entering the PhD or postdoctoral levels know that several positions are open. (send email to, henry.Markram at weizmann.ac.il.) Thanks & all the best, Yours, Henry ================ From brian at mail4.ai.univie.ac.at Fri Dec 21 12:28:49 2001 From: brian at mail4.ai.univie.ac.at (Brian Sallans) Date: Fri, 21 Dec 2001 18:28:49 +0100 (CET) Subject: Thesis announcement Message-ID: <200112211728.SAA23147@fichte.ai.univie.ac.at> Dear connectionists, I am pleased to announce the availability of my PhD thesis: Reinforcement Learning for Factored Markov Decision Processes Brian Sallans University of Toronto Abstract: http://www.ai.univie.ac.at/~brian/pthesis/pthabstract.html Download: http://www.ai.univie.ac.at/~brian/pthesis/ This thesis discusses the combination of learning and inference in graphical models with reinforcement learning. It may be of interest to researchers working in either area. The thesis is available in PostScript, PDF or HTML format. There is also Matlab code implementing the experimental tasks used in the thesis. ---------------------- Brian Sallans brian at ai.univie.ac.at Austrian Research Institute for Artificial Intelligence URL: http://www.ai.univie.ac.at/~brian Schottengasse 3 tel: +43-1-5336112-15 From palm at neuro.informatik.uni-ulm.de Fri Dec 21 10:04:24 2001 From: palm at neuro.informatik.uni-ulm.de (Guenther Palm) Date: Fri, 21 Dec 2001 16:04:24 +0100 Subject: two Neural Networks special sessions at KES 2002 Message-ID: <3C234F78.CA67E268@neuro.informatik.uni-ulm.de> Dear Connectionists, I am organizing a Special Session on "Neural Pattern Recognition" at the Sixth International Conference on Knowledge-Based Intelligent Information Engineering Systems (KES 2002), to be held at Podere d'Ombriano, Crema, Italy, September 16 - 18, 2002. The idea of the Special Session is to discuss possibilities, ideas and methods for the analysis of the activity (or connectivity) in real biological neural networks by artificial neural networks. This includes such topics as spike-train analysis of single or multiple recordings, functional brain imaging, EEG or MEG analysis. Potential contributors to this Special Session are invited to send a short (at most one page) abstract until 01.02.2002. The abstracts will be selected and the topical foci of the Special Session will be determined until 01.03.2002. The selected authors will be asked to submit an up to 5 pages paper before 15.04.2002 and these papers will be reviewed. We hope to complete this review process before the end of May, which is before the early registration deadline for the conference. More information on the conference can be found on the web site http://www.bton.ac.uk/kes/kes2002/ The conference proceedings will be published worldwide by IOS Press, Amsterdam. Guenther Palm Neural Information Processing University of Ulm Germany ================================================================ Dear Connectionists, I am organizing a Special Session on "Neural Networks Understanding Language" at the Sixth International Conference on Knowledge-Based Intelligent Information Engineering Systems (KES 2002), to be held at Podere d'Ombriano, Crema, Italy, from September 16 - 18, 2002. The idea of the Special Session is to bring together researchers who try to use artificial neural networks for language understanding. The focus will be on higher cognitive levels of language, concerning syntax, semantics and pragmatics of language use, language learning and aspects of neuro- or psycho-linguistics, but for example not speech recognition alone. After the first wave of neural networks it may now be the right time to assess the state of the art in this area which can also be crucial for an understanding of the impact of artificial neural network research in areas of traditionally more symbolic artificial intelligence. Potential contributors to this Special Session are invited to send a short (at most one page) abstract until 01.02.2002. The abstracts will be selected and the topical foci of the Special Session will be determined until 01.03.2002. The selected authors will be asked to submit an up to 5 pages paper before 15.04.2002 and these papers will be reviewed. We hope to complete this review process before the end of May, which is before the early registration deadline for the conference. More information on the conference can be found on the web site http://www.bton.ac.uk/kes/kes2002/ The conference proceedings will be published worldwide by IOS Press, Amsterdam. Guenther Palm Neural Information Processing University of Ulm Germany From bogus@does.not.exist.com Fri Dec 21 20:10:01 2001 From: bogus@does.not.exist.com () Date: Sat, 22 Dec 2001 01:10:01 +0000 Subject: Adaptive Brain Interfaces Message-ID: Hi, at http://sta.jrc.it/abi you can find info about the very interesting Esprit Project Adaptive Brain Interfaces. jbf. [ Moderator's note: here are the first three paragraphs from that web page: "The objective of the ABI project is to use EEG signals as an alternative means of interaction with computers. We seek to recognise five mental states from on-line spontaneous EEG signals by means of artificial neural networks, which are associated to simple commands. For instance, to select an item from a computer screen it suffices 5 mental states; four of them will move the pointer "up", "down", "left", and "right", while the fifth pattern will "click" and activate the item underneath the pointer. We seek to build individual brain interfaces rather than universal ones valid for everybody and forever. Our approach is based on a mutual learning process whereby the individual user and the ABI are coupled and adapt to each other: a neural network learns user-specific EEG patterns describing the mental tasks while subjects learn to think in such a way that they are better understood by their personal interface. In other words, every single user chooses his/her most natural mental tasks to concentrate on (e.g., relaxation, visualisation, music composition, arithmetic, preparation of movements) and also the preferred strategies to undertake those tasks. Another concern of this project is the robust recognition of EEG patterns outside laboratory settings. This presumes the existence of an appropriate EEG equipment that should be compact, easy-to-use, and suitable for deployment in natural environments. No such a commercial EEG system exists, and we will manufacture an appropriate helmet with integrated and amplified electrodes." ] From samwang at molbio.princeton.edu Fri Dec 21 20:41:24 2001 From: samwang at molbio.princeton.edu (Samuel Wang) Date: Fri, 21 Dec 2001 20:41:24 -0500 Subject: Graduate training in neuroscience at Princeton University Message-ID: <3C23E4C4.24CF2D97@molbio.princeton.edu> GRADUATE TRAINING IN NEUROSCIENCE AT PRINCETON UNIVERSITY *** Graduate application deadline for September admissions: January 2, 2002. *** Graduate study at Princeton University offers interdisciplinary training in all areas of neuroscience. Recent rapid growth at Princeton has opened numerous research opportunities for students and postdocs interested in molecular, cellular, and quantitative/computational approaches to fundamental problems in neuroscience. Furthermore, the imminent opening of the Lewis-Sigler Institute for Integrative Genomics brings exciting new opportunities for chemistry, physics and engineering to be brought to bear on problems in biology, including neuroscience. Graduate training in neuroscience at Princeton is supported by a training grant from the National Institutes of Health. Faculty include: Michael Berry - Neural computation in the retina William Bialek - The interface between physics and biology Jonathan Cohen - Neural bases of cognitive control Lynn Enquist - Neurovirology Michale Fee - Motor control and sequence generation in birdsong Alan Gelperin - Olfaction Elizabeth Gould - Neurogenesis and hippocampal function Michael Graziano - Motor control and perceptual representations in cortex Charles Gross - Visual perception and visual learning Michaela Hau - Neuroendocrinology Bartley Hoebel - Neural circuits for reinforcement of behavior and cognition Philip Holmes - Modeling of neural systems John Hopfield - Computational neurobiology / biophysics Sabine Kastner - Attention Barry Jacobs - Neural substrates of arousal and emotion Partha Mitra - Engineering principles in biological systems Ken Norman - Neural bases of episodic memory Jeffry Stock - Membrane receptors and signal transduction David Tank - Measurement and analysis of neural circuit dynamics Frank Tong - Attention and perception Anne Treisman - Attention and intention Joe Tsien - Molecular bases and neural coding of learning and memory Samuel Wang - Dynamics and learning in neural circuits; brain evolution Eric Wieschaus - Embryonic development of Drosophila melanogaster Students are admitted for study through the Departments of Molecular Biology, Physics, or Psychology. Once admitted, students must meet the degree requirements of the department to which he/she is admitted. Applications may be submitted via the Princeton Web site: https://apply.embark.com/Grad/Princeton/23/ Further information about specific departments may be obtained from: Department of Molecular Biology - http://www.molbio.princeton.edu Elena Chiarchiaro, Program Administrator elenach at princeton.edu Dr. David Tank dwtank at princeton.edu Department of Physics - http://pupgg.princeton.edu/ Laurel Lerner laurel at pupgg.princeton.edu Dr. William Bialek wbialek at princeton.edu Department of Psychology - http://www.princeton.edu/~psych/ Arlene Kerch, Program Administrator arlener at princeton.edu Dr. Elizabeth Gould goulde at princeton.edu Lewis-Sigler Institute for Integrative Genomics http://www.genomics.princeton.edu/ Princeton University is located in Princeton, New Jersey. Its campus covers approximately 500 acres and is one of the most beautiful in the Ivy League. It is located approximately one hour (by train) south of New York City and one hour northeast of Philadelphia. From mayank at MIT.EDU Mon Dec 24 20:35:22 2001 From: mayank at MIT.EDU (Mayank R Mehta) Date: Mon, 24 Dec 2001 20:35:22 -0500 (EST) Subject: Paper available Message-ID: The following article has recently appeared in print and can be downloaded from my home page http://www.mit.edu/~mayank Title: Neuronal Dynamics of Predictive Coding Author: Mayank R. Mehta Journal: The Neuroscientist, 7:490-495 (2001) Abstract: A critical task of the central nervous system is to learn causal relationships between stimuli in order to anticipate events in the future, such as the position of a moving prey or predator. What are the neuronal phenomena underlying anticipation? In this article we review recent results in hippocampal electrophysiology that shed light on this issue. It is shown that the hippocampal spatial receptive fields show large and rapid anticipatory changes in their firing characteristics. These changes are experience- and environment-dependent and can be explained by a computational model based on NMDA-dependent synaptic plasticity during behavior. Striking similarities between the anticipatory network dynamics of widely different neural circuits, such as the hippocampus and the primary visual cortex, are discussed. These experimental and theoretical results indicate how the macroscopic laws of synaptic plasticity give rise to emergent anticipatory properties of receptive fields and behavior. ------------------ Cheers! -Mayank -----------------------+----------------------------+ Mayank R. Mehta | Email: Mayank at MIT.edu | E18-366, M.I.T. | Phone: 617 252 1841 | 50 Ames St. | FAX: 617 452 4120 | Cambridge, MA 02139 | http://www.mit.edu/~mayank | -----------------------+----------------------------+ From malchiodi at dsi.unimi.it Thu Dec 27 11:15:11 2001 From: malchiodi at dsi.unimi.it (Dario Malchiodi) Date: Thu, 27 Dec 2001 17:15:11 +0100 Subject: Course at the International School on Neural Nets "E.R.Caianiello" - Extended deadline Message-ID: <3C2B490F.3000505@dsi.unimi.it> Many apologizes for cross-posting The following meeting may be of interest to researchers interested in artificial intelligence, biology, neural networks and psychology FROM SYNAPSES TO RULES: DISCOVERING SYMBOLIC RULES FROM NEURAL PROCESSED DATA A course of INTERNATIONAL SCHOOL ON NEURAL NETS "E. R. CAIANIELLO" ETTORE MAJORANA CENTRE FOR SCIENTIFIC CULTURE ERICE-SICILY: 25 FEBRUARY - 7 MARCH 2002 Application deadline: December 15, 2001, extended to January 20, 2002. The school aims at fixing a theoretical and applicatry framework for extracting formal rules from data. To this end the modern approaches will be expounded that collapse the two typical goals of the conventional AI and connectionism - respectively, deducing within an axiomatic shell formal rules about a phenomenon and inferring the actual behavior of it from examples - into a challenging inferential framework where we learn from data and understand what we have learnt. The target reads as a translation of the subsymbolic structure of the data - stored in the synapses of a neural network - into formal properties described by rules. To capture this trip from synapses to rules and then render it manageable for affording real world learning tasks, the Course will deal in depth with the following aspects: i. theoretical foundations of learning algorithms and soft computing, ii. intimate relationships between symbolic and subsymbolic reasoning methods, iii. integration of the related hosting architectures in both physiological and artificial brain. TOPICS Inferential bases for learning Theoretical foundations for soft computing Integration of symbolic-subsymbolic reasoning methods Physics and metaphysics of learning Toward applications LECTURERS * B. Apolloni, University of Milan, I * D. Malchiodi, University of Milan, I * D. Mundici, University of Milan, I * M. Gori, University of Siena, I * F. Kurfess, California Polytechnic State Univ., San Luis Obispo, CA, USA * A. Roy, Arizona State University, Tempe, AZ, USA * R. Sun, University of Missouri-Columbia, MO, USA * L. Agnati, Karolinska Institutet, Stockholm, S * G. Basti, Pontificia Universit? Lateranense, Rome, I * G. Biella, C.N.R. LITA, Milan, I * J. G. Taylor, King's College, London, UK * A. Esposito, Istituto Italiano Alti Studi Scientifici, Vietri, I * A. Moise, Boise State University, ID, USA DIRECTORS OF THE COURSE B. APOLLONI, A. MOISE DIRECTORS OF THE SCHOOL M. J. JORDAN, M. MARINARO DIRECTOR OF THE CENTRE A. ZICHICHI APPLICATIONS Interested candidates should send a letter to: * Professor Bruno Apolloni - Dipartimento di Scienze dell'Informazione Universit? degli Studi di Milano Via Comelico 39/41 20135 Milano, Italy Tel: ++39.02.5835.6284, Fax: ++39.02.5835.6228 e-mail: apolloni at dsi.unimi.it specifying: i) date and place of birth and present activity; ii) nationality. Thanks to the generosity of the sponsoring Institutions, partial support can be granted to some deserving students who need financial aid. Requests to this effect must be specified and justified in the letter of application. Notification of acceptance will be sent within the end of January 2002. For APPLICATION, CONTRIBUTING PAPERS, GRANTS, FEES, and further information please visit http://laren.usr.dsi.unimi.it/ericeSchool.html. For information about the Ettore Majorana Centre please visit http://www.ccsem.infn.it From jfgf at cs.berkeley.edu Sat Dec 1 13:28:41 2001 From: jfgf at cs.berkeley.edu (Nando de Freitas) Date: Sat, 01 Dec 2001 10:28:41 -0800 Subject: Parallel Paper Submission Message-ID: Dear connectionists Some concerns: 1) Is our goal to publish as much as we can? Or is it to advance science and technology? May be less time writing and reviewing would leave us with more time for contributing to higher goals. 2) As someone who just entered the tenure track process, I honestly don't feel any pressure to write lots of papers - I do feel pressure to carry out good research. Is this a Berkeley/UBC phenomenon only? I suspect not. Where does this not hold? May be this is what needs to be fixed. 3) Whatever we do, let us remember that in most fields of science we encounter papers that weren't recognised for the first, say 50, years of existence and subsequently had a significant impact on science. How do we deal with this? 4) I love journals like "Journal of the Royal Statistical Society - B" because many of the papers include reviews at the end. It turns out that some of the reviews are very critical and really good. I often find myself reading the reviews before reading the paper! Of course, since the reviews get published and CITED, people make an effort to be constructive, soundly critical and not make fools of themselves. This is a great model - slow but good. Cheers! Nando From sfr at unipg.it Sun Dec 2 11:16:55 2001 From: sfr at unipg.it (Simone G.O. Fiori (Pg)) Date: Sun, 02 Dec 2001 17:16:55 +0100 Subject: Parallel Paper Submission Message-ID: <1.5.4.32.20011202161655.01ba4e1c@unipg.it> A problem that deserves attention deals with the interdisciplinary nature of connectionism, which plays a non negligible role in the determination of the difficulties related to the reviewing process. Connectionists come in fact from diverse research areas, ranging e.g. from electrical engineering to psychology, from neurobiology to mathematics and physics, and so on. This often makes papers result in a cross-fertilization of several research branches and, as a matter of fact, makes them difficult to be read from reviewers that do not possess such wide knowledge. Published broad-area papers are interesting to the Readers as well as specialized papers, but they may make severe difficulties arise in the review phase. In my opinion, part of the delay in the review processes arises when an Editor (or action or associate Editor) faces the problem of assigning a paper a proper set of reviewers: It is not infrequent that, after long time, the people simply return the papers unreviewed reporting they are unable to make any useful comments or reporting some sections, e.g. theoretical ones, appear unaccessible. This simply means that reviewers are not in late wrt the review deadline, but they provide a null report. This creates troubles to the Editors who, when this happens, usually take one of these two possible decisions: 1) Simply reject the paper suggesting the Author to submit it to another more suitable journal, or 2) Try to assign a new set of reviewers in the hope to have better luck, re-starting in fact the whole process again. In this situation, by taking a negative decision the Editor implicitly assumes the Author is responsible for the bad outcome -- and this might be not so wrong, actually -- while the second choice burdens the Editor's office or the Editor him/her-self and leave the Author the feeling that an embarrassing, unjustified, long review time is being taken for his/her paper, because he/she is unaware of the difficulties the hidden people are encountering. As someone else has already suggested, a possible solution to this problem is a semi-blind review process, where any Author can suggest a list of handy potential reviewers for the submitted paper; the Author knows they are potentially able to read and comment on the paper, and the longer the list an Editor can count on, the smaller the knowledge an Author has about to whom the paper will be actually sent for review to. To be realistic, I think that if we want our papers to be read by people that actually know the topic, the "conflict of interests" is intrinsic... but this is physiological to our scientific life. About the reviewers, I don't see drawbacks in asking PhD students or post-docs to perform reviews, provided that this is intended in the right way: This could be ultimately a good exercise for them -- striving to comment on an academic valuable paper, or to detect and comment on the weakness of a scientific proposal -- and a good source of high-level notes and observations for Authors. A pool of PhD students or post-docs (such as room-mates) with some research experience, can sometime exceed the knowledge-spread and knowledge-diversity of a single person. My last note concerns a ground-level proposal that I ask the opinion of colleagues on: Some conferences and journals have started managing submissions and reviews by email or, even better, by dedicated web-pages; I can report the great examples of the IEEE Trans. on Antennas and Propagation, the IEEE Trans. on Circuits and Systems - Part II, and Neural Processing Letters, just to cite three; they allow to submit electronic versions of the papers and the reviews electronically, without the need of printing, sending stuff by snail-mail, faxing, etc. with a non-negligible gain of time (and postage saving, of course...). I would suggest journals definitely move to electronic paper submission and review. All the best, Simon. =================================================== Dr Simone Fiori (EE, PhD)- Assistant Professor Dept. of Industrial Engineering (IED) University of Perugia (UNIPG) Via Pentima bassa, 21 - 05100 TERNI (Italy) eMail: sfr at unipg.it - Fax: +39 0744 492925 Web: http://www.unipg.it/~sfr/ =================================================== From bmg at mail.csse.monash.edu.au Sun Dec 2 22:59:08 2001 From: bmg at mail.csse.monash.edu.au (Bernadette Garner) Date: Mon, 3 Dec 2001 14:59:08 +1100 (EST) Subject: Parallel Paper Submission In-Reply-To: from "Nando de Freitas" at Dec 01, 2001 10:28:41 AM Message-ID: <200112030359.fB33x8w19102@nexus.csse.monash.edu.au> > 4) I love journals like "Journal of the Royal Statistical Society - B" > because many of the papers include reviews at the end. It turns out > that some of the reviews are very critical and really good. I often > find myself reading the reviews before reading the paper! Of course, > since the reviews get published and CITED, people make an effort to be > constructive, soundly critical and not make fools of themselves. This > is a great model - slow but good. I think this is a good idea. It will cut down the number of terrible reviews (where the reviewer didn't have a clue). But I am wondering if it could prevent people actually reading papers if they read the reviews first. I know people who won't see movies if the reviews are bad, and that may not be fair because occassionally editors/reviewers have their own agendas. Bernadette Garner From rid at ecs.soton.ac.uk Mon Dec 3 07:37:33 2001 From: rid at ecs.soton.ac.uk (Bob Damper) Date: Mon, 3 Dec 2001 12:37:33 +0000 (GMT) Subject: Parallel Paper Submission: Separate Refereeing and Editorial processes In-Reply-To: <004001c17761$c0941db0$17bcfea9@DBJH8M01> Message-ID: .. but it's not uncommon for journals to send submissions straight out to graduate students, short-circuiting the advisor/supervisor. Sometimes, graduate students will ask the advice of their supervisor about how to approach the review, but not always. The reason students get asked to do such an important task when they ``lack the knowledge and wisdom to provide a fair review of novel ideas'', to use Rob's words, is that journals are generally struggling to get enough reviewers. Editors and editorial assistants don't always know who is who in the field, especially if the journal has a wide remit. If a grad student has recently published something relevant and it comes to the attention of an editor seeking a reviewer, then they become fair game. This shortage of good qualified referees is going to continue all the time there is no tangible reward (other than a warm altruistic feeling) for the onerous task of reviewing. So, as many others have pointed out, parallel submissions will exacerbate this situation rather than improve it. Not a good idea! Bob. On Tue, 27 Nov 2001, rinkus wrote: > > > If people are genuinely interested in improving the scientific review > process you might want to consider making it unacceptable for the > graduate students of reviewers to do the actual reviewing. Graduate > students are just that...students...and lack the knowledge and wisdom to > provide a fair review of novel ideas. > > In many instances a particular student may have particular knowledge and > insight relevant to a particular submission but the proper model here is > for the advertised reviewer (i.e., whose name appears on the editorial > board of the publication) to