From moodylab at ICSI.Berkeley.EDU Mon Aug 2 23:06:18 2004 From: moodylab at ICSI.Berkeley.EDU (Moody Lab) Date: Mon, 2 Aug 2004 20:06:18 -0700 (PDT) Subject: Postdoc -- Reinforcement Learning & Finance Message-ID: INTERNATIONAL COMPUTER SCIENCE INSTITUTE Berkeley & Portland Post-Doc / Research Scientist in Machine Learning & Computational Finance Preferred Start Dates: September - December 2004 DESCRIPTION: The International Computer Science Institute (ICSI) invites applications for a one to two year Post-Doctoral Fellow or Research Scientist position that is part of a project directed by Prof. John Moody and funded by the National Science Foundation entitled "Risk, Reward and Reinforcement". This interdisciplinary investigation is exploring powerful, new algorithms for Direct Reinforcement and the application of these algorithms to games, multi-agent systems and important, real-world financial problems. Activities include fundamental algorithms research, extensive simulation and empirical testing. Substantial financial market data resources under development at ICSI are available for application prototype development. The goals are to create highly effective and efficient algorithms for Direct Reinforcement that can discover robust solutions to challenging, dynamic, real-world problems. ICSI is an independent, nonprofit research institute with headquarters in Berkeley, California. It is closely affiliated with the University of California at Berkeley. ICSI is funded by the U.S. and several European governments, and brings together top researchers from participating countries. This ICSI project will be based in Portland, Oregon, which offers exceptional quality of life and was recently named America's "Best Big City". See http://www.moneymag.com/best/bplive/portland.html . The successful candidate will have opportunities to interact with researchers at ICSI, UC Berkeley, and other leading Northwest and West Coast universities. QUALIFICATIONS: Candidates must have a Ph.D. or comparable research experience in computer science, an engineering, physical or mathematical science or a quantitative social science such as economics or finance. Strong mathematical, statistical and computational skills are required. Ideally, applicants should have expertise in two or more of the following topics: machine learning (especially reinforcement learning), Monte Carlo methods, nonparametric statistics, time series analysis, optimization, control engineering or quantitative finance. Preference will be given to candidates who are about to complete or have completed a Ph.D. within the past three years. Exceptionally well-qualified non- Ph.D. candidates with three to five years of relevant professional experience may also be considered. APPLICATION PROCEDURE: Interested individuals should email a curriculum vitae, up to three representative publications, names / phones / emails of three to five references and a cover note describing research interests, professional goals and availability. Please submit materials to: Cordelia Nwaekwe, Assistant to Professor Moody Email: moodylab at icsi.berkeley.edu URL: www.icsi.berkeley.edu/~moody/ Applications submitted on or before August 31, 2004 will receive priority consideration. We will continue considering candidates until the position is filled. Applicants should be available to begin a one year position between September 1, 2004 and January 1, 2005. Extension to a second year and beyond will depend upon performance in year one and procurement of additional funding. ICSI is an equal opportunity employer; minorities and women are encouraged to apply. From zoubin+cs at gatsby.ucl.ac.uk Tue Aug 3 13:44:33 2004 From: zoubin+cs at gatsby.ucl.ac.uk (zoubin+cs@gatsby.ucl.ac.uk) Date: Tue, 3 Aug 2004 18:44:33 +0100 Subject: Three Faculty Positions in CS at University College London Message-ID: <16655.52993.992548.62606@wald.gatsby.ucl.ac.uk> UNIVERSITY COLLEGE LONDON Department of Computer Science Three Lecturer / Senior Lecturer Posts (UK Lecturer is roughly equivalent to US Assistant Professor) We are seeking talented researchers whose interests are aligned with our existing departmental strengths. One such focus is in the application and theory of Machine Learning and Artificial Intelligence. A candidate with these strengths will be expected to play a leading role in the research and teaching of ML/AI in