consult with the student about the > submission (and this should probably be in an indirect fashion so as to > protect the author's identity and ideas) and then write the review from > scratch himself. The scientific review process is undoubtedly worse off > to the extent this kind of accountability is not ensured. We end up > seeing far too much rehashing of old ideas and not enough new ideas. > > Rod Rinkus > > > > From anand at speech.sri.com Mon Dec 3 21:15:43 2001 From: anand at speech.sri.com (Anand Venkataraman) Date: Mon, 3 Dec 2001 18:15:43 -0800 (PST) Subject: Parallel Paper Submission In-Reply-To: <200112030359.fB33x8w19102@nexus.csse.monash.edu.au> (message from Bernadette Garner on Mon, 3 Dec 2001 14:59:08 +1100 (EST)) Message-ID: <200112040215.SAA09737@stockholm> >> 4) I love journals like "Journal of the Royal Statistical Society - B" >> because many of the papers include reviews at the end. It turns out >> that some of the reviews are very critical and really good. I often >> find myself reading the reviews before reading the paper! Of course, >> since the reviews get published and CITED, people make an effort to be >> constructive, soundly critical and not make fools of themselves. This >> is a great model - slow but good. > > I think this is a good idea. It will cut down the number of terrible I too think this is a fantastic idea. It simultaneously solves two problems -- that of reviewer "remuneration" and that of "malicious/bad reviews". The problem, however, is the loss upon publication of anonymity of the reviewer. But why would a reviewer want to remain anonymous unless he/she gave in a malicious review? In my own case at least, I have wished on one occasion that one of four reviews a paper of mine received got published with the reviewer's name on it. I have also wished on more than one occasion that the author of a paper I had reviewed knew my identity when reading my review. The only other issue I see here is that "reviews written to be published" and those written to "improve the paper" tend to be quite different in character. But I guess this is a simple matter to address. The reviewer can simply be requested to relook at the final submission with instructions not to suggest more changes, but rather to submit the final review for publication. Isn't this how the JRSS handles it? & From kpfleger at cs.stanford.edu Mon Dec 3 17:39:49 2001 From: kpfleger at cs.stanford.edu (Karl Pfleger) Date: Mon, 3 Dec 2001 14:39:49 -0800 (PST) Subject: Parallel Paper Submission: Separate Refereeing and Editorial In-Reply-To: from "Bob Damper" at Dec 03, 2001 12:37:33 PM Message-ID: <200112032239.OAA04183@hpp-ss10-4.Stanford.EDU> From Lakhmi.Jain at unisa.edu.au Mon Dec 3 07:50:02 2001 From: Lakhmi.Jain at unisa.edu.au (Lakhmi Jain) Date: Mon, 3 Dec 2001 23:20:02 +1030 Subject: invitation Message-ID: <0402819922B44E4CA0860B3EB619862C2EF6A4@exstaffb.levels.unisa.edu.au> INVITATION SPRINGER-VERLAG Book Series on Advanced Information Processing (AIP) http://www.springer.de/comp/series/aip/index.html Book proposals are invited for a book series titled "Advanced Information Processing" published by Springer-Verlag. The following categories will be considered for publication: (1) Books (text books, reference books, hand books) (2) Coherently integrated multi-author edited books (3) Research monograms L.C. Jain , PhD, ME, BE(Hons), Fellow IE(Australia) Series Editor Director KES, SCT-Building University of South Australia, Adelaide The Mawson Lakes, SA 5095 Australia phone: +61 8 8302 3315 fax: +61 8 8302 3384 email: L.jain at unisa.edu.au (Sincere apologies for multiple copies) From alorincz at matavnet.hu Mon Dec 3 08:01:15 2001 From: alorincz at matavnet.hu (LORINCZ, Andras) Date: Mon, 03 Dec 2001 14:01:15 +0100 Subject: "parallel submission" -- software References: Message-ID: <3C0B779A.42D571@matavnet.hu> Information distributing software with ACCESS CONTROL is available. If you wish to solve the original problem of Gabriele Dorothea Scheler and Johann Martin Philipp Schumann, you need to decide ONLY about access control at connectionists mailing list. Connectionists mail list serves as an advertisement place for technical reportss and papers. anyway. It is then a good idea to start parallel submission at this single point. There is not too much controversy in this statement. Here is an initiating suggestion, which may need to be polished/ironed/confronted. The author uploads his/her paper to to connectionists. Notification goes to everybody who has subsrciption. Uploading and notification are unmoderated. (One can set a filter his/her email not to accept mails from connectionists with subject 'new paper'.) The paper is cached at connectionists and becomes available for downloading. Anybody can make a review of the paper. Reviews are automatically linked to the paper. Reviews are secretive -- the reviewer has an ssh-like communication with connectionists -- and there is a public part of his code. The list and "top acknowledged reviewers" together can reveal the names of "top acknowledged reviewers". If the opinion of the reviewer is considered by the author then he/she can write a revised version of the paper. During uploading this revised version he/she is supposed to acknowledge the reviewer's public code. This is clearly in sake of the author -- provided that he/she would like to promote the reviewer. In turn, works which need improvments and are improved by the reviewer will serve as the basis of selection. If a reviewer is acknowledged, then this reviewer receives a credit (impact) point (factor). There is a ranking of reviewers according to their impact factors. There is a list of the top $n$ most acknowledged reviewers. The names of these $n$ reviewers can be discovered for the public. This is a decision of the reviewer if he/she belongs to this top. These acknowledged reviewers decide (vote) if a paper becomes 'accepted' or not. A paper can be accepted without acknowledgment, for example, if it is perfect. Acceptance means qualification. Acceptance may also mean the opening a forum for discussion about the paper -- which is open reviewing written by people (alike to discussions at BBS). Open reviewing happens through connectionists -- this will be made by another notification list. Top $N>n$ acknowledged reviewers have the right for open reviewing. Their names are provided. In turn, $N$ acknowledged reviewers may be known to the public and $n$ top acknowledged reviewers may vote. Any journal can accept the paper. If an editorial board of a journal accepts the paper then it is a question to the author whether he would like to give the copyright to the journal or not -- he/she might be waiting for a better journal, or, alternatively, -- he/she might have submitted the paper to a journal at the very beginning and might have given the copyright to that journal to start with. If copyright is given to a journal, it should be noted for connectionists. It is the journals' problem how to deal with this challenge. The experienced shift of the editorial board of MLJ to JMLR provides a feeling about the possible outcome. Regards, Andras Lorincz http://people.inf.elte.hu/lorincz P.S. Anyone could build this software. There are freeware solutions, such as 'mailman'. We have also built one with intelligent search options. It has been thoroughly tested for Windows Explorer, but would not support Netscape. Any organization might decide to write/set up/buy a similar software. This seems to be a most probable step in the near future. In this case we shall experience a selective process similar to the evolution of electronic markets: Lots of attempts will start and only a few will survive. So, get started! P.P.S. I have put a paper onto the web. It is closely related to this topic It will appear in the Special Issue of IJFCS (International Journal of Foundations of Computer Science) on Mining the Web Title: "New Generation of the World Wide Web: Anticipating the birth of the 'hostess' race" http://people.inf.elte.hu/lorincz/ParallelSubmission/Lorincz_et_al_Intelligent_Crawler_revised.zip The paper is in a WinZipped postscript file. P.P.P.S. I like the idea of parallel submission. I have the feeling that some reviewers are negligent, may be lacking time, may be students (and lacking knowledge) of authorities on the field, and may be biased agaynszt non-nateave-Inglish-spieking autorz. :-) From mike at stats.gla.ac.uk Tue Dec 4 07:26:28 2001 From: mike at stats.gla.ac.uk (Mike Titterington) Date: Tue, 4 Dec 2001 12:26:28 +0000 (GMT) Subject: Parallel Paper Submission Message-ID: ------------- Begin Forwarded Message ------------- >> 4) I love journals like "Journal of the Royal Statistical Society - B" >> because many of the papers include reviews at the end. It turns out >> that some of the reviews are very critical and really good. I often >> find myself reading the reviews before reading the paper! Of course, >> since the reviews get published and CITED, people make an effort to be >> constructive, soundly critical and not make fools of themselves. This >> is a great model - slow but good. > > I think this is a good idea. It will cut down the number of terrible > The only other issue I see here is that "reviews written to be published" > and those written to "improve the paper" tend to be quite different in > character. But I guess this is a simple matter to address. The reviewer > can simply be requested to relook at the final submission with instructions > not to suggest more changes, but rather to submit the final review for > publication. Isn't this how the JRSS handles it? ------------- End Forwarded Message ------------- I think that it is worth clarifying the JRSS practice. It is not really true that the journal publishes referees' reviews of papers. What happens is that the RSS holds about 10 meetings per year at which certain papers are 'read' and discussed. Versions of the verbal discussions and any written contributions sent in soon after the meeting are lightly edited and are printed, followed by a rejoinder from the authors of the paper. It is very likely that some of the discussants are people who acted as referees, and possibly some of the points made in the referee reports are reiterated in the discussion, but not necessarily. Anyone at all is at liberty to submit a discussion contribution, whether or not they have reviewed the paper. These discussion papers are carefully selected with a view to their being likely to stimulate a lively discussion, as well as being 'scientifically important'. I'd agree with Nando that the discussion can be at least as interesting and stimulating as the paper itself! Maybe I can add one or two points, from the point of view of an editor. 1. I can't imagine coping with parallel submissions. Handling x incoming submissions per year is bad enough. The thought of 4x or even 2x is frightening. I have to side with Grace's original reaction to the proposal! 2. It is hard to envisage any easy alternative to the present system. It is important to have a strong, conscientious and knowledgeable group of associate editors, whose joint expertise covers the journal's range and who can express a cogent opinion on any paper they are sent; this means they either can act, in effect, as the sole referee (a practice that helps to speed things up) or can adjudicate reliably if multiple referees provide conflicting reports. 3. The issue of rewarding referees is difficult, although I believe some journals offer free issues as 'payment'. I think there's more to it than pure altruism. If one wants one's own work to be efficiently and promptly reviewed then it seems fair to repay this by contributing some time to refereeing other people's work. The journal I'm involved with does print an annual list of referees, as an acknowledgement, and this sort of practice does provide some small public recognition. Mike Titterington. =================================================================== D.M. Titterington, Department of Statistics, University of Glasgow, Glasgow G12 8QQ, Scotland, UK. mike at stats.gla.ac.uk Tel (44)-141-330-5022 Fax (44)-141-330-4814 http://www.stats.gla.ac.uk/~mike From jbower at bbb.caltech.edu Tue Dec 4 12:39:00 2001 From: jbower at bbb.caltech.edu (James M. Bower) Date: Tue, 4 Dec 2001 09:39:00 -0800 Subject: improving the review process Message-ID: I am currently writing a book on the state of modern biological research, comparing that state to the development of physics in the 16th and 17th centuries. In the book I am using examples from paper and grant reviews we have received to support the proposition that biology is essentially a folkloric pre-paradigmatic science that needs to develop a sold, quantitative foundation to move forward as a real science. For that reason, I have spent quite a bit of time recently looking through old reviews of our papers. The remarkable thing about those reviews is that there is typically very little criticism of the methods or results sections, but instead the focus is almost always on the discussion. My favorite quote from one of our reviews (and in fact, the source for the title of the forthcoming book), is "I have no more concerns about the methods or results, but I am deeply concerned about what would happen if a graduate student read the discussion". Accordingly, I think that the quality and usefulness of the review process would be greatly improved if the discussion section was excluded, and not even sent to reviewers. In my view, the discussion section should provide an author free reign to consider the implications of their work in their own words, unfettered by what is all to often a kind of thought censorship or, in effect, demand for patronage. Professional expertise is necessary to assure that a paper has no methodological flaws, and that the results are not overstated or overdrawn. But the discussion is the reward that an author should get for having pulled off the former two. How much more interesting and revealing would the scientific literature be if authors felt free to express their real opinions, and heavens forbid, even speculate once in a while? I should mention one other theme in the book that is relevant to much of this discussion. "Modern" scientific journal publishing was actually invented in the 17th century as a means of providing general communication between a new age of physicists. (it is also believed that Newton was interested in controlling who said what). The important point for this discussion is that a 10 page paper is sufficient space to describe a new approach to understanding planetary motion, but it is not, in my opinion, even close to sufficient to present a theory appropriate for understanding biology. Just at the Transactions of the Royal Society promoted the development of a common quantitative base for physics, a new form of publication is now necessary to establish such a base for biology and other complex systems. On that - stay tuned.... Jim Bower -- *************************************** James M. Bower Ph.D. Research Imaging Center University of Texas Health Science Center - San Antonio and Cajal Neuroscience Research Center University of Texas - San Antonio (626) 791-9615 (626) 791-9797 FAX (626) 484-3918 (cell worldwide) Temporary address for correspondence: 110 Taos Rd. Altadena, CA. 91001 WWW addresses for: laboratory (temp) http://www.bbb.caltech.edu/bowerlab GENESIS (temp) http://www.bbb.caltech.edu/GENESIS From ken at phy.ucsf.edu Tue Dec 4 19:14:57 2001 From: ken at phy.ucsf.edu (Ken Miller) Date: Tue, 4 Dec 2001 16:14:57 -0800 Subject: UCSF Postdoctoral/Graduate Fellowships in Theoretical Neurobiology Message-ID: <15373.26369.689037.567063@coltrane.ucsf.edu> FULL INFO: http://www.sloan.ucsf.edu/sloan/sloan-info.html PLEASE DO NOT USE 'REPLY'; FOR MORE INFO USE ABOVE WEB SITE OR CONTACT ADDRESSES GIVEN BELOW The Sloan Center for Theoretical Neurobiology at UCSF solicits applications for pre- and post-doctoral fellowships, with the goal of bringing theoretical approaches to bear on neuroscience. Applicants should have a strong background and education in mathematics, theoretical or experimental physics, or computer science, and commitment to a future research career in neuroscience. Prior biological or neuroscience training is not required. The Sloan Center offers opportunities to combine theoretical and experimental approaches to understanding the operation of the intact brain. Young scientists with strong theoretical backgrounds will receive scientific training in experimental approaches to understanding the operation of the intact brain. They will learn to integrate their theoretical abilities with these experimental approaches to form a mature research program in integrative neuroscience. The research undertaken by the trainees may be theoretical, experimental, or a combination. Resident Faculty of the Sloan Center and their research interests include: William Bialek (1/8 time): Information-theoretic and statistical characterization of, and physical limits to, neural coding and representation Allison Doupe: Development of song recognition and production in songbirds Stephen Lisberger: Learning and memory in a simple motor reflex, the vestibulo-ocular reflex, and visual guidance of smooth pursuit eye movements by the cerebral cortex Michael Merzenich: Experience-dependent plasticity underlying learning in the adult cerebral cortex, and the neurological bases of learning disabilities in children Kenneth Miller: Circuitry of the cerebral cortex: its structure, self-organization, and computational function (primarily using cat primary visual cortex as a model system) Philip Sabes: Sensorimotor coordination, adaptation and development of spatially guided behaviors, experience dependent cortical plasticity. Christoph Schreiner: Cortical mechanisms of perception of complex sounds such as speech in adults, and plasticity of speech recognition in children and adults Michael Stryker: Mechanisms that guide development of the visual cortex There are also a number of visiting faculty, including Larry Abbott, Brandeis University; Sebastian Seung, MIT; David Sparks, Baylor University; Steve Zucker, Yale University. TO APPLY for a POSTDOCTORAL position, please send a curriculum vitae, a statement of previous research and research goals, up to three relevant publications, and have two letters of recommendation sent to us. The application deadline is February 1, 2002. Send applications to: Sloan Center 2002 Admissions Sloan Center for Theoretical Neurobiology at UCSF Department of Physiology University of California 513 Parnassus Ave. San Francisco, CA 94143-0444 PRE-DOCTORAL applicants with strong theoretical training may seek admission into the UCSF Neuroscience Graduate Program as a first-year student. Applicants seeking such admission must apply by Jan. 5, 2002 to be considered for fall, 2002 admission. Application materials for the UCSF Neuroscience Program may be obtained from http://www.neuroscience.ucsf.edu/neuroscience/admission.html or from Pat Vietch Neuroscience Graduate Program Department of Physiology University of California San Francisco San Francisco, CA 94143-0444 neuroscience at phy.ucsf.edu Be sure to include your surface-mail address. The procedure is: make a normal application to the UCSF Neuroscience program; but also alert the Sloan Center of your application, by writing to sloan-info at phy.ucsf.edu. If you need more information: -- Consult the Sloan Center WWW Home Page: http://www.sloan.ucsf.edu/sloan -- Send e-mail to sloan-info at phy.ucsf.edu -- See also the home page for the W.M. Keck Foundation Center for Integrative Neuroscience, in which the Sloan Center is housed: http://www.keck.ucsf.edu/ From jaksa at neuron-ai.fei.tuke.sk Wed Dec 5 09:16:45 2001 From: jaksa at neuron-ai.fei.tuke.sk (Rudolf Jaksa) Date: Wed, 5 Dec 2001 15:16:45 +0100 Subject: publishing model Message-ID: <15374.11341.734421.130097@lada.aid.kyushu-id.ac.jp> I'm thinking how to apply free software development (publishing) model to scientific publishing... Present scientific publishing: 1. Article (for instance paper.pdf) is sent to journal or conference for review (it is in camera ready form). 2. If author will get some feedback from reviewers, she may improve this article. 3. Article is printed on paper (and presented in talk). 4. Other people may read this article and use ideas from it in their future work. Free software model applied to scientific publishing: 1. All the data useful for further work on problem are published in single "package". Instead of only camera ready paper, also source code for algorithms, pictures, sample data etc. are published. This "package" is displayed somewhere on the internet. 2. Availability of this work is announced in established mailing lists or internet forums. 3. Other people may download this "article" or read it directly on internet. 4. They also may download it, incorporate parts of it in their own future work, or publish improved version of this article. They may send their comments to the author and she can incorporate them into next version of article ("package"). Good thing about this model is that it is yet proved that it works, however it may not work for "scientific articles". But in my opinion working on paper or on program code is very similar. And many people seems think that free software itself is inspired by scientific publishing... I like on this model (as opposite to current scientific publishing model) also: * Less money are wasted in publishing process, and it means that more people are "allowed" to read article. And more people are allowed to publish too. * Continuation of work is better as they may be several versions of single "article". This is opposite to several articles spread across different journals and proceedings. * Exchange of ideas can by much faster. The loop author-reviewer-readers-author can be reduced to few days if the work is actually "hot topic". * More data and more types of data can be published, publishing is not restricted to 10 pages of text. Actually I know about one book published this way and few program packages with papers included, but I think this free software publishing approach may be more useful for scientific community. I can even imagine this as primary publishing method in science... R.Jaksa From ehildreth at wellesley.edu Wed Dec 5 09:17:46 2001 From: ehildreth at wellesley.edu (Ellen C. Hildreth) Date: Wed, 5 Dec 2001 15:17:46 +0100 Subject: computational neuroscience position Message-ID: Hi, Wellesley College is conducting a search for a tenure-track faculty position in computational neuroscience. If you are interested in this position, please contact us and submit an application as soon as possible, thanks, Ellen Hildreth --------------------------------------- Tenure-track position in Computational Neuroscience Wellesley College, a pre-eminent liberal arts college for women with a long tradition of excellence in the sciences, has a new tenure-track position available to teach in the expanding Neuroscience Program. The successful candidate will have teaching responsibilities in a home department-- Biological Sciences, Chemistry, Computer Science, or Physics --as well as in the Neuroscience Program. The teaching load would include courses at the introductory, intermediate and advanced undergraduate levels. The successful candidate will be expected to develop a strong research program in computational neuroscience that involves undergraduates. Qualifications include a Ph.D. in computational neuroscience or a related area. Post-doctoral training is preferred. Interested individuals should send curriculum vitae, statement of research and teaching interests, and three letters of recommendation to: Dr. Barbara S. Beltz, Chair, Neuroscience Search Committee, Wellesley College, Wellesley, MA 02481. Review of applications will begin December 1, 2001. Wellesley College is an Equal Opportunity/ Affirmative Action educational institution and employer; successful candidates must be able to work effectively in a culturally diverse environment. Applications from women, minorities, veterans, and candidates with disabilities are encouraged. From school at cogs.nbu.bg Thu Dec 6 09:51:06 2001 From: school at cogs.nbu.bg (CogSci Summer School) Date: Thu, 6 Dec 2001 16:51:06 +0200 Subject: CogSci 2002 Message-ID: 9th International Summer School in Cognitive Science Sofia, New Bulgarian University, July 8 - 28, 2002 Courses: Jeff Elman (University of California at San Diego, USA) - Connectionist Models of Learning and Development Michael Mozer (University of Colorado, USA) - Connectionist Models of Human Perception, Attention, and Awareness Eran Zaidel (University of California at Los Angeles, USA) - Hemispheric Specialization Barbara Knowlton (University of California at Los Angeles, USA) - Cognitive Neuroscience of Memory Markus Knauff (University of Freiburg, Germany) - Imagery and Reasoning: Cognitive and Cortical Models Stella Vosniadou (University of Athens, Greece) - Cognitive Development and Conceptual Change Peter van der Helm (University of Nijmegen, the Netherlands) - Structural Description of Visual Form Antonio Rizzo (University of Siena, Italy) - The Nature of Interactive Artifacts and Their Design Nick Chater (University of Warwick, UK) - Simplicity as a Fundamental Cognitive Principle Organised by the New Bulgarian University Endorsed by the Cognitive Science Society For more information look at: http://www.nbu.bg/cogs/events/ss2002.htm Central and East European Center for Cognitive Science New Bulgarian University 21 Montevideo Str. Sofia 1635 phone: 955-7518 From shultz at psych.mcgill.ca Thu Dec 6 10:43:03 2001 From: shultz at psych.mcgill.ca (Tom Shultz) Date: Thu, 6 Dec 2001 10:43:03 -0500 Subject: job ad Message-ID: <000501c17e6c$b1147440$b86ace84@psych.mcgill.ca> Readers of this list may be interested in the following job ad -------------------------- The Department of Psychology of McGill University seeks applicants for a tenure-track position at the Assistant or junior Associate Professor level in Human Cognitive Neuroscience or Human Cognitive Science. The deadline for receipt of completed applications is January 1, 2002, with an anticipated starting date of September 1, 2002. Applicants with interests in any area of human cognitive neuroscience or human cognitive science will be considered. The Department has excellent facilities for interdisciplinary research through its links with related academic departments at McGill and other universities in Montreal, research units in the McGill University Health Centre including the Montreal Neurological Institute, and McGill Cognitive Science. Applicants at the Assistant Professor level should present early evidence of the ability to establish a record of significant, externally funded research productivity, and applicants at the Associate Professor level should have such a record. All applicants are expected to have an aptitude for undergraduate and graduate teaching. Applicants should arrange for three confidential letters of recommendation to be sent to the address below. A curriculum vitae, description of current and proposed areas of research, selected reprints of published or in press research articles, a description of areas of teaching competency, interest, and approaches, and other relevant material, should also be sent to: Chair, Human Cognitive Neuroscience / Human Cognitive Science Search Committee Department of Psychology McGill University 1205 Penfield Avenue Montreal, QC, Canada H3A 1B1 ----------------------------------------------------------------- Thomas R. Shultz, Professor, Department of Psychology McGill University, 1205 Penfield Ave., Montreal, Quebec, Canada H3A 1B1. E-mail: shultz at psych.mcgill.ca Updated 14 November 2001: http://www.psych.mcgill.ca/perpg/fac/shultz/default.htm Phone: 514 398-6139 Fax: 514 398-4896 ----------------------------------------------------------------- From schmidler at stat.duke.edu Thu Dec 6 10:55:00 2001 From: schmidler at stat.duke.edu (Scott Schmidler) Date: Thu, 6 Dec 2001 10:55:00 -0500 (EST) Subject: Statistics Faculty Positions at Duke University Message-ID: <200112061555.fB6Ft0Q18350@bioinfo.isds.duke.edu> ============================================================== Duke University ISDS Faculty Positions The Institute of Statistics and Decision Sciences (ISDS) at Duke University invites applications and nominations for faculty positions to begin Fall 2002: Open Rank Tenured and Tenure-track Faculty Positions: Successful candidates will have demonstrated excellence in statistical research and teaching (or potential for excellence, for candidates for Assistant Professor) and an interest in participating actively in departmental and university life. Assistant Professor of the Practice of Statistics: Successful candidate will demonstrate excellence, and the potential for national recognition, in statistics with leadership potential to further develop the teaching and statistical practice activities of the Institute. The Institute seeks applicants who will participate enthusiastically in student life, promote standards of academic excellence in education, and provide leadership in service teaching. Visiting Positions: ISDS also offers positions as Visiting Professor of Statistics for periods of one to three years. Successful candidates will have strong skills and interests in teaching and research interests that contribute to the intellectual life of the Institute. Some postdoctoral research positions are also available. ISDS faculty and students are involved in research and education in the development and application of contemporary statistical methods, with particular emphasis on computationally-intensive methods and Bayesian analysis. The department stresses interdisciplinarity in research and teaching, with recent and ongoing projects in a wide range of scientific fields, and the Duke environment offers many opportunities for collaboration across disciplinary boundaries. The Institute currently has 16 regular-rank faculty, 10 visiting, adjunct and postdoctoral faculty, and 26 Ph.D. students. ISDS enrolls approximately 1200 undergraduate and 150 graduate students per year in service courses and approximately 100 graduate students per year in Ph.D. courses. For more information about ISDS and about these openings see the ISDS home page . Candidates must have a doctoral degree in statistics or a related field, and potential for success in an environment where education and collaborative research are valued. There is no application deadline, but screening began December 1, 2001 and is expected to be completed during December. All applicants should send a letter, curriculum vitae, and the names of three references by post to the address below (electronic applications are not accepted). Candidates for Assistant Professor should also send three or more letters of reference. Mail applications to: Faculty Search Committee Duke University ISDS, Box 90251 Durham, NC 27708-0251 or send inquiries by e-mail to: Applications from qualified women and minority candidates are particularly encouraged. Duke University is an Equal Opportunity/Affirmative Action Employer. From maggini at dii.unisi.it Thu Dec 6 11:42:55 2001 From: maggini at dii.unisi.it (Marco Maggini) Date: Thu, 06 Dec 2001 17:42:55 +0100 Subject: CfP: ACM TOIT Special Issue on Machine Learning for the Internet Message-ID: <3C0FA00F.6040203@dii.unisi.it> ------------------------------------------------------ We apologize, if you receive multiple copies. Please feel free to publicize. Thank you. ------------------------------------------------------ CALL FOR PAPERS ACM Transactions on Internet Technology Special Issue on Machine Learning for the Internet Machine learning methods are becoming increasingly important for the development of several internet related technologies. Tasks such as intelligent searching, organizing, retrieving, and filtering information on the Web are extremely challenging and still much too easy for humans than they are for computers, except that humans are unable to scale up with the enormous amount of available data. Explicit coding of rules in this domain is typically very hard, and even if possible, would require exceptional coordination efforts. In particular, the fast dynamics of the information available on the Internet requires new approaches for indexing. The organization of information in Internet portals is becoming hardly manageable by humans. The users' surfing of the Internet can be made easier by personalized tools like search engines optimized for a specific Web community or even for the single user. For example, finding relevant documents by querying a search engine with a set of keywords may be difficult unless a proper ranking scheme is used to order the results. In this case, techniques based on user profiles, on topic selection and on the use of the Web topology can help in defining authoritative sources of information with respect to the given query and interests. Searching, organizing and retrieving information from the Web poses new issues that can be effectively tackled by applying machine learning techniques. Learning algorithms can be used to devise new tools which improve the accessibility to the information available on the Web. Learning is particularly useful to automate those tasks in which it is quite easy to collect examples while coding a set of explicit rules is impractical. For example, the fast dynamics of the Internet can be faced by designing new specialized search tools which cover only the parts of the Web related to a given topic. These search tools focus their exploration only on the portion of the Web which contains the information relevant for this topic. Moreover, learning-based search tools can feature a very high precision in retrieving information and can reduce the need for human efforts for many repetitive tasks (like organizing documents in Web directories). Beside accessing information, understanding and characterizing web structure and usage is essential for future development and organization of new tools and services. In spite of several recent efforts in measuring and producing mathematical models of web connectivity, dynamics, and usage, no definitive answers have emerged and learning may play a fundamental role for advancing our understanding in this field. Papers are invited on applications of machine learning to all aspects of Internet technology. These include (but are not limited to): * Automated creation of web directories * Automatic extraction of information from Web pages * Automatic security management * Categorization of web pages * Design and improvement of web servers through prediction of request patterns * Focused crawling * Information retrieval for the design of thematic search engines * Models and laws that characterize the web structure * User modeling for the personalization of Web services Submissions Authors are requested to send an intention of submission (with authors, title and abstract) as an email message in plain text to acm-toit at dsi.unifi.it by May 1, 2002. Then, papers must be submitted in electronic format as an attachment to the same email address before May 15, 2002. Preferred formats are PDF and PostScript (compressed with gzip or zip). Manuscripts must not exceed 50 single-column, double-spaced pages (including figures and tables) and must be written in English and set in 10 or 11 point font. Please do not send papers directly to guest editors' email addresses. Important Dates Intention of submission: May 1, 2002 Submission deadline: May 15, 2002 Notification: August 1, 2002 Guest editors Gary William Flake NEC Research Institute 4 Independence Way Princeton, NJ 08540 (USA) flake at research.nj.nec.com Voice: +1 609-951-2795 http://www.neci.nj.nec.com/homepages/flake/ Paolo Frasconi Dept. of Systems and Computer Science University of Florence Via di Santa Marta 3, I-50139 Firenze (Italy) paolo at dsi.unifi.it Voice: +39 055 4796 362 http://www.dsi.unifi.it/~paolo/ C. Lee Giles School of Information Sciences and Technology The Pennsylvania State University 001 Thomas Building, University Park, PA, 16802 (USA) giles at ist.psu.edu Voice: +1 814 865 7884 http://ist.psu.edu/giles/ Marco Maggini Dept. of Information Engineering University of Siena Via Roma 56, I-53100 Siena (Italy) maggini at dii.unisi.it Voice: +39 0577 233696 http://www.dii.unisi.it/~maggini/ From bogus@does.not.exist.com Wed Dec 5 01:43:15 2001 From: bogus@does.not.exist.com () Date: Wed, 5 Dec 2001 14:43:15 +0800 Subject: ICONIP'02-SEAL'02-FSKD'02 First Call for Papers Message-ID: <5D138E82835F8143AC52E4899FAEFE38692ECC@EXCHANGE03.staff.main.ntu.edu.sg> [We apologize should you receive multiple copies of this CFP.] =================================== 9th International Conference on Neural Information Processing (ICONIP'02) 4th Asia-Pacific Conference on Simulated Evolution And Learning (SEAL'02) International Conference on Fuzzy Systems and Knowledge Discovery (FSKD'02) =================================== November 18 - 22, 2002, Singapore http://www.ntu.edu.sg/home/nef Organized by: School of Electrical and Electronic Engineering Nanyang Technological University, Singapore Sponsored by: Asia-Pacific Neural Network Assembly SEAL & FSKD Steering Committees Lee Foundation In Co-Operation with: IEEE Neural Network Council International Neural Network Society European Neural Network Society SPIE CALL FOR PAPERS ======= ICONIP'02, SEAL'02, and FSKD'02 will be jointly held in Singapore from November 18 to 22, 2002. The conferences will not only feature the most up-to-date research results in neural information processing, evolutionary computation, fuzzy systems, and knowledge discovery, but also promote cross-fertilization over these exciting and yet closely- related areas. Registration to any one of the conferences will entitle a participant to the technical sessions and the proceedings of all three conferences, as well as the conference banquet, buffet lunches, and a tour to one of the major attractions in Singapore. About Singapore =======Located at one of the most important crossroads of the world, Singapore is truly a place where East and West come together. Here you will find Chinese, Indian, and Malay communities living together, their long established cultures forming a unique backdrop to a clean and modern garden city. English is spoken everywhere and is the common business language of all. Few places on earth promise such a delight for the palate, with gourmet cuisine from over 30 countries. Exotic resorts of Malaysia and Indonesia are only a short bus/ferry ride away. Submission of Papers ========== Authors are invited to submit electronic files (postscript, pdf or Word format) through the conference home page. A selected number of accepted papers will be expanded and revised for possible inclusion in edited books and peer-reviewed journals, such as "Knowledge and Information Systems: An International Journal" by Springer-Verlag. Special Sessions ======== The conferences will feature special sessions on specialized topics to encourage in-depth discussions. One organizer of each successfully organized special session with at least 6 papers will enjoy a 50% discount on the conference registration fee. To propose a special session, email the session title, contact information of the organizer(s), and a short description on the theme and topics covered by the session to Xin Yao, Special Sessions Chair (x.yao at cs.bham.ac.uk), with a copy to Lipo Wang, General Chair (Cc: elpwang at ntu.edu.sg). Sponsorship =====The conferences will offer product vendors a sponsorship package and/or an opportunity to interact with conference participants. Product demonstration and exhibition can also be arranged. For more information, please visit the conference website or contact Tong Seng Quah, Sponsorship/Exhibition Chair (etsquah at ntu.edu.sg), with a copy to Lipo Wang, General Chair (Cc: elpwang at ntu.edu.sg). Keynote Speakers (more will be confirmed later) ======== Shun-ichi Amari, RIKEN Brain Science Institute, Japan David Fogel, Natural Selection, Inc., USA Xin Yao, The University of Birmingham, UK Lotfi A. Zadeh, University of California, USA Important Dates ======= Paper/Summary Deadline : April 30, 2002 Notification of Acceptance : July 15, 2002 Camera-Ready Copy Due : August 15, 2002 Honorary Conference Chairs ============= Shun-ichi Amari, Japan Hans-Paul Schwefel, Germany Lotfi A. Zadeh, USA International Advisory Board ============== Sung-Yang Bang, Korea Meng Hwa Er, Singapore David Fogel, USA Toshio Fukuda, Japan Tom Gedeon, Australia Zhenya He, China Mo Jamshidi, USA Nikola Kasabov, New Zealand Sun-Yuan Kung, USA Tong Heng Lee, Singapore Erkki Oja, Finland Nikhil R. Pal, India Enrique H. Ruspini,USA Harcharan Singh, Singapore Ah Chung Tsoi, Australia Shiro Usui, Toyohashi, Japan Lei Xu, China Benjamin W. Wah, USA Donald C. Wunsch II, USA Xindong Wu, USA Youshou Wu, China Yixin Zhong, China Jacek M. Zurada, USA Advisor === Alex C. Kot, Singapore General Chair ====== Lipo Wang, Singapore Program Co-Chairs ======== ICONIP'02: Kunihiko Fukushima, Japan Soo-Young Lee, Korea Jagath C. Rajapakse, Singapore SEAL'02: Takeshi Furuhashi, Japan Jong-Hwan Kim, Korea Kay Chen Tan, Singapore FSKD'02: Saman Halgamuge, Australia Special Sessions: Xin Yao, UK Finance Chair ====== Charoensak Charayaphan, Singapore Local Arrangement Chair =========== Meng Hiot Lim, Singapore Proceedings Chair ======== Farook Sattar, Singapore Publicity Chair ======= Chunru Wan, Singapore Sponsorship/Exhibition Chair ============== Tong Seng Quah, Singapore Tutorial Chair ======= P. N. Suganthan, Singapore For More Information ========== Please visit the conference home page or contact: Lipo Wang, ICONIP'02-SEAL'02-FSKD'02 General Chair School of Electrical and Electronic Engineering Nanyang Technological University Block S2, 50 Nanyang Avenue, Singapore 639798 Email: elpwang at ntu.edu.sg Phone: +65 790 6372 Conference Secretariat =========== ICONIP'02-SEAL'02-FSKD'02 Secretariat Conference Management Center/CCE, NTU Administration Annex Building #04-06 42 Nanyang Avenue, Singapore 639815 Email: nef at ntu.edu.sg Fax: +65 793 0997 From berthier at psych.umass.edu Fri Dec 7 06:00:23 2001 From: berthier at psych.umass.edu (Neil Berthier) Date: Fri, 07 Dec 2001 06:00:23 -0500 Subject: Assistant Professor position in Cognitive neuroscience Message-ID: <1007722823.8525.92.camel@arpeggio> Readers may be interested in the following job-- THE DEPARTMENT OF PSYCHOLOGY, UNIVERSITY OF MASSACHUSETTS -- AMHERST invites applications for a three year, non-tenure track, Assistant Professor position in Cognitive neuroscience beginning Fall, 2002. The ideal candidate will have research interests in human perception and/or action (although other areas of cognition will be considered), and will have training in one or more of the following areas: cognitive neuroscience, cognitive psychology, human neuropsychology, or neurophysiology. The successful applicant will become part of our growing emphasis in cognitive neuroscience and join existing faculty in strong graduate programs in cognitive and developmental psychology and neuroscience and behavior. This individual will have access to on-campus research facilities and expertise in fMRI study design and analysis, transcranial magnetic stimulation (TMS), kinematic and eye movement recording, and psychophysics. Off-campus resources for fMRI data collection are also available. Teaching responsibilities will include three undergraduate or graduate courses per year. Salary is dependent on experience and qualifications. Applicants should send a vita, a statement of research and teaching interests, reprints of recent publications, and at least three letters of recommendation to: Cognitive Neuroscience Search Committee, Department of Psychology, University of Massachusetts, Amherst, MA 01003-7710. We will begin reviewing application in January, 2002, and will continue until the position is filled. Hiring is contingent upon the availability of funds. The University of Massachusetts is an Affirmative Action/Equal Opportunity Employer. Women and members of minority groups are highly encouraged to apply. Contact Charles Clifton (cec at psych.umass.edu) for more information. From cindy at cns.bu.edu Fri Dec 7 14:00:18 2001 From: cindy at cns.bu.edu (Cynthia Bradford) Date: Fri, 7 Dec 2001 14:00:18 -0500 Subject: 6th ICCNS: Final Invited Program and Call for Abstracts Message-ID: <200112071900.OAA04466@retina.bu.edu> Apologies if you receive this more than once. ***** FINAL INVITED SPEAKER PROGRAM AND CALL FOR ABSTRACTS ***** SIXTH INTERNATIONAL CONFERENCE ON COGNITIVE AND NEURAL SYSTEMS Tutorials: May 29, 2002 Meeting: May 30 - June 1, 2002 Boston University http://www.cns.bu.edu/meetings/ This interdisciplinary conference focuses on two fundamental questions: How Does the Brain Control Behavior? How Can Technology Emulate Biological Intelligence? A single oral or poster session enables all presented work to be highly visible. Contributed talks will be presented on each of the three conference days. Three-hour poster sessions with no conflicting events will be held on two of the conference days. All posters will be up all day, and can also be viewed during breaks in the talk schedule. CONFIRMED INVITED SPEAKERS TUTORIAL SPEAKERS: Wednesday, May 29, 2002 Mark Gluck (Rutgers University) Neural networks in neurology and clinical neuropsychology: Alzheimer's disease, amnesia, and Parkinson's disease Gail A. Carpenter (Boston University) Adaptive resonance theory Ferdinando Mussa-Ivaldi (Northwestern University Medical School) Learning and adaptive control of arm movements Frank Guenther (Boston University) Neural modeling of speech INVITED SPEAKERS Thursday, May 30, 2002 CELL AND CIRCUIT DYNAMICS: Daniel Johnston (Baylor College of Medicine) Information processing and storage by neuronal dendrites Bard Ermentrout (University of Pittsburgh) Learning at a slug's pace: The role of oscillations in odor learning in the Limax John Rinzel (New York University) Cellular dynamics involved in sound localization VISION AND IMAGE PROCESSING: Rudiger von der Heydt (Johns Hopkins University School of Medicine) Visual cortex: Global structure in local feature maps David J. Field (Cornell University) Visual systems and the statistics of natural scenes: How far can we go? Philip J. Kellman (UCLA) From niebur at russell.mb.jhu.edu Fri Dec 7 14:46:03 2001 From: niebur at russell.mb.jhu.edu (niebur@russell.mb.jhu.edu) Date: Fri, 7 Dec 2001 14:46:03 -0500 Subject: Applications to the Johns Hopkins Neuroscience Graduate Program Message-ID: <200112071946.OAA16190@russell.mb.jhu.edu> The deadline is coming up for applications to the Johns Hopkins Neuroscience Graduate Program http://neuroscience.jhu.edu/gradprogram.asp DEADLINE: January 4, 2002 For the readers of this group, I should emphasize that applications from students interested in computational neuroscience and systems level neuroscience are particularly encouraged. Systems level research in the Program ranges from single unit recordings in behaving nonhuman primates to psychophysical and functional MRI studies in humans and is complemented by training in computational neuroscience. The Neuroscience Training Program at The Johns Hopkins University School of Medicine includes over sixty faculty members in the Departments of Neuroscience, Psychology, Cognitive Science, Molecular Biology and Genetics, Biological Chemistry, Physiology, Biomedical Engineering, Pharmacology and Molecular Sciences, Ophthalmology, Neurology, Psychiatry and Behavioral Sciences, Medicine, Otolaryngology, and Pathology. The Training Program addresses the broad areas encompassed by modern neuroscience. The purpose of the Program is to train doctoral students for independent research and teaching in neuroscience. It is the goal of the Program to ensure that candidates for the Ph.D. and M.D./Ph.D. degrees obtain a background covering molecular/cellular and systems/cognitive approaches to neuroscience, as well as receive training that brings them to the forefront of research in their particular area of interest. A series of core courses in neuroscience, along with advanced electives, seminar series, laboratory rotations and original independent dissertation research form the Neuroscience Graduate Training Program. The Neuroscience Training Program and the Neuroscience Department are among the oldest in the United States and date back to 1980. The faculty of the Neuroscience Training Program have trained about 250 Ph.D. and M.D./Ph.D. students and 500 