the Department, and especially in the development of our MSc programme in Intelligent Systems (see http://www.cs.ucl.ac.uk/pg/is/). A successful candidate will have the opportunity to interact with members of the Gatsby Unit at UCL (see http://www.gatsby.ucl.ac.uk) and may possible hold an honorary appointment there. The strengths of the Gatsby Unit lie in Machine Learning and Theoretical Neuroscience. You can find out more about us at http://www.cs.ucl.ac.uk . Further details of the posts and the application procedure can be found at http://www.cs.ucl.ac.uk/vacancies . The closing date for applications is Thursday, 30 September 2004. From paulv at ling.ed.ac.uk Fri Aug 6 07:10:01 2004 From: paulv at ling.ed.ac.uk (Paul Vogt) Date: Fri, 06 Aug 2004 12:10:01 +0100 Subject: CFP: Adaptive Behavior: Special Issue on Language Acquisition and Evolution Message-ID: <41136709.50707@ling.ed.ac.uk> Call for Papers: Language Acquisition and Evolution Special Issue: Adaptive Behavior Guest editor: Paul Vogt Submission deadline: 15 November 2004 URL: http://www.ling.ed.ac.uk/~paulv/ab-cfp.html It is widely believed that language has evolved through mutual interactive behaviour of individuals within an ecological niche, through individual adaptations and self-organisation. Humans communicate with each other about events that happen in their environment. When novel events occur, they might construct new internal representations of these events - either by learning from other's behaviour or by inventing new behaviour. They can then transmit this newly constructed knowledge to other humans. By subsequent local interactions between individuals, self-organisation can guide the emergence of a global structure called language as has repeatedly been shown by several computer models. Many computational studies on the evolution of language have primarily focused on the idea that language is a complex dynamical adaptive system, as outlined above. Central to these studies is the cultural evolution of language, i.e. language is thought to have evolved based on cultural transmissions rather than on biological adaptations. Cultural transmission of language is impossible without the ability to learn language. This special issue is inspired by a recent Symposium on Language Evolution and Acquisition held at the 2004 Human Behavior & Evolution Society conference, and focuses on the relation between language origins, acquisition and evolution. Two main themes to be explored are how could language acquisition mechanisms have evolved, and the impact that particular acquisition skills may have had on the evolution of language itself. /Adaptive Behavior/ solicits papers that present synthetic studies that explicitly focuses on the interface between language origins and/or evolution, and language acquisition. The models should involve either computer simulations or robotic platforms. However, those papers that integrate models with psychological, linguistic or biological data are particularly welcome. Papers in this special issue should not exceed the equivalent length of 10 journal pages. See the web-site of the Adaptive Behavior (http://www.isab.org.uk/journal/) for further instructions. Topics include (though not restricted): * Evolution of o language acquisition skills. o joint attention. o corrective feedback. * Phonetics. * Lexicon formation. * Meaning inference. * Symbol grounding in language. * Emergence of syntax or grammar. * Language change. * Language diversity. If you intend to submit a paper, please send a tentative title and abstract to the guest editor (Paul Vogt, paulv at ling.ed.ac.uk). (This would help to speed up the selection of reviewers.) If you are uncertain whether your paper would satisfy the topic of this special issue, or if you wish further information, please contact the guest editor too. Important dates: * *15 November 2004: Submission deadline.* * 15 February 2005: Notification of acceptance. * 15 April 2005: Revised versions due. * 30 May 2005: Authors notified (for revised papers). * Late 2005: Special issue appears. -- Dr. Paul Vogt, Research Fellow Language Evolution and Computation Research Unit School of Philosophy, Psychology and Language Sciences University of Edinburgh Phone: +44 (0)131 6503960 Fax: +44 (0)131 6503962 URL: http://www.ling.ed.ac.uk/~paulv From ahu at cs.stir.ac.uk Fri Aug 6 11:03:19 2004 From: ahu at cs.stir.ac.uk (Dr. Amir Hussain) Date: Fri, 6 Aug 2004 16:03:19 +0100 Subject: Final Call for Participation: BICS'2004, Stirling, Scotland, UK Message-ID: <003401c47bc6$89c77db0$c16d6e42@DrAmir> Brain Inspired Cognitive Systems (BICS-2004): Final Call for Participation University of Stirling, Scotland, UK August 29 - September 1, 2004 Share the latest research, developments and ideas in the wide arena of disciplines encompassed under the heading of BICS-2004, including: First International ICSC Symposium on Cognitive Neuro Science (CNS) Chair: Prof. Igor Aleksander, Imperial College London, U.K Second International ICSC Symposium on Biologically Inspired Systems (BIS) Chair: Prof. Leslie Smith, University of Stirling, U.K. Third International ICSC Symposium on Neural Computation (NC) Chair: Dr. Amir Hussain, University of Stirling, U.K. Conference Sponsors: The Institution of Electrical Engineers (IEE) University of Stirling, Scotland, UK Imperial College London, UK ICSC Interdisciplinary Research, Canada Workshop: Information coding in early sensory stages Plenary Debate : Machine Consciousness: Does it Make Sense? Tutorial : Models of Consciousness: The world scene Prof I Aleksander, Imperial College London Tutorial: Implementing neural models in silicon Prof L S Smith, University of Stirling, Scotland Tutorial: Neural Networks for Adaptive Speech Enhancement Dr A. Hussain, University of Stirling, Scotland Plenary Lecture : Fifteen years of Neuromorphic Engineering: progress, problems, and prospects; Prof R. Douglas, ETH Zurich, Switzerland Plenary Lecture: Self-Organisation in the Nervous System: the Establishment of Nerve Connections by an Inductive Mechanism; Prof David Willshaw, University of Edinburgh, Scotland Plenary Lecture: Computation, cognition, and control Dr. O Holland, University of Essex, U.K. Plenary Lecture: Neural Nets: the hype and the reality, from an industrial perspective Prof G Hesketh, Rolls-Royce, UK Plenary Lecture: Disentangling signals blindly from nonlinear mixtures Prof E Oja, Helsinki University of Technology, Finland Plenary Lecture: Attention and Consciousness as Control System Components in the Brain Prof John G Taylor, King's College, U.K and contributed papers on: Audition and Robotics (BIS) Neural Modelling (BIS) Neuromorphic Approaches (BIS) Neuromorphic and spiking networks: BSS (BIS) Novel approaches (BIS) Vision (BIS) Computational Neural Network Models (NC) Neural Network Applications (NC) Software and Hardware Implementations (NC) Neurological Analysis (CNS) Representation and Modelling (CNS) Attention and Emotion (CNS) Agent Consciousness (CNS) Venue: beautiful campus University of Stirling, Scotland, with an excellent centre to visit Scotland from. BICS2004 is being held in Stirling, a historic city located in the heart of Scotland. The conference venue and accommodation are all on the University campus, which is convenient for visiting the ancient castle and Wallace monument, or for going further a field and exploring the beautiful countryside. For the full programme: HYPERLINK "http://www.icsc-naiso.org/conferences/bics2004/bics-cfp.html"http://www icsc-naiso.org/conferences/bics2004/bics-cfp.html Registration on page: HYPERLINK "http://www.cs.stir.ac.uk/~lss/BICS2004/registration1.html"http://www.cs stir.ac.uk/~lss/BICS2004/registration1.html NOTE: Authors of selected papers will be invited to submit an extended version of their paper for publication in a special issue of the Neurocomputing Journal, published by Elsevier Science B.V. (HYPERLINK "http://www.elsevier.nl/locate/neucom"http://www.elsevier.nl/locate/neuc om) - Dr. Amir Hussain Senior Lecturer in Computing Science University of Stirling Stirling FK9 4LA, UK Email: HYPERLINK "mailto:ahu at cs.stir.ac.uk"ahu at cs.stir.ac.uk HYPERLINK "http://www.cs.stir.ac.uk/~ahu"http://www.cs.stir.ac.uk/~ahu Tel/Fax: (+44) 01786 - 467437 / 464551 -- The University of Stirling is a university established in Scotland by charter at Stirling, FK9 4LA. Privileged/Confidential Information may be contained in this message. If you are not the addressee indicated in this message (or responsible for delivery of the message to such person), you may not disclose, copy or deliver this message to anyone and any action taken or omitted to be taken in reliance on it, is prohibited and may be unlawful. In such case, you should destroy this message and