postdoctoral fellows over the past ten years. All doctoral candidates receive full tuition remission and a stipend. Currently, about 90 doctoral candidates and 150 postdoctoral fellows work in the laboratories of faculty in the Neuroscience Program. For more information and contact information, see also neuroscience.jhu.edu. -- Ernst Niebur, PhD Krieger Mind/Brain Institute Assoc. Prof. of Neuroscience Johns Hopkins University niebur at jhu.edu 3400 N. Charles Street (410)516-8643, -8640 (secr), -8648 (fax), -3357 (lab) Baltimore, MD 21218 From miguel at giccs.georgetown.edu Mon Dec 10 21:13:17 2001 From: miguel at giccs.georgetown.edu (Miguel . Carreira-Perpin) Date: Mon, 10 Dec 2001 21:13:17 -0500 Subject: thesis: latent var. models, dim. reduction & missing data reconstr. Message-ID: <15381.27581.312558.417306@giccs.georgetown.edu> Dear connectionists, I am pleased to make my PhD thesis available online (abstract below): Continuous latent variable models for dimensionality reduction and sequential data reconstruction Miguel A. Carreira-Perpinan 333 pages, 130 figures, 24 tables, 445 references This thesis may be of interest to researchers working on probabilistic models for data analysis, in particular dimensionality reduction, inverse problems and missing data problems. Applications are given mainly for speech processing (electropalatography, acoustic-to-articulatory mapping). It also contains extensive surveys of all these areas. The thesis can be retrieved in PostScript and PDF formats from: http://www.dcs.shef.ac.uk/~miguel/papers/phd-thesis.html or http://www.giccs.georgetown.edu/~miguel/papers/phd-thesis.html Also available there are: - Matlab software for several of the models and algorithms discussed - A BibTeX file with the references Best regards, Miguel -- Miguel A Carreira-Perpinan Department of Neuroscience Tel. (202) 6878679 Georgetown University Medical Center Fax (202) 6870617 3900 Reservoir Road NW mailto:miguel at giccs.georgetown.edu Washington, DC 20007, USA http://www.giccs.georgetown.edu/~miguel ----------------------------------8<---------------------------------- CONTINUOUS LATENT VARIABLE MODELS FOR DIMENSIONALITY REDUCTION AND SEQUENTIAL DATA RECONSTRUCTION Miguel A. Carreira-Perpinan Dept. of Computer Science, University of Sheffield, UK February 2001 Abstract ======== Continuous latent variable models (cLVMs) are probabilistic models that represent a distribution in a high-dimensional Euclidean space using a small number of continuous, latent variables. This thesis explores, theoretically and practically, the ability of cLVMs for dimensionality reduction and sequential data reconstruction. The first part of the thesis reviews and extends the theory of cLVMs: definition in terms of a prior distribution in latent space, a mapping to data space and a noise model; maximum likelihood parameter estimation with an expectation-maximisation (EM) algorithm; specific cLVMs (factor analysis, principal component analysis (PCA), independent component analysis, independent factor analysis and the generative topographic mapping (GTM)); mixtures of cLVMs; identifiability, interpretability and visualisation; and derivation of mappings for dimensionality reduction and reconstruction and their properties, such as continuity, for each cLVM. We extend GTM to diagonal noise and give a corresponding EM algorithm. We also describe a discrete LVM for binary data, Bernoulli mixtures, widely used in practice. We show that their log-likelihood surface has no singularities, unlike other mixture models, which makes EM estimation practical; and that their theoretical non-identifiability is rarely realised in actual estimates, which makes them interpretable. The second part deals with dimensionality reduction. We define the problem and give an extensive, critical review of nonprobabilistic methods for it: linear methods (PCA, projection pursuit), nonlinear autoassociators, kernel methods, local dimensionality reduction, principal curves, vector quantisation methods (elastic net, self-organising map) and multidimensional scaling methods. We then empirically evaluate, in terms of reconstruction error, computation time and visualisation, several latent-variable methods for dimensionality reduction of binary electropalatographic (EPG) data: PCA, factor analysis, mixtures of factor analysers, GTM and Bernoulli mixtures. We compare these methods with earlier, nonadaptive EPG data reduction methods and derive 2D maps of EPG sequences for use in speech research and therapy. The last part of this thesis proposes a new method for missing data reconstruction of sequential data that includes as particular case the inversion of many-to-one mappings. We define the problem, distinguish it from inverse problems, and show when both coincide. The method is based on multiple pointwise reconstruction and constraint optimisation. Multiple pointwise reconstruction uses a Gaussian mixture joint density model for the data, conveniently implemented with a nonlinear cLVM (GTM). The modes of the conditional distribution of missing values given present values at each point in the sequence represent local candidate reconstructions. A global sequence reconstruction is obtained by efficiently optimising a constraint, such as continuity or smoothness, with dynamic programming. We give a probabilistic interpretation of the method. We derive two algorithms for exhaustive mode finding in Gaussian mixtures, based on gradient-quadratic search and fixed-point search, respectively; as well as estimates of error bars for each mode and a measure of distribution sparseness. We discuss the advantages of the method over previous work based on the conditional mean or on universal mapping approximators (including ensembles and recurrent networks), conditional distribution estimation, vector quantisation and statistical analysis of missing data. We study the performance of the method with synthetic data (a toy example and an inverse kinematics problem) and real data (mapping between EPG and acoustic data). We describe the possible application of the method to several well-known reconstruction or inversion problems: decoding of neural population activity for hippocampal place cells; wind field retrieval from scatterometer data; inverse kinematics and dynamics of a redundant manipulator; acoustic-to-articulatory mapping; audiovisual mappings for speech recognition; and recognition of occluded speech. Contents (abridged) =================== 1. Introduction 2. The continuous latent variable modelling formalism 3. Some properties of finite mixtures of multivariate Bernoulli distributions 4. Dimensionality reduction 5. Dimensionality reduction of electropalatographic (EPG) data 6. Inverse problems and mapping inversion 7. Sequential data reconstruction 8. Exhaustive mode finding in Gaussian mixtures 9. Experiments with synthetic data 10. Experiments with real-world data: the acoustic-to-articulatory mapping problem 11. Conclusions Appendices ----------------------------------8<---------------------------------- From qian at brahms.cpmc.columbia.edu Tue Dec 11 11:14:06 2001 From: qian at brahms.cpmc.columbia.edu (Ning Qian) Date: Tue, 11 Dec 2001 11:14:06 -0500 Subject: paper: stochastic resonance in sensory perception Message-ID: <200112111614.fBBGE6k31900@brahms.cpmc.columbia.edu> Dear colleagues, The following short paper (0.08 MB) is available online at: http://brahms.cpmc.columbia.edu/publications/sr.ps.gz A model for stochastic resonance-type behavior in sensory perception Yunfan Gong, Nestor Matthews, and Ning Qian Physical Review E, 2002 (in press). Abstract Recently it was found that noise could help improve human detection of sensory stimuli via stochastic resonance-type behavior. Specifically, the ability of an individual to detect a weak tactile stimulus could be enhanced by adding a certain amount of noise. Here we propose, from the perspective of classic signal detection theory, a simple and general model to elucidate the mechanism underlying this novel phenomenon. We demonstrate that noise-mediated enhancements and decrements in human sensation can be well reproduced by our model. The predicted upper bound of the performance improvement by adding noise is also consistent with the experimental data. We suggest additional experiments to further test the model. Best regards, Ning Qian ------------------------------------------------------------- http://brahms.cpmc.columbia.edu Ning Qian, Ph. D. qian at brahms.cpmc.columbia.edu Associate Professor nq6 at columbia.edu Ctr. Neurobiology & Behavior Columbia University 212-543-5213 (Office) NYSPI Annex Rm 730 212-543-5161 (Lab/fax) 1051 Riverside Drive 212-543-5410 (Center/fax) New York, NY 10032, USA ------------------------------------------------------------- From aslin at cvs.rochester.edu Tue Dec 11 13:10:15 2001 From: aslin at cvs.rochester.edu (Richard Aslin) Date: Tue, 11 Dec 2001 13:10:15 -0500 Subject: postdoc slots at University of Rochester Message-ID: THE UNIVERSITY OF ROCHESTER The University of Rochester seeks five or more outstanding postdoctoral fellows with research interests in several areas of the Cognitive Sciences, including language, learning, and development. Two NIH training grants provide support. (1) An NIH training grant is affiliated with the Center for the Sciences of Language. The Center brings together faculty and students with interests in spoken and signed languages from the Departments of Brain and Cognitive Sciences, Computer Science, Linguistics, and Philosophy, as well as the interdepartmental program in Neuroscience. We encourage applicants from any of these disciplines who have expertise in any area of natural language. We are particularly interested in postdoctoral fellows who want to contribute to an interdisciplinary community. (2) A second NIH training grant spans the disciplines of Learning and Developmental Plasticity. Applicants should have expertise in human or animal research on learning and developmental plasticity or in computational modeling. Contributing faculty are in the Departments of Brain and Cognitive Sciences, Computer Science, and the interdepartmental program in Neuroscience. All fellowships are open only to US citizens or permanent residents. Applicants should send a letter describing their graduate training and research interests, a curriculum vitae, and arrange to have three letters of recommendation sent to: Professor Richard N. Aslin Department of Brain and Cognitive Sciences Meliora Hall University of Rochester Rochester, NY 14627-0268. Review of applications will begin on January 15, 2002 and continue until all of the positions are filled, with expected start dates ranging from June 30 to September 1, 2002. Learn more about the community of faculty, students, and training facilities of the Center for Language Sciences (and affiliated departments and programs) and the Department of Brain and Cognitive Sciences by visiting our web sites: http://www.cls.rochester.edu and http://www.bcs.rochester.edu From Dave_Touretzky at cs.cmu.edu Mon Dec 17 03:22:36 2001 From: Dave_Touretzky at cs.cmu.edu (Dave_Touretzky@cs.cmu.edu) Date: Mon, 17 Dec 2001 03:22:36 -0500 Subject: Graduate training with the Center for the Neural Basis of Cognition Message-ID: <5378.1008577356@ammon.boltz.cs.cmu.edu> Note: application deadline January 1, 2002. Graduate Training with the Center for the Neural Basis of Cognition The Center for the Neural Basis of Cognition offers an interdisciplinary doctoral training program operated jointly with eight affiliated PhD programs at Carnegie Mellon University and the University of Pittsburgh. Detailed information about this program is available on our web site at http://www.cnbc.cmu.edu/Training. The Center is dedicated to the study of the neural basis of cognitive processes including learning and memory, language and thought, perception, attention, and planning; to the study of the development of the neural substrate of these processes; to the study of disorders of these processes and their underlying neuropathology; and to the promotion of applications of the results of these studies to artificial intelligence, robotics, and medicine. CNBC students have access to some of the finest facilities for cognitive neuroscience research in the world: Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) scanners for functional brain imaging, neurophysiology laboratories for recording from brain slices and from anesthetized or awake, behaving animals, electron and confocal microscopes for structural imaging, high performance computing facilities including an in-house supercomputer for neural modeling and image analysis, and patient populations for neuropsychological studies. Students are admitted jointly to a home department and the CNBC Training Program. Applications are encouraged from students with interests in biology, neuroscience, psychology, engineering, physics, mathematics, computer science, or robotics. For more information about the program, and to obtain application materials, visit our web site at www.cnbc.cmu.edu, or contact us at the following address: Center for the Neural Basis of Cognition 115 Mellon Institute 4400 Fifth Avenue Pittsburgh, PA 15213 Tel. (412) 268-4000. Fax: (412) 268-5060 email: cnbc-admissions at cnbc.cmu.edu The affiliated PhD programs at the two universities are: Carnegie Mellon University of Pittsburgh Biological Sciences Mathematics Computer Science Neuroscience Psychology Psychology Robotics Statistics The CNBC training faculty includes: Eric Ahrens (CMU Biology): MRI studies of the vertebtate nervous system John Anderson (CMU Psychology): models of human cognition German Barrionuevo (Pitt Neuroscience): LTP in hippocampal slice Alison Barth (CMU Biology): molecular basis of plasticity in neocortex Marlene Behrmann (CMU Psychology): spatial representations in parietal cortex Pat Carpenter (CMU Psychology): mental imagery, language, and problem solving Cameron S. Carter (Pitt Psychology/Neuroscience): fMRI and PET attention studies Carson Chow (Pitt Mathematics): spatiotemporal dynamics in neural networks Carol Colby (Pitt Neuroscience): spatial reps. in primate parietal cortex Steve DeKosky (Pitt Neurobiology): neurodegenerative human disease William Eddy (CMU Statistics): analysis of fMRI data Bard Ermentrout (Pitt Mathematics): oscillations in neural systems Julie Fiez (Pitt Psychology): fMRI studies of language Chris Genovese (CMU Statistics): making inferences from scientific data Lori Holt (CMU Psychology): mechanisms of auditory and speech perception John Horn (Pitt Neurobiology): synaptic plasticity in autonomic ganglia Allen Humphrey (Pitt Neurobiology): motion processing in primary visual cortex Satish Iyengar (Pitt Statistics): spike train data analsysis Marcel Just (CMU Psychology): visual thinking, language comprehension Robert Kass (CMU Statistics): transmission of info. by collections of neurons Roberta Klatzky (CMU Psychology): human perception and cognition Richard Koerber (Pitt Neurobiology): devel. and plasticity of spinal networks Tai Sing Lee (CMU Comp. Sci.): primate visual cortex; computer vision Michael Lewicki (CMU Comp. Sci.): learning and representation David Lewis (Pitt Neuroscience): anatomy of frontal cortex Brian MacWhinney (CMU Psychology): models of language acquisition Yoky Matsuoka (CMU Robotics): human motor control and motor learning James McClelland (CMU Psychology): connectionist models of cognition Paula Monaghan Nichols (Pitt Neurobiology): vertebrate CNS development Carl Olson (CNBC): spatial representations in primate frontal cortex Charles Perfetti (Pitt Psychology): language and reading processes David Plaut (CMU Psychology): connectionist models of reading Michael Pogue-Geile (Pitt Psychology): development of schizophrenia Lynne Reder (CMU Psychology): models of memory and cognitive processing Erik Reichle (Pitt Psychology): attention and eye movements in reading Jonathan Rubin (Pitt Mathematics): analysis of systems of coupled neurons Walter Schneider (Pitt Psych.): fMRI, models of attention & skill acquisition Charles Scudder (Pitt Neurobiology): motor learning in cerebellum Susan Sesack (Pitt Neuroscience): anatomy of the dopaminergic system Dan Simons (Pitt Neurobiology): sensory physiology of the cerebral cortex Peter Strick (Pitt Neurobiology): motor control; basal ganglia and cerebellum Flo Thiels (Pitt Neurosicence): LTP and LTD in hippocampus David Touretzky (CMU Comp. Sci.): hippocampus, rat navigation, animal learning Nathan Urban (CMU Bioogy): circuitry of the olfactory bulb Valerie Ventura (CMU Statistics): structure of neural firing patterns See http://www.cnbc.cmu.edu for further details. From dayan at gatsby.ucl.ac.uk Mon Dec 17 15:22:27 2001 From: dayan at gatsby.ucl.ac.uk (Peter Dayan) Date: Mon, 17 Dec 2001 20:22:27 +0000 (GMT) Subject: New Book : Theoretical Neuroscience Message-ID: <200112172022.UAA32375@flies.gatsby.ucl.ac.uk> Larry Abbott and I would like to announce our new book: Theoretical Neuroscience Computational and Mathematical Modeling of Neural Systems Peter Dayan and L. F. Abbott For more information, please visit http://people.brandeis.edu/~abbott/book Theoretical neuroscience provides a quantitative basis for describing what nervous systems do, determining how they function, and uncovering the general principles by which they operate. This text introduces the basic mathematical and computational methods of theoretical neuroscience and presents applications in a variety of areas including vision, sensory-motor integration, development, learning, and memory. The book is divided into three parts. Part I discusses the relationship between sensory stimuli and neural responses, focusing on the representation of information by the spiking activity of neurons. Part II discusses the modeling of neurons and neural circuits on the basis of cellular and synaptic biophysics. Part III analyzes the role of plasticity in development and learning. An appendix covers the mathematical methods used, and exercises are available on the book's Web site. Peter Dayan is on the faculty of the Gatsby Computational Neuroscience Unit at University College London. L. F. Abbott is the Nancy Lurie Marks Professor of Neuroscience and Director of the Volen Center for Complex Systems at Brandeis University. He is the coeditor of Neural Codes and Distributed Representations (MIT Press, 1999). 7 x 9, 476 pp., 165 illus. cloth ISBN 0-262-04199-5 From ftrjin at mail.ipm.net Thu Dec 13 04:47:12 2001 From: ftrjin at mail.ipm.net (Yaochu Jin) Date: Thu, 13 Dec 2001 10:47:12 +0100 (MET) Subject: CFP: Workshop on Approximation and Learning in EC Message-ID: <200112130908.KAA29306@mail.ipm.net> Call for Papers A workshop on ``Approximation and Learning in Evolutionary Computation'' is to be organized within the Genetic and Evolutionary Computation Conference (GECCO) from July 9 to July 13, 2002, New York City, USA. See further details at http://www.cs.unr.edu/~sushil/workshop/ . 1. Workshop Description In real-world applications, it is often necessary to build approximate models for fitness evaluation. One essential difficulty in applying evolutionary algorithms to the optimization of complex systems is the high time complexity of each fitness evaluation. Besides, in some applications, no explicit mathematical functions are available for fitness evaluation. Further more, approximate fitness models have also been proved useful in dealing with noisy and multi-modal fitness functions. This workshop aims to get together researchers coming from different research areas to see the state-of-art, to discuss the main problems and future work in this area. 2. Topics of Interests Submissions are invited in, but not limited to, any of the following areas: * Off-line and on-line learning for approximate model construction * Off-line and on-line learning for performance improvement * Evolution control and model management in evolutionary computation * Multi-level evolutionary optimization * Learning in multi-objective evolutionary optimization * Fitness estimation in noisy environment * Comparison of different modeling methods, such as neural networks, response surface and least squares methods, and probabilistic models for evolutionary computation * Comparison of different sampling techniques for on-line and off-linelearning 3. Submission Details Please follow the main conference guidelines with regards to the format of the paper. We expect submissions to be short papers or extended abstracts upto four (4) pages in length. Please send an electronic copy of the paper in PDF or postscript to yaochu_jin at de.hrdeu.com with subject ``GECCO workshop submission'' no later than March 4, 2002. Workshop proceedings will be published and will be available at the conference. Important dates: Paper submission deadline: March 4, 2002 Notification of acceptance: April 5, 2002 Final manuscript: April 25, 2002 4. Conferences Organizers Yaochu Jin Future Technology Research Honda R&D Europe Carl-Legien-Str. 30 63073 Offenbach/Main Germany Phone: +49-69-89011735 Fax: +49-69-89011749 Email: yaochu_jin at de.hrdeu.com yaochu.jin at hre-ftr.f.rd.honda.co.jp Sushil J. Louis University of Nevada, Reno Reno, NV 89557 U.S.A. Phone:(775)784-4315 Fax:(775)784-1877 Email: sushil at cs.unr.edu Khaled M. Rasheed Computer Science Department The University of Georgia Athens, GA 30602 U.S.A. Phone:(706)542-3444 Fax:(706)542-2966 Email: khaled at cs.uga.edu ------------------------------------------------------------------- Yaochu Jin Future Technology Research Honda R&D Europe (D) Carl-Legien-Str. 30 63073 Offenbach/Main GERMANY Tel: +49 69 89011735 Fax: +49 69 89011749 Email: yaochu.jin at hre-ftr.f.rd.honda.co.jp yaochu_jin at de.hrdeu.com Alias: yaochu.jin at ieee.org From juergen at idsia.ch Fri Dec 14 04:03:36 2001 From: juergen at idsia.ch (Juergen Schmidhuber) Date: Fri, 14 Dec 2001 10:03:36 +0100 Subject: reviewing Message-ID: <3C19C068.DF68B70@idsia.ch> A few comments on the recent discussion. The situation in theoretical physics heralds the things to come in other fields such as ours. In the early 1990s they were the first to institutionalize electronic publishing - astonishingly, computer science itself is a late-comer in this area. In theoretical physics, priority in the digital public archive has become pretty much the only thing that counts. Leading journals were forced to shorten the subsequent peer review process down to 2-3 months (!), otherwise most citations would go to digital preprints instead of journal papers. To a certain extent the "bidding-for-papers process" suggested by various contributors to this list is already evolving. More and more frequently, journal editors are approaching authors of interesting preprints, encouraging them to submit a version to their journal, listing rapid review among the incentives. How important is the peer review system anyway? Rustum Roy & James R. Ashburn (co-author of the 1:2:3 superconductor paper) recently wrote (Nature 414:6862, p394, Nov 2001): >>>...many leaders [...] such as Nobel laureates [...] regard peer review as a great hindrance to good science [...] An enormous amount of the best science has been and is run without the benefit of this rubric, as is the worldwide patent system [...] Everyone except the true believers know that it is your nearest competitors who often `peer' review your paper [...] The enormous waste of scientists' time, and the absolute, ineluctable bias against innovation, are its worst offences. `Review by competitors' is an all-too-accurate description of this system, wreaking devastation on papers and proposals [...] ... should not repeat the old canards such as:" despite the problems thrown up by peer review, no serious alternative has yet been proposed." Nonsense. They have not only been proposed but have been in regular use worldwide for a very long time. The users include the world's largest research agency [...] and industrial research worldwide.<<< I omitted many statements - do read the full letter. Fortunately, none of this criticism applies to connectionism and machine learning, where all reviewers are completely objective and unbiased :-) ------------------------------------------------- Juergen Schmidhuber director IDSIA, Galleria 2, 6928 Manno-Lugano, Switzerland juergen at idsia.ch http://www.idsia.ch/~juergen From bruns at cs.tu-berlin.de Fri Dec 14 06:05:32 2001 From: bruns at cs.tu-berlin.de (Camilla Bruns) Date: Fri, 14 Dec 2001 12:05:32 +0100 Subject: EU Advanced Course in Computational Neuroscience Message-ID: <200112141103.MAA17434@mail.cs.tu-berlin.de> EU ADVANCED COURSE IN COMPUTATIONAL NEUROSCIENCE (AN I.B.R.O. NEUROSCIENCE SCHOOL) August 19th - September 13th, 2002, OBIDOS, PORTUGAL DIRECTORS: Klaus Obermayer (Technical University Berlin, Germany) Alessandro Treves (SISSA, Trieste, Italy) Eilon Vaadia (Hebrew University, Jerusalem, Israel) Alain Destexhe (CNRS, Gif-sur-Yvette, France) LOCAL ORGANIZER: Vasco Galhardo (University of Porto, Portugal) The EU Advanced Course in Computational Neuroscience introduces students to the panoply of problems and methods of computational neuroscience, simultaneously addressing several levels of neural organisation, from sub-cellular processes to operations of the entire brain. The course consists of two complementary parts. A distinguished international faculty gives morning lectures on topics in experimental and computational neuroscience. The rest of the day is devoted to practical training, including learning how to use simulation software and how to implement a model of the system the student wishes to study on individual unix workstations. The course gradually introduces students to essential neuroscience concepts and to the most important techniques in modelling single cells, networks and neural systems. Students learn how to apply software packages like GENESIS, MATLAB, NEURON, XPP, etc. to the solution of their problems. The lectures will cover specific brain functions, each week topics ranging from modelling single cells and their biophysical properties to the simulation of simple circuits, large neuronal networks and system level models of the brain. The course ends with a presentation of the students' projects. The EU Advanced Course in Computational Neuroscience is designed for advanced graduate students and postdoctoral fellows in a variety of disciplines, including neuroscience, physics, electrical engineering, computer science and psychology. Students are expected to have a basic background in neurobiology as well as some computer experience. Students of any nationality can apply. A total of 30 students will be accepted. About 20 students will be from the European Union and affiliated countries (Iceland, Israel, Liechtenstein and Norway plus all countries which are negotiating future membership with the EU). These students are supported by the European Commission and we specifically encourage applications from researchers who work in less-favoured regions of the EU and women. There will be no tuition fee but students are expected to pay for travel and part of their subsidence costs. A limited number of fellowships will be available, further informations are on the course website under 'fellowships'. More information and application forms can be obtained: http://www.neuroinf.org/courses Please apply electronically only, using a web browser. Contact address: - mail: Camilla Bruns, Technical University Berlin Faculty of Computer Science, FR 2-1 Franklinstr. 28/29 10587 Berlin, Germany Phone: +49-(0)30-314-73442 Fax: +49-(0)30-314-73121 - e-mail: bruns at cs.tu-berlin.de APPLICATION DEADLINE: April 3, 2002 Applicants will be notified of the results of the selection procedures by May 20, 2002. From Steven_Sloman at brown.edu Fri Dec 14 14:21:34 2001 From: Steven_Sloman at brown.edu (Steven Sloman) Date: Fri, 14 Dec 2001 14:21:34 -0500 Subject: Post-doc at Brown Message-ID: <3C1A5138.33FDC0BF@brown.edu> BROWN UNIVERSITY. Post-doctoral positions available for cognitive or computational scientist. As part of an NSF award to Brown University through the IGERT program, the Departments of Cognitive and Linguistic Sciences, Computer Science, and Applied Mathematics are hiring research associates. The associates should be scholars who have displayed interest and ability in conducting collaborative interdisciplinary research involving a combination of computational and empirical approaches to one of the content areas of the program: cognition, language, or vision. As well as participating in collaborative research, responsibilities will include helping to coordinate cross-departmental events as well as some graduate teaching. Applicants must hold a PhD in Psychology, Linguistics, Cognitive Science, Computer Science, Mathematics, Applied Mathematics, or a related discipline, or show evidence that the PhD will be completed before the start of the position. Applicants should send a vita, a short research statement, three letters of reference, and other supporting material (e.g., representative publications if available), to IGERT Post-doc Search, Department of Cognitive and Linguistic Sciences, Brown University, Box 1978, Providence, RI 02912. Special consideration will be given to those applicants whose research is relevant to at least two of the participating departments. The positions are open immediately for one year, renewable upon satisfactory completion of duties. Salaries will be between $35,000 and $45,000 per year. All materials must be received by Feb. 15, 2002, for full consideration. Like all NSF-funded programs, this opportunity is available only to American citizens and permanent residents. Brown University is an Equal Opportunity/Affirmative Action Employer. For additional information about the program and ongoing research initiatives please visit our website at: http://www.cog.brown.edu/IGERT From marcus at idsia.ch Fri Dec 14 13:35:08 2001 From: marcus at idsia.ch (Marcus Hutter) Date: Fri, 14 Dec 2001 19:35:08 +0100 Subject: Review Time Page Message-ID: <016201c184ce$0f420980$65bfb0c3@idsia.ch> Dear connectionists and other computer scientists, following the discussion on reviewing process in general and reviewing time in particular, I created a page intended to provide a list of average reviewing/revision/publication time of computer science journals. Reviewing time is definitely not the only important measure. Other quantifiable information may be added to the page in time. Still, before deciding to submit something to a particular journal, authors may be interested in the expected waiting time until publication of their submission. And journal editors may be interested whether their journals occupy the top or flop positions regarding reviewing time. Currently the page is virtually empty. Its success relies on your contribution. Please use the form on the web page http://www.idsia.ch/~marcus/journals.htm to submit your own recent experiences with various journals. Suggestions for improvement are welcome. Thanks in advance for your help! Marcus Hutter -------------------------------- Dr. Marcus Hutter, IDSIA Istituto Dalle Molle di Studi sull'Intelligenza Artificiale Galleria 2 CH-6928 Manno(Lugano) - Switzerland Phone: +41-91-6108668 Fax: +41-91-6108661 E-mail marcus at idsia.ch http://www.idsia.ch/~marcus From sfr at unipg.it Sun Dec 16 12:43:00 2001 From: sfr at unipg.it (Simone G.O. Fiori (Pg)) Date: Sun, 16 Dec 2001 18:43:00 +0100 Subject: New papers on neural blind signal processing. Message-ID: <1.5.4.32.20011216174300.01ba5050@unipg.it> Dear Colleagues, I would like to announce three new papers on blind signal processing by neural networks, which might be of interest to people working on principal/independent component analysis, blind system deconvolution, learning on Stiefel-manifold, and probability structure identification. Best wishes for the incoming new year! Kind regards, Simon. =========================================================================== "Blind Deconvolution by Simple Adaptive Activation Function Neuron", S. Fiori, Neurocomputing (full paper) The `Bussgang' algorithm is one among the most known blind deconvolution techniques in the adaptive signal processing literature. It relies on a Bayesian estimator of the source signal that requires the prior knowledge of the source statistics as well as the deconvolution noise characteristics. In this paper we propose to implement the estimator with a simple adaptive activation function neuron, whose activation function is endowed with one learnable parameter; in this way the algorithm does not require to hypothesize deconvolution noise level. Neuron's weights adapt through an unsupervised learning rule that closely recalls non-linear minor component analysis. In order to assess the effectiveness of the proposed method, computer simulations are presented and discussed. Downloadable at: http://www.unipg.it/~sfr/publications/NEUCOM2001.ps ============================================================================ "Probability Density Function Learning by Unsupervised Neurons", S. Fiori, Int. Journal of Neural Systems (full paper) In a recent work we introduced the concept of pseudo-polynomial adaptive activation function neuron (FAN) and presented an unsupervised information- theoretic learning theory for such structure. The learning model is based on entropy optimization and provides a way of learning probability distributions from incomplete data. The aim of the present paper is to illustrate some theoretical features of the FAN neuron, to extend its learning theory to asymmetrical density function approximation, and to provide an analytical and numerical comparison with other known density function estimation methods, with special emphasis to the universal approximation ability. The paper also provides a large survey of PDF approximation via functional expansion on orthogonal bases wrt weighting kernels, which lead to eg the Gram-Charlier expansion, and of PDF learning from incomplete data, as well as results of several experiments performed on real-world problems and signals. One of the experiment presents preliminary results about statistical characterization of the macro- mechanical properties of polypropylene composites reinforced with natural fibers. Downloadable at: http://www.unipg.it/~sfr/publications/IJNS2001.zip ============================================================================ "A Theory for Learning Based on Rigid-Bodies Dynamics", S. Fiori, IEEE Transactions on Neural Networks (full paper) A new learning theory derived from the study of the dynamics of an abstract system of masses, rigidly constrained over mutually-orthogonal immaterial axes and moving in a multidimensional space under an external force field, is presented. The set of rational-kinematic equations describing system's dynamics may be directly interpreted as a learning algorithm for neural layers which preserve the ortho-normality of the connection matrices; as a consequence, the proposed learning theory belongs to the class of strongly-constrained learning paradigms that allow a neural network to learn connection patterns over orthogonal group. Relevant properties of the proposed learning theory are discussed within the paper, along with results of computer simulations performed in order to assess its effectiveness in applied fields. The connections with the general theory of Stiefel-flow learning and the Riemannian gradient theory are also discussed, and the experiments concern optimal data compression by the PCA and signal separation by the ICA. This paper summarizes the work done by the Author on this topic during the last five years. Downloadable at: http://www.unipg.it/~sfr/publications/TNN2001.zip =================================================== Dr Simone Fiori (EE, PhD)- Assistant Professor Dept. of Industrial Engineering (IED) University of Perugia (UNIPG) Via Pentima bassa, 21 - 05100 TERNI (Italy) eMail: sfr at unipg.it - Fax: +39 0744 492925 Web: http://www.unipg.it/~sfr/ =================================================== From John.Carney at PredictionDynamics.com Tue Dec 18 10:50:34 2001 From: John.Carney at PredictionDynamics.com (Dr. John Carney) Date: Tue, 18 Dec 2001 15:50:34 +0000 Subject: JOB ANNOUNCEMENT: Machine Learning Researchers Message-ID: <5.1.0.14.0.20011218143844.02c49908@192.168.2.1> MACHINE LEARNING RESEARCHERS ============================= Prediction Dynamics is a rapidly growing and well-funded software company based in Dublin, Ireland. Our technology leverages the power of machine learning and computational statistics techniques to build powerful non-parametric multi-factor models of financial markets. See www.PredictionDynamics.com for more details. The Product Innovation Group at Prediction Dynamics is currently seeking to recruit a number of researchers with demonstrated expertise in machine learning. Working in the Product Innovation Group, you will be part of a team that is responsible for driving innovation in our core modeling technology. You must be a creative thinker with strong software development and written communication skills. The key responsibilities of this role include: * Researching ground-breaking new approaches to financial time-series modeling using machine learning methods * Implementing these techniques in code and testing them using live financial market data * Publishing technical articles and providing thought leadership Background and experience: * Ph.D. in Machine Learning, Statistics, Computer Science, or a related quantitative discipline * Broad knowledge of most of the following and a specialist knowledge of any one of the following: - Rule extraction - Neural network ensembles - Feature selection - Computational statistics - Time-series modeling - Other machine learning methods e.g. decision trees, k-nearest neighbour * Strong software engineering skills are desirable, especially in C/C++ * Creative thinker, strong written communication skills and a team player A range of experience levels will be considered including those who recently completed a Ph.D./Postdoc and Ph.D.s with several years academic or commercial experience. Prediction Dynamics will offer suitable candidates excellent packages including a competitive salary, stock options, health insurance and pension benefits. The Product Innovation Group is located at our headquarters in Dublin, Ireland. Applicants are asked to send a Resume/CV by e-mail to John.Carney at PredictionDynamics.com. __________________________________ Dr. John Carney Prediction Dynamics 7-8 Mount Street Crescent Dublin 2 Ireland Tel: +353 (1) 439 5000 Fax: +353 (1) 439 5050 Web: www.PredictionDynamics.com ___________________________________ From tgd at cs.orst.edu Mon Dec 17 23:55:24 2001 From: tgd at cs.orst.edu (Thomas G. Dietterich) Date: Mon, 17 Dec 2001 20:55:24 -0800 Subject: reviewing In-Reply-To: <3C19C068.DF68B70@idsia.ch> (message from Juergen Schmidhuber on Fri, 14 Dec 2001 10:03:36 +0100) References: <3C19C068.DF68B70@idsia.ch> Message-ID: <9601-Mon17Dec2001205524-0800-tgd@cs.orst.edu> Hi Juergen, It may be that Nobel prize winners don't benefit from peer review, but I know that many of my papers have been improved as a result of peer review. If you read the acknowledgements sections of the papers published in Machine Learning, Neural Computation, and JMLR, you will often see the authors thanking the referees. I know of several cases where the referees not only identified bugs in proofs, but helped strengthen theorems and simplify proofs. Why is there this difference between machine learning and other discplines? Perhaps because in our young discipline research is not nearly as competitive as it is in mature fields such as physics and biology. A difficulty with physics and biology is that you and your competitors are studying the *same system* and trying to answer exactly the *same questions*. It is a race to publish, "priority" matters, and unscrupulous reviewers can delay a paper unfairly. But in computer science, perhaps because it is a "Science of the Artificial", most work involves developing frameworks, perspectives, analytical techniques, and models, and these rarely compete directly. For all of these, peer review can play an important role in checking the proofs, clarifying the ideas, and improving the presentation. In this way, I think peer review advances the field rather than holding it back. --Tom -- Thomas G. Dietterich Voice: 541-737-5559 Department of Computer Science FAX: 541-737-3014 Dearborn Hall 102 URL: http://www.cs.orst.edu/~tgd Oregon State University Corvallis, OR 97331-3102 From ken at phy.ucsf.edu Tue Dec 18 01:19:57 2001 From: ken at phy.ucsf.edu (Ken Miller) Date: Mon, 17 Dec 2001 22:19:57 -0800 Subject: Paper available: Coding in the cat LGN Message-ID: <15390.57357.976039.276607@coltrane.ucsf.edu> The following paper is available from ftp://ftp.keck.ucsf.edu/pub/ken/LGNPaper.pdf or from http://www.keck.ucsf.edu/~ken (click on 'Publications', then on 'Experimental Results') Liu, R.C., S. Tzonev, S. Rebrik and K.D. Miller (2001). "Variability and information in a neural code of the cat lateral geniculate nucleus." This is a final draft of a paper that has now appeared as Journal of Neurophysiology 86, 2789-2806. Abstract: A central theme in neural coding concerns the role of response variability and noise in determining the information transmission of neurons. This issue was investigated in single cells of the lateral geniculate nucleus of barbiturate anesthetized cats by quantifying the degree of precision in and the information transmission properties of individual spike train responses to full field, binary (bright or dark), flashing stimuli. We found that neuronal responses could be highly reproducible in their spike timing (about 1-2 ms standard deviation) and spike count (about 0.3 ratio of variance/mean, compared to 1.0 expected for a Poisson process). This degree of precision only became apparent when an adequate length of the stimulus sequence was specified to determine the neural response, emphasizing that the variables relevant to a cell's response must be controlled in order to observe the cell's intrinsic response precision. Responses could carry as much as 3.5 bits/spike of information about the stimulus, a rate that was within a factor of two of the limit the spike train can transmit. Moreover, there appeared to be little sign of redundancy in coding: on average, longer response sequences carried at least as much information about the stimulus as would be obtained by adding together the information carried by shorter response sequences considered independently. There also was no direct evidence found for synergy between response sequences. These results could largely, but not entirely, be explained by a simple model of the response in which one filters the stimulus by the cell's impulse response kernel, thresholds the result at a fairly high level, and incorporates a post-spike refractory period. Ken Kenneth D. Miller telephone: (415) 476-8217 Associate Professor fax: (415) 476-4929 Dept. of Physiology, UCSF internet: ken at phy.ucsf.edu 513 Parnassus www: http://www.keck.ucsf.edu/~ken San Francisco, CA 94143-0444 From robtag at unisa.it Wed Dec 19 11:40:36 2001 From: robtag at unisa.it (Roberto) Date: Wed, 19 Dec 2001 17:40:36 +0100 Subject: Call for paper WIRN 2002 Message-ID: <3C20C304.8070101@unisa.it> The 13-th Italian Workshop on Neural Nets WIRN VIETRI-2002 May 30 - June 1, 2002,Vietri Sul Mare, Salerno ITALY CALL FOR PAPERS - FIRST ANNOUNCEMENT Organizing - Scientific Committee B. Apolloni (Univ. Milano), A. Bertoni (Univ. Milano), N. A. Borghese (CNR Milano), D. D. Caviglia (Univ. Genova), P. Campadelli (Univ. Milano), A. Chella (Univ. Palermo), A. Colla (ELSAG Genova), A. Esposito (I.I.A.S.S.), M. Frixione (Univ. Salerno), C. Furlanello (ITC-IRST Trento), G. M. Guazzo (I.I.A.S.S.), M. Gori (Univ. Siena), F. Lauria (Univ. Napoli), M. Marinaro (Univ. Salerno), F. Masulli (Univ. Pisa), C. Morabito (Univ. Reggio Calabria), P. Morasso (Univ. Genova), G. Orlandi (Univ. Roma), T. Parisini (Politecnico Milano), E. Pasero (Politecnico Torino), A. Petrosino (CNR Napoli), V. Piuri (Politecnico Milano), R. Serra (CRA Montecatini Ravenna), F. Sorbello (Univ. Palermo), A. Sperduti (Univ. Pisa), R. Tagliaferri (Univ. Salerno) Topics Mathematical Models, Architectures and Algorithms, Hardware and Software Design, Hybrid Systems, Pattern Recognition and Signal Processing, Industrial and Commercial Applications, Fuzzy Tecniques for Neural Networks Schedule Papers Due: February 15, 2002 Replies to Authors: April 15, 2002 Revised Papers Due: June 1, 2002 Sponsors International Institute for Advanced Scientific Studies (IIASS) "E.R. Caianiello" Dept. of Scienze Fisiche "E.R. Caianiello", University of Salerno Dept. of Matematica ed Informatica, University of Salerno Dept. of Scienze dell'Informazione, University of Milano Societa' Italiana Reti Neuroniche (SIREN) IEEE Neural Network Council INNS/SIG Italy Istituto Italiano per gli Studi Filosofici, Napoli The three-day conference, to be held in the I.I.A.S.S., will feature both introductory tutorials and original, refereed papers, to be published by an International Publishing Company (?) . Official languages are Italian and English, while papers must be in English. Papers should be 6 pages, including title, figures, tables, and bibliography. The accompanying letter should give keywords, postal and electronic mailing addresses, telephone and FAX numbers, indicating oral or poster presentation. Submit 3 copies and a 1 page abstract (containing keywords, postal and electronic mailing addresses, telephone, and FAX numbers with no more than 300 words) to the address shown (WIRN 2002 c/o IIASS). An electronic copy of the abstract should be sent to the E-mail address below. During the Workshop the "Premio E.R. Caianiello" will be assigned to the best Ph.D. thesis in the area of Neural Nets and related fields of Italian researchers. The amount is of 1.000 Euros. The interested researchers (with the Ph.D degree obtained after January 1, 1999 and before March 31 2002) must send 3 copies of a c.v. and of the thesis to "Premio Caianiello" WIRN 2002 c/o IIASS before April 10,2002. A candidate can submit his Ph. D. thesis at most twice. Only SIREN associated are admitted (subscription forms can be downloaded from the SIREN site). For more information, contact the Secretary of I.I.A.S.S. "E.R. Caianiello", Via G.Pellegrino, 19, 84019 Vietri Sul Mare (SA), ITALY Tel. +39 89 761167 Fax +39 89 761189 E-Mail robtag at unisa.it or the SIREN www pages at: http://www-dsi.ing.unifi.it/neural From jose.dorronsoro at iic.uam.es Thu Dec 20 02:39:58 2001 From: jose.dorronsoro at iic.uam.es (Jose Dorronsoro) Date: Thu, 20 Dec 2001 08:39:58 +0100 Subject: ICANN 2002 Final Call for Papers Message-ID: <1.5.4.32.20011220073958.00bf2e48@iic.uam.es> Note: efforts have been made to avoid duplicate postings of this message. Apologies if, nevertheless, you are getting them. ICANN 2002 Second and Final Call for Papers The 12th International Conference on Artificial Neural Networks, ICANN 2002, will be held from August 27 to August 30 2002 at the Universidad Autnoma de Madrid, Spain. ICANN 2002 welcomes contributions on Theory, Algorithms, Applications and Implementations on the following broad Areas: Computational Neuroscience Data Analysis and Pattern Recognition Vision and Image Processing Robotics and Control Signal and Time Series Processing Connectionist Cognitive Science Selforganization. An independent Call for Tutorials, Workshops and Special Sessions has also been issued. You can find more details on this and other ICANN 2002 matters at its web site, www.ii.uam.es/icann2002. ICANN Proceedings will be published in the "Lecture Notes in Computer Science" series of Springer-Verlag. Paper length is restricted to a maximum of 6 pages, including figures. Detailed author instructions are also available at the web site. Submissions will be possible by file uploading or e-mail attach of postscript or pdf files, and also surface mail. All submissions will require to fill out electronically a paper information page. The web pages for this and for file uploads will open in January 7 2002 at the ICANN 2002 site. More details on these matters can also be found in the author instructions. Important deadlines are End of submission receptions: February 15, 2002. Notification of acceptance/rejection: April 15, 2002. Final papers due (in hardcopy and electronically): May 15, 2002. The Conference Calendar will be: August 27, 2002: Tutorials and Workshops August 28-31, 2002: ICANN 2002 Conference For further information