kindly notify the sender by reply email. Please advise immediately if you or your employer do not consent to Internet email for messages of this kind. Opinions, conclusions and other information in this message that do not relate to the official business of the University of Stirling shall be understood as neither given nor endorsed by it. From gasser at cs.indiana.edu Mon Aug 9 13:01:31 2004 From: gasser at cs.indiana.edu (Michael Gasser) Date: Mon, 9 Aug 2004 12:01:31 -0500 (EST) Subject: Computational linguistics faculty position: Indiana University Message-ID: (This position is for a "computational linguist" very broadly construed. Connectionist researchers are encouraged to apply. They would find plenty of like-minded colleagues and students at Indiana. --Mike Gasser) -------------------------------------------------------------------- Indiana University, Bloomington, Indiana. Faculty position beginning Fall, 2005 As one of a series of new appointments, the Cognitive Science Program at Indiana University seeks applicants with a developing strong record of research in computational linguistics, broadly defined. We are looking for someone with vision, energy, and a desire to explore new forms of interdisciplinary study. Areas of specialty could include, but are not limited to: computational, statistical, psychological, experimental, and developmental approaches. The right candidate is more important than the specific disciplinary background. Although we anticipate appointment at the junior rank, more senior appointments are also possible for exceptional applicants. Applicants should send full dossiers, including letters of recommendation and sample of papers. Indiana University is an equal opportunity/affirmative action employer. Applications from women and minority group members are especially encouraged. Please send materials to Professor Richard Shiffrin, Computational Linguistics Search Committee, Cognitive Science Program, 1033 E. Third St., Sycamore 0014, Bloomington, IN 47405. Applications received by December 1, 2004 are assured full consideration. Please see our website: http://www.cogs.indiana.edu for information regarding additional open faculty positions. If you have questions about this position, you may contact Michael Gasser at gasser at indiana.edu. From maass at igi.tugraz.at Mon Aug 9 17:09:50 2004 From: maass at igi.tugraz.at (Wolfgang Maass) Date: Mon, 09 Aug 2004 23:09:50 +0200 Subject: Phd /Postdoc position in biological vision Message-ID: <4117E81E.4050802@igi.tugraz.at> A position for a Phd-student or Postdoc is available in our research project COMPUTER MODELS FOR BIOLOGICAL VISION SYSTEMS This is a subproject within a larger research project on COGNITIVE VISION, see http://www.acin.tuwien.ac.at/groups/robtec/fsp/fsp.htm Research for this subproject is carried out by our Institute in collaboration with the Department for the Physiology of Cognitive Processes (Director Nikos Logothetis) at the MPI for Biological Cybernetics in T=FCbingen, see http://www.kyb.tuebingen.mpg.de/lo/. The research in this subproject will focus on the design of theoretical models as well as computer models on several spatial scales, with biologically realistic anatomy and dynamics. These models will serve as testbed for the exploration of learning algorithms that may endow such models with partial visual function for movement analysis and object recognition. In addition these models will serve as links to experimental neuroscientists at the MPI T=FCbingen for the design of new experiments and the integration of new experimental data on movement analysis and object recogntion in primates.. These models will also serve as link to researchers from computer vision in the larger COGNITIVE VISION project, where we will compare empirically successful approaches for generic object recognition in computer vision and associated learning algorithms with biological data and models. We are looking for a highly qualified and strongly motivated student/postdoc with experience in areas such as computer vision, machine learning, computer simulations, computational neuroscience, programming. Courses and seminars for Phd-students are carried out in English, leading to a Phd in Computer Science at the Graz University of Technology. Applications should be sent by August 16 to Wolfgang Maass maass at igi.tugraz.at -- Prof. Wolfgang Maass Institut fuer Grundlagen der Informationsverarbeitung Technische Universitaet Graz Inffeldgasse 16b , A-8010 Graz, Austria Tel.: ++43/316/873-5811 Fax ++43/316/873-5805 http://www.igi.tugraz.at/maass/Welcome.html From mcgl-ci0 at wpmail.paisley.ac.uk Tue Aug 10 05:19:44 2004 From: mcgl-ci0 at wpmail.paisley.ac.uk (Stephen McGlinchey) Date: Tue, 10 Aug 2004 10:19:44 +0100 Subject: CGAIDE Special Session on Neural Networks - Submission deadline extended till 31 August 2004 Message-ID: Due to popular demand, we have extended the deadlines for paper submission and acceptance notification for the CGAIDE 2004 International Conference on Computer Games: Artificial Intelligence, Design and Education. This conference includes a special session on neural networks. Papers should now be submited by 31st August 2004. C A L L F O R P A P E R S Special Session On NEURAL NETWORKS IN COMPUTER GAMES AND SIMULATION as part of International Conference on Computer Games: Artificial Intelligence, Design and Education (CGAIDE) 8-10 November 2004 Hosted at the Microsoft Campus, Reading, UK http://www.scit.wlv.ac.uk/~cm1822/cgaide.htm The main objectives of this special session are: * To provide a forum for presenting and discussing the application of neural networks in computer games and simulations * To promote collaboration between the computer games and computational intelligence research communities. Neural Networks (NN) in in Computer Games and Simulations =========================================================== We invite submission of papers presenting recent research on Artificial Neural Networks applied to any aspect of computer games technology or simulation. The scope of the session may include topics from the following non-exclusive list. Autonomous control of game agents. Processing of game content data. Real-time feature extraction from game data. Simulation or anaylisis of emotions / intelligence. Automatic analysis of human player behaviours. Synthesis of dynamic game content. Strategic game applications (e.g. Go and Chess) Optimising search spaces. Submissions are encouraged from any other related application of neural networks in games or simulation. Full papers should be sent to stephen.mcglinchey at paisley.ac.uk by the submission deadline. Send a full paper - not previously published - in Word format (no smaller than 10-point format) to include author, address, e-mail, keywords and abstract (200 words max) in one of the following categories: Regular paper max. 5 pages Extended Paper max. 8 pages Critical Review paper max. 10 pages Important dates: Draft paper submission : 31 August 2004 Notification of acceptance : 20 September 2004 Camera-ready submission deadline : 4 October 2004 Please send enquiries to: Stephen McGlinchey (stephen.mcglinchey at paisley.ac.uk) School of Computing University of Paisley Paisley, Scotland or Darryl Charles (dk.charles at ulster.ac.uk) School of Computing and Information Engineering University of Ulster Coleraine, Northern Ireland. From dirk at bioss.sari.ac.uk Wed Aug 11 14:31:57 2004 From: dirk at bioss.sari.ac.uk (Dirk Husmeier) Date: Wed, 11 Aug 2004 19:31:57 +0100 Subject: PhD and postdoc positions in computational systems biology Message-ID: <411A661D.602B25A3@bioss.ac.uk> I would be grateful if you could bring the following webpage to the attention of suitable candidates: http://www.bioss.sari.ac.uk/~dirk/jobs/jobAdvert.pdf This is a job advert for 6 research positions in systems biology to investigate regulatory and signalling networks controlling bacterial disease development. Positions 5 (postdoctoral researcher in genetic network analysis) and 6 (PhD student in structural genomics) are ideally suited for candidates with a strong mathematical and computational background, who are interested in applying machine learning methods to computational molecular biology. Many thanks and best regards Dirk -- Dirk Husmeier Biomathematics & Statistics Scotland (BioSS) JCMB, The King's Buildings, Edinburgh EH9 3JZ, United Kingdom http://www.bioss.sari.ac.uk/~dirk From j.odoherty at fil.ion.ucl.ac.uk Thu Aug 12 08:49:44 2004 From: j.odoherty at fil.ion.ucl.ac.uk (John O'Doherty) Date: Thu, 12 Aug 2004 13:49:44 +0100 Subject: Post-doctoral position in fMRI of reward and decision making Message-ID: <200408121349.44654.j.odoherty@fil.ion.ucl.ac.uk> Post-doctoral position in fMRI of reward and decision making