and/or contacts, send inquiries to icann2002 at ii.uam.es or to ICANN 2002 Conference Secretariat Mrs. Juana Calle Escuela Tcnica Superior de Informtica Universidad Autnoma de Madrid 28049 Madrid, Spain Jos Dorronsoro ICANN 2002 Chairman jose.dorronsoro at iic.uam.es From S.M.Bohte at cwi.nl Thu Dec 20 03:29:58 2001 From: S.M.Bohte at cwi.nl (Sander Bohte) Date: Thu, 20 Dec 2001 09:29:58 +0100 Subject: Paper available: hebbian learning with time spikes Message-ID: <000201c18930$83d38ec0$81f4a8c0@cwi.nl> The following paper, on computing with precisely times spiking neurons, is available from http://www.cwi.nl/~sbohte/publication/usnnrep.pdf or from http://www.cwi.nl/~sbohte/pub_usnn2k2.htm S.M. Bohte, H. La Poutre and J.N. Kok (2002). "Unsupervised Clustering with Spiking Neurons by Sparse Temporal Coding and Multi-Layer RBF Networks." This is a final draft of a paper that will appear in IEEE Transactions on Neural Networks (2002). Abstract: We demonstrate that spiking neural networks encoding information in the timing of single spikes are capable of computing and learning clusters from realistic data. We show how a spiking neural network based on spike-time coding and Hebbian learning can successfully perform unsupervised clustering on real-world data, and we demonstrate how temporal synchrony in a multi-layer network can induce hierarchical clustering. We develop a temporal encoding of continuously valued data to obtain adjustable clustering capacity and precision with an efficient use of neurons: input variables are encoded in a population code by neurons with graded and overlapping sensitivity profiles. We also discuss methods for enhancing scale-sensitivity of the network and show how the induced synchronization of neurons within early RBF layers allows for the subsequent detection of complex clusters. Keywords: Spiking neurons, unsupervised learning, high-dimensional clustering, complex clusters, Hebbian-learning, synchronous firing, sparse coding, temporal coding, coarse coding. Sander ===================================== Sander Bohte The Netherlands Center for Mathematics and Computer Science (CWI) Dept SEN4 tel: +31-20 592 4926 Kruislaan 413 fax: +31-20 592 4199 NL-1098 SJ Amsterdam www: http://www.cwi.nl/~sbohte The Netherlands mail: sbohte at cwi.nl From erik at bbf.uia.ac.be Thu Dec 20 08:57:38 2001 From: erik at bbf.uia.ac.be (Erik De Schutter) Date: Thu, 20 Dec 2001 14:57:38 +0100 Subject: CNS*2002: Call for papers Message-ID: CALL FOR PAPERS: APPLICATION DEADLINE: February 8, 2002 midnight GMT Eleventh Annual Computational Neuroscience Meeting CNS*2002 July 21 - July 25, 2002 Chicago, Illinois USA http://www.neuroinf.org/CNS.shtml Info at cp at bbf.uia.ac.be CNS*2002 will be held in Chicago from Sunday, July 21, 2002 to Thursday, July 25 in the Congress Plaza Hotel & Convention Center. This is a historic hotel located on Lake Michigan in downtown Chicago. General sessions will be Sunday-Wednesday, Thursday will be a full day of workshops. The conference dinner will be Wednesday night, followed by the rock-n-roll jam session. Papers can include experimental, model-based, as well as more abstract theoretical approaches to understanding neurobiological computation. We especially encourage papers that mix experimental and theoretical studies. We also accept papers that describe new technical approaches to theoretical and experimental issues in computational neuroscience or relevant software packages. The paper submission procedure is new this year: it is at a different web site and makes use of a preprint server. This allows everybody to view papers before the actual meeting and to engage in discussions about submitted papers. PAPER SUBMISSION Papers for the meeting can be submitted ONLY through the web site at http://www.neuroinf.org/CNS.shtml. Papers can be submitted either old style (a 100 word abstract followed by a 1000 word summary) or as a full paper (max 6 typeset pages). In both cases the abstract (100 words max) will be published in the conference program. Submission will occur through a preprint server run by Elsevier, more information can be found on the submission web site. Authors have the option of declaring their submission restricted access, not making it publicly visible. All submissions will be acknowledged by email. It is important to note that this notice, as well as all other communication related to the paper will be sent to the designated correspondence author only. THE REVIEW PROCESS All submitted papers will be first reviewed by the program committee. Papers will be judged and accepted for the meeting based on the clarity with which the work is described and the biological relevance of the research. For this reason authors should be careful to make the connection to biology clear. We reject only a small fraction of the papers (~ 5%) and this usually based on absence of biological relevance (e.g. pure artificial neural networks). We expect to notify authors of meeting acceptance before end of March. The second stage of review involves evaluation of each submission by two independent referees. The primary objective of this round of review will be to select papers for oral and featured oral presentation. In addition to perceived quality as an oral presentation, the novelty of the research and the diversity and coherence of the overall program will be considered. To ensure diversity, those who have given talks in the recent past will not be selected and multiple oral presentations from the same lab will be discouraged. A second objective of the review is to rank papers for inclusion in the conference proceedings. All accepted papers not selected for oral talks as well as papers explicitly submitted as poster presentations will be included in one of three evening poster sessions. Authors will be notified of the presentation format of their papers by end of April. CONFERENCE PROCEEDINGS The proceedings volume is published each year as a special supplement to the journal Neurocomputing. In addition the proceedings are published in a hardbound edition by Elsevier Press. Only papers which are made publicly available on the preprint server, which are presented at the CNS meeting and which are not longer than 6 typeset pages will be eligible for inclusion in the proceedings. Authors who only submitted a 1000 word symmary will be required to submit a full paper to the preprint server. The proceedings size is limited to 1200 pages (about 200 papers). In case more papers are eligible the lowest ranked papers will not be included in the proceedings but will remain available on the preprint server. Authors will be advised of the status of their papers immediately after the CNS meeting. Submission of final papers will be through the preprint server with a deadline early October. For reference, papers presented at CNS*99 can be found in volumes 32-33 of Neurocomputing (2000) and those of CNS*00 in volumes 38-40 (2001). INVITED SPEAKERS: Ad Aertsen (Albert-Ludwigs-University, Germany) Leah Keshet (University British Columbia, Canada) Alex Thomson (University College London, UK) ORGANIZING COMMITTEE: Program chair: Erik De Schutter (University of Antwerp, Belgium) Local organizer: Philip Ulinski (University of Chicago, USA) Workshop organizer: Maneesh Sahani (Gatsby Computational Neuroscience Unit, UK) Government Liaison: Dennis Glanzman (NIMH/NIH, USA) Program Committee: Upinder Bhalla (National Centre for Biological Sciences, India) Avrama Blackwell (George Mason University, USA) Victoria Booth (New Jersey Institute of Technology, USA) Alain Destexhe (CNRS Gif-sur-Yvette, France) John Hertz (Nordita, Denmark) David Horn (University of Tel Aviv, Israel) Barry Richmond (NIMH, USA) Steven Schiff (George Mason University, USA) Todd Troyer (University of Maryland, USA) From Johan.Suykens at esat.kuleuven.ac.be Thu Dec 20 10:12:05 2001 From: Johan.Suykens at esat.kuleuven.ac.be (Johan Suykens) Date: Thu, 20 Dec 2001 16:12:05 +0100 (MET) Subject: NATO-ASI on Learning Theory and Practice Message-ID: <200112201512.QAA10354@euler.esat.kuleuven.ac.be> ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ NATO Advanced Study Institute on Learning Theory and Practice (LTP 2002) July 8-19 2002 - K.U. Leuven Belgium http://www.esat.kuleuven.ac.be/sista/natoasi/ltp2002.html ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ -General Objective- This NATO Advanced Study Institute on Learning Theory and Practice aims at creating a fascinating interplay between advanced fundamental theory and several application areas such as bioinformatics, multimedia/computer vision, e-commerce finance, internet search, textmining and others. It offers an interdisciplinary forum for presenting recent progress and breakthroughs in learning theory with respect to several areas as neural networks, machine learning, mathematics and statistics. -Invited Lecturers- Peter Bartlett (Australian National University Canberra, AUS) Kristin Bennett (Rensselaer Polytechnic Institute New York, USA) Chris Bishop (Microsoft Research Cambridge, UK) Nello Cristianini (Royal Holloway London, UK) Luc Devroye (McGill University Montreal, CAN) Lazlo Gyorfi (T.U. Budapest, HUN) Gabor Horvath (T.U. Budapest, HUN) Rudolf Kulhavy (Honeywell Prague Laboratory, CZ) Vera Kurkova (Academy of Sciences of the Czech Republic, CZ) Joerg Lemm (University of Muenster, GER) Charles Micchelli (IBM T.J. Watson, USA) Tomaso Poggio (MIT, USA) Massimiliano Pontil (University of Siena, IT) Bernhard Schoelkopf (Max-Planck-Institute Tuebingen, GER) Yoram Singer (Hebrew University Jerusalem, IS) Steve Smale (U.C. Berkeley, USA) Johan Suykens (K.U. Leuven, BEL) Vladimir Vapnik (AT&T Labs Research, USA) Mathukumalli Vidyasagar (Tata Consultancy Services, IND) -Organizing committee- Johan Suykens (K.U. Leuven, BEL), Director Gabor Horvath (T.U. Budapest, HUN), Co-director partner country Joos Vandewalle (K.U. Leuven, BEL) Sankar Basu (IBM T.J. Watson, USA) Charles Micchelli (IBM T.J. Watson, USA) -Program and participation- According to the NATO rules http://www.nato.int/science the number of ASI students will be limited to 80. All participants will obtain a *free* registration (including welcome reception, lunches, banquets, refreshments and a NATO-ASI Science Series book to be published with IOS Press). Limited additional funding will be available to cover attendance costs. All interested participants should fill out an application form, taking into account the NATO restrictions. Application form and preliminary program are available at http://www.esat.kuleuven.ac.be/sista/natoasi/ltp2002.html -Venue- The Advanced Study Institute will take place in the Arenberg Castle of the K.U. Leuven Heverlee. The place is surrounded by several restaurants/cafes and parks where one may have a relaxing walk. The historical town of Leuven is within walking distance from the meeting site. Leuven is also well-known for its pleasant atmosphere, pubs and restaurants. -Housing- In addition to hotels rooms, blocks of low cost student rooms are reserved for the ASI students. The student rooms and hotels are located within walking distance from the Arenberg castle meeting site. In order to stimulate the interaction among the participants the option of student rooms will be recommended to all ASI students. -Important Dates- Deadline submission of application form: March 18, 2002 Notification of acceptance: April 30, 2002 NATO-ASI LTP 2002 meeting: July 8-19, 2002 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ From bard at math.pitt.edu Thu Dec 20 13:50:49 2001 From: bard at math.pitt.edu (G. Bard Ermentrout) Date: Thu, 20 Dec 2001 13:50:49 -0500 (EST) Subject: Electronic submission for JCNS Message-ID: Announcing electronic manuscript submission and review for The Journal of Computational Neuroscience Kluwer Academic Publishers is very pleased to announce an agreement with Aries Systems Inc for making use of their fully customized, web-enabled manuscript submission, review and tracking system. Starting December 17, 2001, The Journal of Computational Neuroscience will start to accept online submissions and provide online review services. Authors, editors and reviewers can make use of this system via a special click-able button - My Manuscripts - on the journal's home page http://www.wkap.nl/journals/jcns Processing of manuscripts and communications with authors, editors and reviewers will be entirely electronic. This will reduce the review time substantially as no time is lost in the mail. Authors can submit manuscripts using computer programs they are familiar with, as the system automatically converts, on the fly, submission source files from Word, WordPerfect, .RTF, LaTeX2e, text files, Adobe Postscript files, PDF files, GIF, TIFF, JPEG, PICT graphic files into a single PDF for review distribution. Authors are also entitled to download this PDF file for their own use. Authors can check the status of their manuscripts 24 hours a day, 7 days per week. Role-based (author, editor, reviewer, publisher) security and confidentially is ensured by requiring a user name and password. (The system automatically generates a password when submitting a new manuscript and people can select their own user name). This role-based configuration limits access to a person's role and enables a single- or double-blind review system. Journal of Computational Neuroscience will consider manuscripts either sent by mail or electronically. Manuscripts sent by mail should contain a floppy disk with the electronic file so that the Editorial Office staff can enter the manuscript into the review system and handle it by proxy. Should you have any queries or encounter any problems, please do not hesitate to contact Ms Karen Cullen e-mail: karen.cullen at wkap.com tel: +1 781 871 6600 After extensive internal and external testing of this online submission, review and tracking system we are confident that the service to our authors, editors and reviewers is considerably improved. Your support and cooperation is very much appreciated. Bard Ermentrout Barry Richmond Editors From meesad at okstate.edu Thu Dec 20 10:37:23 2001 From: meesad at okstate.edu (Phayung Meesad) Date: Thu, 20 Dec 2001 09:37:23 -0600 Subject: Extended Call for Papers: IJCNN 2002 (Deadline Dec 24, 2001) Message-ID: <006501c1896c$3821d860$fa384e8b@okstate.edu> Extended Call for Papers: IJCNN 2002 *** Submission Deadline is December 24, 2001. ****** The deadlines for WCCI submissions have been revised in consideration of the recently held FUZZ-IEEE01 meeting (December 2-5, 2001, Melbourne, Australia). Please take advantage of the new December 24, 2001 deadline for submissions to IJCNN. ************************************************************************* * CALL FOR PAPERS 2002 International Joint Conference on Neural Networks (IJCNN2002) May 12-17, 2002 Hilton Hawaiian Village, Honolulu, HI Held as part of the World Congress on Computational Intelligence (http://www.wcci2002.org) The annual IEEE/INNS International Joint Conference on Neural Networks (IJCNN), is one of the premier international conferences in the field. It covers all topics in neural networks, including but not limited to: - supervised, unsupervised and reinforcement learning, - hardware implementation, - time series analysis, - neurooptimization, - neurocontrol, - hybrid architectures, - bioinformatics, - neurobiology and neural modeling, - embedded neural systems, - intelligent agents, - image processing, - rule extraction, - statistics, - chaos, - learning theory, - and a huge variety of applications. The emphasis of the Congress will be on original theories and novel applications of neural networks. The Congress welcomes paper submissions from researchers, practitioners, and students worldwide. IJCNN 2002 will be held in conjunction with the Congress on Evolutionary Computation (CEC) and the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) as part of the World Congress on Computational Intelligence (WCCI). Crossfertilization of the three fields will be strongly encouraged. The Congress will feature keynote speeches and tutorials by world-leading researchers. It also will include a number of special sessions and workshops on the latest hot topics. Your registration admits you to all events and includes the World Congress proceedings and banquet. The new deadline for 6-page paper review submissions is December 24, 2001. The submissions page: https://commerce9.pair.com/nnc/conferences/wcci2002/ijcnn/review/upload.phps Look for more details at http://www.wcci2002.org.=20 From cns at cns.bu.edu Thu Dec 20 14:01:51 2001 From: cns at cns.bu.edu (Boston University CNS Department) Date: Thu, 20 Dec 2001 14:01:51 -0500 Subject: No subject Message-ID: <3C22359F.6050100@cns.bu.edu> PLEASE POST ******************************************************************* GRADUATE TRAINING IN THE DEPARTMENT OF COGNITIVE AND NEURAL SYSTEMS (CNS) AT BOSTON UNIVERSITY ******************************************************************* The Boston University Department of Cognitive and Neural Systems offers comprehensive graduate training in the neural and computational principles, mechanisms, and architectures that underlie human and animal behavior, and the application of neural network architectures to the solution of technological problems. The brochure may also be viewed on line at: http://www.cns.bu.edu/brochure/ and application forms at: http://www.bu.edu/cas/graduate/application. html Applications for Fall 2002 admission and financial aid are now being accepted for both the MA and PhD degree programs. To obtain a brochure describing the CNS Program and a set of application materials, write, telephone, or fax: DEPARTMENT OF COGNITIVE AND NEURAL SYSTEMS Boston University 677 Beacon Street Boston, MA 02215 617/353-9481 (phone) 617/353-7755 (fax) or send via email your full name and mailing address to the attention of Mr. Robin Amos at: amos at cns.bu.edu Applications for admission and financial aid should be received by the Graduate School Admissions Office no later than January 15. Late applications will be considered until May 1; after that date applications will be considered only as special cases. Applicants are required to submit undergraduate (and, if applicable, graduate) transcripts, three letters of recommendation, and Graduate Record Examination (GRE) scores. The Advanced Test should be in the candidate's area of departmental specialization. GRE scores may be waived for MA candidates and, in exceptional cases, for PhD candidates, but absence of these scores will decrease an applicant's chances for admission and financial aid. Non-degree students may also enroll in CNS courses on a part-time basis. ******************************************************************* Description of the CNS Department: The Department of Cognitive and Neural Systems (CNS) provides advanced training and research experience for graduate students and qualified undergraduates interested in the neural and computational principles, mechanisms, and architectures that underlie human and animal behavior, and the application of neural network architectures to the solution of technological problems. The department's training and research focus on two broad questions. The first question is: How does the brain control behavior? This is a modern form of the Mind/Body Problem. The second question is: How can technology emulate biological intelligence? This question needs to be answered to develop intelligent technologies that are well suited to human societies. These goals are symbiotic because brains are unparalleled in their ability to intelligently adapt on their own to complex and novel environments. Models of how the brain accomplishes this are developed through systematic empirical, mathematical, and computational analysis in the department. Autonomous adaptation to a changing world is also needed to solve many of the outstanding problems in technology, and the biological models have inspired qualitatively new designs for applications. During the past decade, CNS has led the way in developing biological models that can quantitatively simulate the dynamics of identified brain cells in identified neural circuits, and the behaviors that they control. This new level of understanding is leading to comparable advances in intelligent technology. CNS is a graduate department that is devoted to the interdisciplinary training of graduate students. The department awards MA, PhD, and BA/MA degrees. Its students are trained in a broad range of areas concerning computational neuroscience, cognitive science, and neuromorphic systems. The biological training includes study of the brain mechanisms of vision and visual object recognition; audition, speech, and language understanding; recognition learning, categorization, and long-term memory; cognitive information processing; self-organization and development, navigation, planning, and spatial orientation; cooperative and competitive network dynamics and short-term memory; reinforcement and motivation; attention; adaptive sensory-motor planning, control, and robotics; biological rhythms; consciousness; mental disorders; and the mathematical and computational methods needed to support advanced modeling research and applications. Technological training includes methods and applications in image processing, multiple types of signal processing, adaptive pattern recognition and prediction, information fusion, and intelligent control and robotics. The foundation of this broad training is the unique interdisciplinary curriculum of seventeen interdisciplinary graduate courses that have been developed at CNS. Each of these courses integrates the psychological, neurobiological, mathematical, and computational information needed to theoretically investigate fundamental issues concerning mind and brain processes and the applications of artificial neural networks and hybrid systems to technology. A student's curriculum is tailored to his or her career goals with an academic and a research adviser. In addition to taking interdisciplinary courses within CNS, students develop important disciplinary expertise by also taking courses in departments such as biology, computer science, engineering, mathematics, and psychology. In addition to these formal courses, students work individually with one or more research advisors to learn how to do advanced interdisciplinary research in their chosen research areas. As a result of this breadth and depth of training, CNS students have succeeded in finding excellent jobs in both academic and technological areas after graduation. The CNS Department interacts with colleagues in several Boston University research centers or groups, and with Boston-area scientists collaborating with these centers. The units most closely linked to the department are the Center for Adaptive Systems and the CNS Technology Laboratory. Students interested in neural network hardware can work with researchers in CNS and at the College of Engineering. Other research resources include the campus-wide Program in Neuroscience, which includes distinguished research groups in cognitive neuroscience, neurophysiology, neuroanatomy, neuropharmacology, and neural modeling across the Charles River Campus and the Medical School; in sensory robotics, biomedical engineering, computer and systems engineering, and neuromuscular research within the College of Engineering; in dynamical systems within the Mathematics Department; in theoretical computer science within the Computer Science Department ; and in biophysics and computational physics within the Physics Department. Key colleagues in these units hold joint appointments in CNS in order to expedite training and research interactions with CNS core faculty and students. In addition to its basic research and training program, the department organizes an active colloquium series, various research and seminar series, and international conferences and symposia, to bring distinguished scientists from experimental, theoretical, and technological disciplines to the department. The department is housed in its own four-story building, which includes ample space for faculty and student offices and laboratories (computational neuroscience, visual psychophysics, psychoacoustics, speech and language, sensory-motor control, neurobotics, computer vision), as well as an auditorium, classroom, seminar rooms, a library, and a faculty-student lounge. The department has a powerful computer network for carrying out large-scale simulations of behavioral and brain models and applications. Below are listed departmental faculty, courses and labs. FACULTY AND STAFF OF THE DEPARTMENT OF COGNITIVE AND NEURAL SYSTEMS AND CENTER FOR ADAPTIVE SYSTEMS Jelle Atema Professor of Biology Director, Boston University Marine Program (BUMP) PhD, University of Michigan Sensory physiology and behavior Helen Barbas Professor, Department of Health Sciences, Sargent College PhD, Physiology/Neurophysiology, McGill University Organization of the prefrontal cortex, evolution of the neocortex Jacob Beck Research Professor of Cognitive and Neural Systems PhD, Psychology, Cornell University Visual perception, psychophysics, computational models of vision Neil Bomberger Research Associate, CNS Technology Laboratory, Department of Cognitive and Neural Systems PhD, Cognitive and Neural Systems, Boston University Daniel H. Bullock Associate Professor of Cognitive and Neural Systems, and Psychology PhD, Experimental Psychology, Stanford University Sensory-motor performance and learning, voluntary control of action, serial order and timing, cognitive development Val Bykoski Research Associate, CNS Technology Laboratory, Department of Cognitive and Neural Systems PhD, Applied Mathematics and Physics, The Russian Academy, Moscow, Russia Gail A. Carpenter Professor of Cognitive and Neural Systems and Mathematics Director of Graduate Studies, Department of Cognitive and Neural Systems PhD, Mathematics, University of Wisconsin, Madison Learning and memory, synaptic processes, pattern recognition, remote sensing, medical database analysis, machine learning, differential equati= ons Michael A. Cohen Associate Professor of Cognitive and Neural Systems and Computer Science PhD, Psychology, Harvard University Speech and language processing, measurement theory, neural modeling, dynamical systems, cardiovascular oscillations physiology and time series H. Steven Colburn Professor of Biomedical Engineering PhD, Electrical Engineering, Massachusetts Institute of Technology Audition, binaural interaction, auditory virtual environments, signal processing models of hearing Howard Eichenbaum Professor of Psychology PhD, Psychology, University of Michigan Neurophysiological studies of how the hippocampal system mediates declarative memory William D. Eldred III Professor of Biology PhD, University of Colorado, Health Science Center Visual neuralbiology David Fay Research Associate, Department of Cognitive and Neural Systems Assistant Director, CNS Technology Laboratory MA, Cognitive and Neural Systems, Boston University John C. Fiala Research Assistant Professor of Biology PhD, Cognitive and Neural Systems, Boston University Synaptic plasticity, dendrite anatomy and pathology, motor learning, robotics, neuroinformatics Jean Berko Gleason Professor of Psychology PhD, Harvard University Psycholinguistics Sucharita Gopal Associate Professor of Geography PhD, University of California at Santa Barbara Neural networks, computational modeling of behavior, geographical information systems, fuzzy sets, and spatial cognition Stephen Grossberg Wang Professor of Cognitive and Neural Systems Professor of Mathematics, Psychology, and Biomedical Engineering Chairman, Department of Cognitive and Neural Systems Director, Center for Adaptive Systems PhD, Mathematics, Rockefeller University Vision, audition, language, learning and memory, reward and motivation, cognition, development, sensory-motor control, mental disorders, applications Frank Guenther Associate Professor of Cognitive and Neural Systems PhD, Cognitive and Neural Systems, Boston University MSE, Electrical Engineering, Princeton University Speech production, speech perception, biological sensory-motor control and functional brain imaging Catherine L. Harris Assistant Professor of Psychology PhD, Cognitive Science and Psychology, University of California at San Di= ego Visual word recognition, psycholinguistics, cognitive semantics, second language acquisition, computational models of cognition Michael E. Hasselmo Associate Professor of Psychology Director of Graduate Studies, Psychology Department PhD, Experimental Psychology, Oxford University Computational modeling and experimental testing of neuromodulatory mechanisms involved in encoding, retrieval and consolidation Allyn Hubbard Associate Professor of Electrical and Computer Engineering PhD, Electrical Engineering, University of Wisconsin Peripheral auditory system (experimental and modeling), chip design spanning the range from straightforward digital applications to exotic sub-threshold analog circuits that emulate the functionality of the visual and auditory periphery, BCS/FCS, the mammalian cochlea in silicon and MEMS, and drug discovery on silicon Richard Ivey Research Associate, CNS Technology Laboratory, Department of Cognitive and Neural Systems MA, Cognitive and Neural Systems, Boston University Thomas G. Kincaid Professor of Electrical, Computer and Systems Engineering, College of Engineering PhD, Electrical Engineering, Massachusetts Institute of Technology Signal and image processing, neural networks, non-destructive testing Mark Kon Professor of Mathematics PhD, Massachusetts Institute of Technology Neural network theory, complexity theory, wavelet theory, mathematical physics Nancy Kopell Professor of Mathematics PhD, Mathematics, University of California at Berkeley Dynamics of networks of neurons Jacqueline A. Liederman Associate Professor of Psychology PhD, Psychology, University of Rochester Dynamics of interhemispheric cooperation; prenatal correlates of neurodevelopmental disorders Ennio Mingolla Professor of Cognitive and Neural Systems and Psychology PhD, Psychology, University of Connecticut Visual perception, mathematical modeling of visual processes Joseph Perkell Adjunct Professor of Cognitive and Neural Systems Senior Research Scientist, Research Lab of Electronics and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology PhD, Massachusetts Institute of Technology Motor control of speech production Adam Reeves Adjunct Professor of Cognitive and Neural Systems Professor of Psychology, Northeastern University PhD, Psychology, City University of New York Psychophysics, cognitive psychology, vision Michele Rucci Assistant Professor of Cognitive and Neural Systems PhD, Scuola Superiore S.-Anna, Pisa, Italy Vision, sensory-motor control and learning, and computational neuroscienc= e Elliot Saltzman Associate Professor of Physical Therapy, Sargent College Research Scientist, Haskins Laboratories, New Haven, CT Assistant Professor in Residence, Department of Psychology and Center for the Ecological Study of Perception and Action, University of Connecticut, Storrs, CT PhD, Developmental Psychology, University of Minnesota Modeling and experimental studies of human sensorimotor control and coordination of the limbs and speech articulators, focusing on issues of timing in skilled activities Robert Savoy Adjunct Associate Professor of Cognitive and Neural Systems Scientist, Rowland Institute for Science Experimental Psychologist, Massachusetts General Hospital PhD, Experimental Psychology, Harvard University Computational neuroscience; visual psychophysics of color, form, and motion perception Teaching about functional MRI and other brain mapping methods Eric Schwartz Professor of Cognitive and Neural Systems; Electrical, Computer and Systems Engineering; and Anatomy and Neurobiology PhD, High Energy Physics, Columbia University Computational neuroscience, machine vision, neuroanatomy, neural modeling Robert Sekuler Adjunct Professor of Cognitive and Neural Systems Research Professor of Biomedical Engineering, College of Engineering, BioMolecular Engineering Research Center Frances and Louis H. Salvage Professor of Psychology, Brandeis University Consultant in neurosurgery, Boston Children's Hospital PhD, Psychology, Brown University Visual motion, brain imaging, relation of visual perception, memory, and movement Barbara Shinn-Cunningham Assistant Professor of Cognitive and Neural Systems and Biomedical Engineering PhD, Electrical Engineering and Computer Science, Massachusetts Institute of Technology Psychoacoustics, audition, auditory localization, binaural hearing, sensorimotor adaptation, mathematical models of human performance David Somers Assistant Professor of Psychology PhD, Cognitive and Neural Systems, Boston University Functional MRI, psychophysical, and computational investigations of visual perception and attention Chantal E. Stern Assistant Professor of Psychology and Program in Neuroscience, Boston University Assistant in Neuroscience, MGH-NMR Center and Harvard Medical School PhD, Experimental Psychology, Oxford University Functional neuroimaging studies (fMRI and MEG) of learning and memory Malvin C. Teich Professor of Electrical and Computer Engineering, Biomedical Engineering, and Physics PhD, Cornell University Quantum optics and imaging, photonics, wavelets and fractal stochastic processes, biological signal processing and information transmission Lucia Vaina Professor of Biomedical Engineering Research Professor of Neurology, School of Medicine PhD, Sorbonne (France); Dres Science, National Politechnique Institute, Toulouse (France) Computational visual neuroscience, biological and computational learning, functional and structural neuroimaging Takeo Watanabe Associate Professor of Psychology PhD, Behavioral Sciences, University of Tokyo Perception of objects and motion and effects of attention on perception using psychophysics and brain imaging (f-MRI) Allen Waxman Research Professor of Cognitive and Neural Systems Director, CNS Technology Laboratory Senior Staff Scientist, MIT Lincoln Laboratory PhD, Astrophysics, University of Chicago Visual system modeling, multisensor fusion, image mining, parallel computing, and advanced visualization Jeremy Wolfe Adjunct Associate Professor of Cognitive and Neural Systems Associate Professor of Ophthalmology, Harvard Medical School Psychophysicist, Brigham & Women's Hospital, Surgery Department Director of Psychophysical Studies, Center for Clinical Cataract Research PhD, Massachusetts Institute of Technology Visual attention, pre-attentive and attentive object representation Curtis Woodcock Professor of Geography Chairman, Department of Geography Director, Geographic Applications, Center for Remote Sensing PhD, University of California, Santa Barbara Biophysical remote sensing, particularly of forests and natural vegetation, canopy reflectance models and their inversion, spatial modeling, and change detection; biogeography; spatial analysis; geographic information systems; digital image processing CNS DEPARTMENT COURSE OFFERINGS CAS CN500 Computational Methods in Cognitive and Neural Systems CAS CN510 Principles and Methods of Cognitive and Neural Modeling I CAS CN520 Principles and Methods of Cognitive and Neural Modeling II CAS CN530 Neural and Computational Models of Vision CAS CN540 Neural and Computational Models of Adaptive Movement Planning and Control CAS CN550 Neural and Computational Models of Recognition, Memory and Attention CAS CN560 Neural and Computational Models of Speech Perception and Production CAS CN570 Neural and Computational Models of Conditioning, Reinforcement= , Motivation and Rhythm CAS CN580 Introduction to Computational Neuroscience GRS CN700 Computational and Mathematical Methods in Neural Modeling GRS CN720 Neural and Computational Models of Planning and Temporal Structure in Behavior GRS CN730 Models of Visual Perception GRS CN740 Topics in Sensory-Motor Control GRS CN760 Topics in Speech Perception and Recognition GRS CN780 Topics in Computational Neuroscience GRS CN810 Topics in Cognitive and Neural Systems: Visual Event Perceptio= n GRS CN811 Topics in Cognitive and Neural Systems: Visual Perception GRS CN911,912 Research in Neural Networks for Adaptive Pattern Recognition GRS CN915,916 Research in Neural Networks for Vision and Image Processing GRS CN921,922 Research in Neural Networks for Speech and Language Processing GRS CN925,926 Research in Neural Networks for Adaptive Sensory-Motor Planning and Control GRS CN931,932 Research in Neural Networks for Conditioning and Reinforcement Learning GRS CN935,936 Research in Neural Networks for Cognitive Information Processing GRS CN941,942 Research in Nonlinear Dynamics of Neural Networks GRS CN945,946 Research in Technological Applications of Neural Networks GRS CN951,952 Research in Hardware Implementations of Neural Networks CNS students also take a wide variety of courses in related departments. In addition, students participate in a weekly colloquium series, an informal lecture series, and student-run special interest groups, and attend lectures and meetings throughout the Boston area; and advanced students work in small research groups. LABORATORY AND COMPUTER FACILITIES The department is funded by fellowships, grants, and contracts from federal agencies and private foundations that support research in life sciences, mathematics, artificial intelligence, and engineering. Facilities include laboratories for experimental research and computational modeling in visual perception; audition, speech and language processing; and sensory-motor control and robotics. Data analysis and numerical simulations are carried out on a state-of-the-art computer network comprised of Sun workstations, Silicon Graphics workstations, Macintoshes, and PCs. A PC farm running Linux operating systems is available as a distributed computational environment. All students have access to X-terminals or UNIX workstation consoles, a selection of color systems and PCs, a network of SGI machines, and standard modeling and mathematical simulation packages such as Mathematica, VisSim, Khoros, and Matlab. The department maintains a core collection of books and journals, and has access both to the Boston University libraries and to the many other collections of the Boston Library Consortium. In addition, several specialized facilities and software are available for use. These include: Active Perception Laboratory The Active Perception Laboratory is dedicated to the investigation of the interactions between perception and behavior. Research focuses on the theoretical and computational analyses of the effects of motor behavior on sensory perception and on the design of psychophysical experiments with human subjects. The Active Perception Laboratory includes extensive computational facilities that allow the execution of large-scale simulations of neural systems. Additional facilities will soon include instruments for the psychophysical investigation of eye movements during visual analysis, including an accurate and non-invasive eye tracker, and robotic systems for the simulation of different types of behavior. Computer Vision/Computational Neuroscience Laboratory The Computer Vision/Computational Neuroscience Laboratory is comprised of an electronics workshop, including a surface-mount workstation, PCD fabrication tools, and an Alterra EPLD design system; a light machine shop; an active vision laboratory including actuators and video hardware; and systems for computer aided neuroanatomy and application of computer graphics and image processing to brain sections and MRI images. The laboratory supports research in the areas of neural modeling, computational neuroscience, computer vision and robotics. The major question being address is the nature of representation of the visual world in the brain, in terms of observable neural architectures such as topographic mapping and columnar architecture. The application of novel architectures for image processing for computer vision and robotics is also a major topic of interest. Recent work in this area has included the design and patenting of novel actuators for robotic active vision systems, the design of real-time algorithms for use in mobile robotic applications, and the design and construction of miniature autonomous vehicles using space-variant active vision design principles. Recently one such vehicle has successfully driven itself on the streets of Boston. Neurobotics Laboratory The Neurobotics Laboratory utilizes wheeled mobile robots to study potential applications of neural networks in several areas, including adaptive dynamics and kinematics, obstacle avoidance, path planning and navigation, visual object recognition, and conditioning and motivation. The laboratory currently has three Pioneer robots equipped with sonar and visual sensors; one B-14 robot with a moveable camera, sonars, infrared, and bump sensors; and two Khepera miniature robots with infrared proximity detectors. Other platforms may be investigated in the future. Psychoacoustics Laboratory The Psychoacoustics Laboratory in the Department of Cognitive and Neural Systems (CNS) is equipped to perform both traditional psychoacoustic experiments as well as experiments using interactive auditory virtual-reality stimuli. The laboratory contains approximately eight PCs (running Windows 98 and/or Linux), used both as workstations for students and to control laboratory equipment and run experiments. The other major equipment in the laboratory includes special-purpose signal processing and sound generating equipment from Tucker-Davis Technologies, electromagnetic head tracking systems, a two-channel spectrum analyzer, and other miscellaneous equipment for producing, measuring, analyzing, and monitoring auditory stimuli. The Psychoacoustics Laboratory consists of three adjacent rooms in the basement of 677 Beacon St. (the home of the CNS Department). One room houses an 8 ft. =B4 8 ft. single-walled sound-treated booth as well as space for students. The second room is primarily used as student workspace for developing and debugging experiments. The third space houses a robotic arm, capable of automatically positioning a small acoustic speaker anywhere on the surface of a sphere of adjustable radius, allowing automatic measurement of the signals reaching the ears of a listener for a sound source from different positions in space, including the effects of room reverberation. Sensory-Motor Control Laboratory The Sensory-Motor Control Laboratory supports experimental and computational studies of sensory-motor control. A computer controlled infrared WatSmart system allows measurement of large-scale (e.g. reaching) movements, and a pressure-sensitive graphics tablet allows studies of handwriting and other fine-scale movements. A second major component is a helmet-mounted, video-based, eye-head tracking system (ISCAN Corp, 1997). The latter's camera samples eye position at 240Hz and also allows reconstruction of what subjects are attending to as they freely scan a scene under normal lighting. Thus the system affords a wide range of visuo-motor studies. The laboratory is connected to the department's extensive network of Linux and Windows workstations and Linux computational servers. Speech and Language Laboratory The Speech Laboratory includes facilities for analog-to-digital and digital-to-analog software conversion. Ariel equipment allows reliable synthesis and playback of speech waveforms. An Entropic signal-processing package provides facilities for detailed analysis, filtering, spectral construction, and formant tracking of the speech waveform. Various large databases, such as TIMIT and TIdigits, are available for testing algorithms of speech recognition. The laboratory also contains a network of Windows-based PC computers equipped with software for the analysis of functional magnetic resonance imaging (fMRI) data, including region-of-interest (ROI) based analyses involving software for the parcellation of cortical and subcortical brain regions in structural MRI images. Technology Laboratory The Technology Laboratory fosters the development of neural network models derived from basic scientific research and facilitates the transition of the resulting technologies to software and applications. The Technology Laboratory was established in July 2001, with a five-year $2,500,000 grant from the Air Force Office of Scientific Research (AFOSR), "Information Fusion for Image Analysis: Neural Models and Technology Development." Initial applied research projects are developing methods for multi-sensor data and information fusion, utilizing multi-spectral and high-resolution stereo imagery from satellites, in conjunction with simulated ELINT (emitter locator intelligence) and GMTI (ground moving target indicator) data and contextual terrain data. Fusion and data mining methods are being developed in a geospatial context, building on models of opponent-color visual processing, boundary contour system (BCS) and texture processing, Adaptive Resonance Theory (ART) pattern learning and recognition, and other models of associative learning and prediction. Multi-modality presentation of fused sensor data and information to human operators is studied in the context of a Common Operating Picture. A related defense application is real-time 3D fusion of low-light visible, thermal infrared, and ladar imagery, for advanced night vision systems incorporating target learning and search. Other research topics include multi-pass search by incorporation of feedback in the classification-to-search pathway for fused image mining, thereby treating classification decisions as context for further search, and multi-spectral MRI and multi-modality medical image fusion. Associated basic research projects are conducted within the joint context of scientific data and technological constraints. The laboratory effort also includes collaborative technology transfer to government laboratories and commercial industry. Under the sponsorship of the National Imagery and Mapping Agency (NIMA), software for multi-sensor image fusion and data mining is being incorporated into the commercial software suite Imagine by ERDAS Corporation. Related efforts aim to create a Matlab toolbox for interactive neural processing of imagery, signals, and patterns, and technology transfer into RSI/Kodak's ENVI software and the geospatial information software ArcGIS from ESRI Corporation. The Director of the Technology Laboratory, Professor Allen Waxman, and the Assistant Director, David Fay, recently joined the CNS Department after collaborating for twelve years at MIT Lincoln Laboratory. The laboratory continues to grow rapidly, with three research associates, one postdoctoral fellow, and four graduate students, as well as faculty from CNS and the Center for Remote Sensing, currently associated with application, implementation, and basic and applied research projects. Dedicated equipment includes six high-end graphics PCs with dual-headed stereo monitors, two SGI O2 workstations, a Sun UltraSparc 10 workstation, a wall-sized stereo projection display system, a large Cybermation mobile robot, and CCD video cameras with real-time image acquisition and processing using Genesis DSP boards from Matrox. The Technology Laboratory occupies 1000 square feet in the CNS building, including a "dark room" for night vision research and a well-equipped conference room. Visual Psychophysics Laboratory The Visual Psychophysics Laboratory occupies an 800-square-foot suite, including three dedicated rooms for data collection, and houses a variety of computer controlled display platforms, including Macintosh, Windows and Linux workstations. Ancillary resources for visual psychophysics include a computer-controlled video camera, stereo viewing devices, a photometer, and a variety of display-generation, data-collection, and data-analysis software. Affiliated Laboratories Affiliated CAS/CNS faculty members have additional laboratories ranging from visual and auditory psychophysics and neurophysiology, anatomy, and neuropsychology to engineering and chip design. These facilities are used in the context of faculty/student collaborations. ******************************************************************* DEPARTMENT OF COGNITIVE AND NEURAL SYSTEMS GRADUATE TRAINING ANNOUNCEMENT Boston University 677 Beacon Street Boston, MA 02215 Phone: 617/353-9481 Fax: 617/353-7755 Email: inquiries at cns.bu.edu Web: http://www.cns.bu.edu/ ******************************************************************* From Henry.Markram at weizmann.ac.il Thu Dec 20 05:29:33 2001 From: Henry.Markram at weizmann.ac.il (bnmark) Date: Thu, 20 Dec 2001 12:29:33 +0200 Subject: new Brain Mind Institute at the EPFL/ETH/Swiss Federal Institute of Technology Message-ID: <3C21BD8D.BBD2D5CB@weizmann.ac.il> Dear Friends and Colleagues, I am moving my lab to the new Brain Mind Institute at the EPFL/ETH/Swiss Federal Institute of Technology in Lausanne in 2002 and would like to draw your attention to this new Institute and to positions being offered. It is a rare opportunity to start a Brain Mind Institute that is unconstrained by tradition, in the form of a network of closely related labs, on a foundation of futuristic technology, in a manner that can be recurrently interconnected with labs around the world and a vision to go beyond established concepts to explore the emergence of the mind. We would like to invite your participation in letting outstanding new thinkers know about positions available at the BMI and invite you to join programs and initiate new collaborations, as the BMI takes shape over the next few years. Vision of the Brain Mind Institute: - a network of labs addressing the emergence of higher brain function across key levels - each with a focus at a particular level, but with extensive overlapping levels, interests and techniques. We believe this structure is important to form a maximally catalytic environment =96 a recurrent environment for individual groups and a concerted team effort for the Institute. - Multidisciplinary groups that employ a spectrum of techniques ranging from molecular biology, protein chemistry, biophysics, electrophysiology, imaging, psychophysics, fMRI to computational modeling. - Establish groups that can capitalize on the immense technological playground that the EPFL offers to develop new techniques that go beyond the frontiers of Neuroscience. (Sticking wires in the brain will probably be seen as archaic technology in the near future!) Special funding will be available for visionary and exploratory research and development of new technologies to explore emergence of higher brain function. - The physical, psychological, and intellectual borders between labs will be reduced to a minimum with an emphasis on shared technology, equipment, approaches, students etc. - Groups will be able to address their questions staring from their level of expertise all the way down to the genetic level and all the way up to fMRI level and to theories of mind. - The BMI will also be composed of scientists in key labs throughout Switzerland and will form a network of collaborations with the University of Lausanne, Geneva, ETH Zurich, The Institute for Neuroinformatics in Zurich and many labs around Europe, the USA and Japan. - We will offer students and postdocs a comprehensive Neuroscience Program from genes to mind which will be integrated with the latest experimental, technological, mathematical, physical, and computational methods. - An extensive visiting scientist and student exchange program will be in place to facilitate world-wide interaction and collaboration. - We hope to have as many revolutionary ideas participate in the adventure as possible! Multilevel and Recurrent Structure of the BMI: 1. Dynamics of Gene Expression: a. Develop new approaches to understand, modulate, and repair genes in the nervous system. b. Isolate key genes underlying structure and function. c. Dynamics of gene networks d. How gene network activity is controlled by the biochemical and electrical activity of neurons. 2. Behavioral Genetics, Models of Disease & Gene Therapy: a. A focus on gene alterations in disease and new approaches in gene therapy. b. A focus on gene modulation as a function of behavioral experience. c. Development of sensory surgical therapies to detour genetic expression around critical stages (using virtual reality environments). 3. Protein Expression, Targeting, and Localization: a. Spatial and temporal dynamics of protein expression, targeting, and localization in neurons =96 axon, somata, dendrites and synapses b. Algorithms to construct and maintain neuronal structure and function. 4. Biochemical Dynamics of Neurons: a. Dynamics of biochemical pathways as well as cross-cellular orchestration of biochemical networks in response to genetic and electrical activity (multi-protein imaging & protein-protein interactions in single and networks of neurons etc). 5. Molecular Biology and Biophysics of Ion Channels and Receptors: a. A focus on isolating the different genetic expression patterns of ion channels and receptors in different types of neurons and determining their biophysical and computational functions. 6. Synaptic Integration: a. A focus on voltage and electrical dynamics in neurons where principles of morphology, ion channel constellations, their spatial distributions, and synaptic input organization underlie neural computation. 7. Neural Microcircuitry: a. Principles of microcircuit design (gene expression, synapses, neurons & connectivity). b. Information processing, representation, and transformation in microcircuits. c. Plasticity of the microcircuitry as a function of genetic predisposition, experience, and behavior. 8. Neural Network Dynamics, Systems: a. Orchestrated activity in networks of neurons (mega multiunit recordings in vivo, multi-neuron patch clamp in vivo, in vivo intrinsic and voltage imaging etc) in the exploration of the neural code and integration of sensory modalities. 9. Behavioral Neuroscience: a. A focus on integrative perception (integration across sensory modalities), attention and memory using behavioral paradigms, psychophysical techniques, and fMRI. 10. Computational Neuroscience: a. Explore the computational power of neural structure and function. b. Reconstruct neural structure and function (The first comprehensive (genes, physiology, morphology, microcircuitry) database of a reconstruction of a several thousand neuron rodent neocortical microcircuit will be located at the BMI). c. Models from genes to behavior simulating the emergence of function. d. Genetic, molecular, physiological, anatomical, and learning algorithms to automatically synthesize realistic neural microcircuits and networks. e. Hardware implementation of neural microcircuits and models. f. Robotics. g. Neuroinformatics. 11. Theories of Mind: a. History and Philosophy of Neuroscience. b. Theories of information representation, transformation, and propagation. c. Theories of consciousness. d. Exploring the physical basis of Mind. e. The Mind-Body Problem. The BMI will develop in several phases: In the first phase, we are considering applications for all the levels above and around March, 2002 we will decide on the sequence and development of the groups at the BMI based on the research proposals received. There is an emphasis on tenure track, but several full professor tenured positions are also being considered. Over the next 4 years, we plan to fill up to 16 faculty positions. Groups sizes may reach up to 30 people. Generous startup and permanent basic annual funding is offered. Extra support for collaborations with the Math, Computer Science, Robotics, and Virtual Reality Institutes at the EPFL. The criteria for evaluating research proposals and applications: Our goal is to explore the emergence of higher brain function from multiplex perspectives and across multiple levels. 1. Identify the key issue(s) at your particular level of expertise and argue how this issue may be pivotal in opening a new door to understanding higher brain function. The BMI will further invite those strong proposals that are exciting, revolutionary, and even high risk. The BMI is not aiming to compete with traditional research around the world. 2. Describe how addressing the isolated issue(s) requires a multilevel approach and interdisciplinary collaborations. 3. Describe how the proposed research could capitalize on the EPFL=92s strength in engineering, mathematics, computer sciences, and physics to create new technologies and approaches to exploring the emergence of higher brain function. Please send this email to anyone you think may be interested in applying: Please send Proposals and Applications to: School of Life Sciences AA-B 1.07 CH-1015 Lausanne E-mail: life.sciences at epfl.ch Tel: ++41 21 693 53 61 FAX: ++41 21 693 53 69 Indicate 3-7 potential referees that may provide letters of recommendation. My lab in the BMI will focus on neocortical microcircuitry and will be composed of 4 related parts: A: Genetic and molecular basis of the structure and function of the microcircuit; B: Synaptic, cellular and network physiology of the microcircuit; C: Synaptic, cellular and microcircuit anatomy; D: Computation in microcircuits (reconstructing microcircuits; theory, simulations, virtual reality microcircuits, hardware implementations). Techniques and approaches used to address these questions will span all the levels indicated above. Please let any bright stars entering the PhD or postdoctoral levels know that several positions are open. (send email to, henry.Markram at weizmann.ac.il.) Thanks & all the best, Yours, Henry ================ From brian at mail4.ai.univie.ac.at Fri Dec 21 12:28:49 2001 From: brian at mail4.ai.univie.ac.at (Brian Sallans) Date: Fri, 21 Dec 2001 18:28:49 +0100 (CET) Subject: Thesis announcement Message-ID: <200112211728.SAA23147@fichte.ai.univie.ac.at> Dear connectionists, I am pleased to announce the availability of my PhD thesis: Reinforcement Learning for Factored Markov Decision Processes Brian Sallans University of Toronto Abstract: http://www.ai.univie.ac.at/~brian/pthesis/pthabstract.html Download: http://www.ai.univie.ac.at/~brian/pthesis/ This thesis discusses the combination of learning and inference in graphical models with reinforcement learning. It may be of interest to researchers working in either area. The thesis is available in PostScript, PDF or HTML format. There is also Matlab code implementing the experimental tasks used in the thesis. ---------------------- Brian Sallans brian at ai.univie.ac.at Austrian Research Institute for Artificial Intelligence URL: http://www.ai.univie.ac.at/~brian Schottengasse 3 tel: +43-1-5336112-15 From palm at neuro.informatik.uni-ulm.de Fri Dec 21 10:04:24 2001 From: palm at neuro.informatik.uni-ulm.de (Guenther Palm) Date: Fri, 21 Dec 2001 16:04:24 +0100 Subject: two Neural Networks special sessions at KES 2002 Message-ID: <3C234F78.CA67E268@neuro.informatik.uni-ulm.de> Dear Connectionists, I am organizing a Special Session on "Neural Pattern Recognition" at the Sixth International Conference on Knowledge-Based Intelligent Information Engineering Systems (KES 2002), to be held at Podere d'Ombriano, Crema, Italy, September 16 - 18, 2002. The idea of the Special Session is to discuss possibilities, ideas and methods for the analysis of the activity (or connectivity) in real biological neural networks by artificial neural networks. This includes such topics as spike-train analysis of single or multiple recordings, functional brain imaging, EEG or MEG analysis. Potential contributors to this Special Session are invited to send a short (at most one page) abstract until 01.02.2002. The abstracts will be selected and the topical foci of the Special Session will be determined until 01.03.2002. The selected authors will be asked to submit an up to 5 pages paper before 15.04.2002 and these papers will be reviewed. We hope to complete this review process before the end of May, which is before the early registration deadline for the conference. More information on the conference can be found on the web site http://www.bton.ac.uk/kes/kes2002/ The conference proceedings will be published worldwide by IOS Press, Amsterdam. Guenther Palm Neural Information Processing University of Ulm Germany ================================================================ Dear Connectionists, I am organizing a Special Session on "Neural Networks Understanding Language" at the Sixth International Conference on Knowledge-Based Intelligent Information Engineering Systems (KES 2002), to be held at Podere d'Ombriano, Crema, Italy, from September 16 - 18, 2002. The idea of the Special Session is to bring together researchers who try to use artificial neural networks for language understanding. The focus will be on higher cognitive levels of language, concerning syntax, semantics and pragmatics of language use, language learning and aspects of neuro- or psycho-linguistics, but for example not speech recognition alone. After the first wave of neural networks it may now be the right time to assess the state of the art in this area which can also be crucial for an understanding of the impact of artificial neural network research in areas of traditionally more symbolic artificial intelligence. Potential contributors to this Special Session are invited to send a short (at most one page) abstract until 01.02.2002. The abstracts will be selected and the topical foci of the Special Session will be determined until 01.03.2002. The selected authors will be asked to submit an up to 5 pages paper before 15.04.2002 and these papers will be reviewed. We hope to complete this review process before the end of May, which is before the early registration deadline for the conference. More information on the conference can be found on the web site http://www.bton.ac.uk/kes/kes2002/ The conference proceedings will be published worldwide by IOS Press, Amsterdam. Guenther Palm Neural Information Processing University of Ulm Germany From bogus@does.not.exist.com Fri Dec 21 20:10:01 2001 From: bogus@does.not.exist.com () Date: Sat, 22 Dec 2001 01:10:01 +0000 Subject: Adaptive Brain Interfaces Message-ID: Hi, at http://sta.jrc.it/abi you can find info about the very interesting Esprit Project Adaptive Brain Interfaces. jbf. [ Moderator's note: here are the first three paragraphs from that web page: "The objective of the ABI project is to use EEG signals as an alternative means of interaction with computers. We seek to recognise five mental states from on-line spontaneous EEG signals by means of artificial neural networks, which are associated to simple commands. For instance, to select an item from a computer screen it suffices 5 mental states; four of them will move the pointer "up", "down", "left", and "right", while the fifth pattern will "click" and activate the item underneath the pointer. We seek to build individual brain interfaces rather than universal ones valid for everybody and forever. Our approach is based on a mutual learning process whereby the individual user and the ABI are coupled and adapt to each other: a neural network learns user-specific EEG patterns describing the mental tasks while subjects learn to think in such a way that they are better understood by their personal interface. In other words, every single user chooses his/her most natural mental tasks to concentrate on (e.g., relaxation, visualisation, music composition, arithmetic, preparation of movements) and also the preferred strategies to undertake those tasks. Another concern of this project is the robust recognition of EEG patterns outside laboratory settings. This presumes the existence of an appropriate EEG equipment that should be compact, easy-to-use, and suitable for deployment in natural environments. No such a commercial EEG system exists, and we will manufacture an appropriate helmet with integrated and amplified electrodes." ] From samwang at molbio.princeton.edu Fri Dec 21 20:41:24 2001 From: samwang at molbio.princeton.edu (Samuel Wang) Date: Fri, 21 Dec 2001 20:41:24 -0500 Subject: Graduate training in neuroscience at Princeton University Message-ID: <3C23E4C4.24CF2D97@molbio.princeton.edu> GRADUATE TRAINING IN NEUROSCIENCE AT PRINCETON UNIVERSITY *** Graduate application deadline for September admissions: January 2, 2002. *** Graduate study at Princeton University offers interdisciplinary training in all areas of neuroscience. Recent rapid growth at Princeton has opened numerous research opportunities for students and postdocs interested in molecular, cellular, and quantitative/computational approaches to fundamental problems in neuroscience. Furthermore, the imminent opening of the Lewis-Sigler Institute for Integrative Genomics brings exciting new opportunities for chemistry, physics and engineering to be brought to bear on problems in biology, including neuroscience. Graduate training in neuroscience at Princeton is supported by a training grant from the National Institutes of Health. Faculty include: Michael Berry - Neural computation in the retina William Bialek - The interface between physics and biology Jonathan Cohen - Neural bases of cognitive control Lynn Enquist - Neurovirology Michale Fee - Motor control and sequence generation in birdsong Alan Gelperin - Olfaction Elizabeth Gould - Neurogenesis and hippocampal function Michael Graziano - Motor control and perceptual representations in cortex Charles Gross - Visual perception and visual learning Michaela Hau - Neuroendocrinology Bartley Hoebel - Neural circuits for reinforcement of behavior and cognition Philip Holmes - Modeling of neural systems John Hopfield - Computational neurobiology / biophysics Sabine Kastner - Attention Barry Jacobs - Neural substrates of arousal and emotion Partha Mitra - Engineering principles in biological systems Ken Norman - Neural bases of episodic memory Jeffry Stock - Membrane receptors and signal transduction David Tank - Measurement and analysis of neural circuit dynamics Frank Tong - Attention and perception Anne Treisman - Attention and intention Joe Tsien - Molecular bases and neural coding of learning and memory Samuel Wang - Dynamics and learning in neural circuits; brain evolution Eric Wieschaus - Embryonic development of Drosophila melanogaster Students are admitted for study through the Departments of Molecular Biology, Physics, or Psychology. Once admitted, students must meet the degree requirements of the department to which he/she is admitted. Applications may be submitted via the Princeton Web site: https://apply.embark.com/Grad/Princeton/23/ Further information about specific departments may be obtained from: Department of Molecular Biology - http://www.molbio.princeton.edu Elena Chiarchiaro, Program Administrator elenach at princeton.edu Dr. David Tank dwtank at princeton.edu Department of Physics - http://pupgg.princeton.edu/ Laurel Lerner laurel at pupgg.princeton.edu Dr. William Bialek wbialek at princeton.edu Department of Psychology - http://www.princeton.edu/~psych/ Arlene Kerch, Program Administrator arlener at princeton.edu Dr. Elizabeth Gould goulde at princeton.edu Lewis-Sigler Institute for Integrative Genomics http://www.genomics.princeton.edu/ Princeton University is located in Princeton, New Jersey. Its campus covers approximately 500 acres and is one of the most beautiful in the Ivy League. It is located approximately one hour (by train) south of New York City and one hour northeast of Philadelphia. From mayank at MIT.EDU Mon Dec 24 20:35:22 2001 From: mayank at MIT.EDU (Mayank R Mehta) Date: Mon, 24 Dec 2001 20:35:22 -0500 (EST) Subject: Paper available Message-ID: The following article has recently appeared in print and can be downloaded from my home page http://www.mit.edu/~mayank Title: Neuronal Dynamics of Predictive Coding Author: Mayank R. Mehta Journal: The Neuroscientist, 7:490-495 (2001) Abstract: A critical task of the central nervous system is to learn causal relationships between stimuli in order to anticipate events in the future, such as the position of a moving prey or predator. What are the neuronal phenomena underlying anticipation? In this article we review recent results in hippocampal electrophysiology that shed light on this issue. It is shown that the hippocampal spatial receptive fields show large and rapid anticipatory changes in their firing characteristics. These changes are experience- and environment-dependent and can be explained by a computational model based on NMDA-dependent synaptic plasticity during behavior. Striking similarities between the anticipatory network dynamics of widely different neural circuits, such as the hippocampus and the primary visual cortex, are discussed. These experimental and theoretical results indicate how the macroscopic laws of synaptic plasticity give rise to emergent anticipatory properties of receptive fields and behavior. ------------------ Cheers! -Mayank -----------------------+----------------------------+ Mayank R. Mehta | Email: Mayank at MIT.edu | E18-366, M.I.T. | Phone: 617 252 1841 | 50 Ames St. | FAX: 617 452 4120 | Cambridge, MA 02139 | http://www.mit.edu/~mayank | -----------------------+----------------------------+ From malchiodi at dsi.unimi.it Thu Dec 27 11:15:11 2001 From: malchiodi at dsi.unimi.it (Dario Malchiodi) Date: Thu, 27 Dec 2001 17:15:11 +0100 Subject: Course at the International School on Neural Nets "E.R.Caianiello" - Extended deadline Message-ID: <3C2B490F.3000505@dsi.unimi.it> Many apologizes for cross-posting The following meeting may be of interest to researchers interested in artificial intelligence, biology, neural networks and psychology FROM SYNAPSES TO RULES: DISCOVERING SYMBOLIC RULES FROM NEURAL PROCESSED DATA A course of INTERNATIONAL SCHOOL ON NEURAL NETS "E. R. CAIANIELLO" ETTORE MAJORANA CENTRE FOR SCIENTIFIC CULTURE ERICE-SICILY: 25 FEBRUARY - 7 MARCH 2002 Application deadline: December 15, 2001, extended to January 20, 2002. The school aims at fixing a theoretical and applicatry framework for extracting formal rules from data. To this end the modern approaches will be expounded that collapse the two typical goals of the conventional AI and connectionism - respectively, deducing within an axiomatic shell formal rules about a phenomenon and inferring the actual behavior of it from examples - into a challenging inferential framework where we learn from data and understand what we have learnt. The target reads as a translation of the subsymbolic structure of the data - stored in the synapses of a neural network - into formal properties described by rules. To capture this trip from synapses to rules and then render it manageable for affording real world learning tasks, the Course will deal in depth with the following aspects: i. theoretical foundations of learning algorithms and soft computing, ii. intimate relationships between symbolic and subsymbolic reasoning methods, iii. integration of the related hosting architectures in both physiological and artificial brain. TOPICS Inferential bases for learning Theoretical foundations for soft computing Integration of symbolic-subsymbolic reasoning methods Physics and metaphysics of learning Toward applications LECTURERS * B. Apolloni, University of Milan, I * D. Malchiodi, University of Milan, I * D. Mundici, University of Milan, I * M. Gori, University of Siena, I * F. Kurfess, California Polytechnic State Univ., San Luis Obispo, CA, USA * A. Roy, Arizona State University, Tempe, AZ, USA * R. Sun, University of Missouri-Columbia, MO, USA * L. Agnati, Karolinska Institutet, Stockholm, S * G. Basti, Pontificia Universit? Lateranense, Rome, I * G. Biella, C.N.R. LITA, Milan, I * J. G. Taylor, King's College, London, UK * A. Esposito, Istituto Italiano Alti Studi Scientifici, Vietri, I * A. Moise, Boise State University, ID, USA DIRECTORS OF THE COURSE B. APOLLONI, A. MOISE DIRECTORS OF THE SCHOOL M. J. JORDAN, M. MARINARO DIRECTOR OF THE CENTRE A. ZICHICHI APPLICATIONS Interested candidates should send a letter to: * Professor Bruno Apolloni - Dipartimento di Scienze dell'Informazione Universit? degli Studi di Milano Via Comelico 39/41 20135 Milano, Italy Tel: ++39.02.5835.6284, Fax: ++39.02.5835.6228 e-mail: apolloni at dsi.unimi.it specifying: i) date and place of birth and present activity; ii) nationality. Thanks to the generosity of the sponsoring Institutions, partial support can be granted to some deserving students who need financial aid. Requests to this effect must be specified and justified in the letter of application. Notification of acceptance will be sent within the end of January 2002. For APPLICATION, CONTRIBUTING PAPERS, GRANTS, FEES, and further information please visit http://laren.usr.dsi.unimi.it/ericeSchool.html. For information about the Ettore Majorana Centre please visit http://www.ccsem.infn.it