A post-doctoral position is available to investigate the neural mechanisms of reward-learning, choice and decision making in the human brain. The post will involve the application of computational models to fMRI data, as well as the design and conduct of fMRI experiments. This position would ideally suit a candidate with a background in computational neuroscience who is interested in gaining experience of brain imaging. The project will be carried out using fMRI facilities at the Broad Center for the Biological Sciences at Caltech. Please send a curriculum vitae and brief cover letter to John O'Doherty, j.odoherty at fil.ion.ucl.ac.uk. The position is for two years with a start date from January 2005. The California Institute of Technology is an Equal Opportunity/Affirmative Action Employer and encourages the applications of qualified women, minorities, veterans and disabled persons. -- -------------- Dr John O'Doherty Wellcome Department of Imaging Neuroscience Institute of Neurology University College London London WC1N 3BG Tel: +44 207 8337479 Fax: +44 207 8131420 e-mail: j.odoherty at fil.ion.ucl.ac.uk web: http://www.fil.ion.ucl.ac.uk/~jdoherty From terry at salk.edu Fri Aug 13 13:37:20 2004 From: terry at salk.edu (Terry Sejnowski) Date: Fri, 13 Aug 2004 10:37:20 -0700 (PDT) Subject: NEURAL COMPUTATION 16:9 In-Reply-To: <200406261632.i5QGWPO06371@dax.salk.edu> Message-ID: <200408131737.i7DHbKn81419@kepler.snl.salk.edu> Neural Computation - Contents - Volume 16, Number 9 - September 1, 2004 NOTES A Note on the Applied Use of MDL Approximations Daniel J. Navarro Optimal Reduced-Set Vectors for Support Vector Machines with a Quadratic Kernel Thorsten Thies and Frank Weber LETTERS Stochastic Reasoning, Free Energy, and Information Geometry Shiro Ikeda, Toshiyuki Tanaka, and Shun-ichi Amari Blind Separation of Positive Sources by Globally Convergent Gradient Search Erkki Oja and Mark Plumbley A New Concept for Separability Problems in Blind Source Separation Fabian J. Theis Modeling Mental Navigation in Scenes with Multiple Objects Patrick Byrne and Suzanna Becker Failure of Motor Learning for Large Initial Errors Terence D. Sanger Fair Attribution of Functional Contribution in Artificial and Biological Networks Alon Keinan, Ben Sandbank, Claus, C. Hilgetag, Isaac Meilijson, and Eytan Ruppin Recurrent Network with Large Representational Capacity Drazen Domijan A Solution for Two-Dimensional Mazes with Use of Chaotic Dynamics in a Recurrent Neural Network Model Yoshikazu Suemitsu and Shigetoshi Nara Online Adaptive Decision Trees (OADT) Jayanta Basak ----- ON-LINE - http://neco.mitpress.org/ SUBSCRIPTIONS - 2004 - VOLUME 16 - 12 ISSUES Electronic only USA Canada* Others USA Canada* Student/Retired $60 $64.20 $108 $54 $57.78 Individual $95 $101.65 $143 $85 $90.95 Institution $635 $679.45 $689 $572 $612.04 * includes 7% GST MIT Press Journals, 5 Cambridge Center, Cambridge, MA 02142-9902. Tel: (617) 253-2889 FAX: (617) 577-1545 journals-orders at mit.edu ----- From jyoshimi at ucsd.edu Tue Aug 17 02:55:30 2004 From: jyoshimi at ucsd.edu (Jeff Yoshimi) Date: Mon, 16 Aug 2004 23:55:30 -0700 Subject: Simbrain 1.0.5 Released Message-ID: <6DC3630C-F01A-11D8-8A30-000393A6E67A@ucsd.edu> A new version of Simbrain (http://simbrain.sourceforge.net/) has been released. This is an interim release, to make recent changes available prior to beginning work on the next iteration, which will involve a major redesign and integration with Snarli (http://snarli.sourceforge.net/) Primary areas of improvement in 1.0.5 are as follows: (1) complete rewrite of the world component, which now allows worlds to be edited in the GUI and includes more sophisticated objects, (2) complete rewrite of the gauges, which have been separately released as the program "HiSee" (http://hisee.sourceforge.net/), (3) updates to the network interface, right-click popup menus in particular, (4) a documentation rewrite. Other improvements include: recurrent connections show in the GUI, improved control over input and output nodes, ability to round off activation values and set precision, new simulations and organization to simulation directory, new documentation viewer, and numerous bug fixes. Your comments and suggestions would be appreciated as we enter the next phase of development. As always, we are seeking developers and help. - Jeff From samengo at cab.cnea.gov.ar Tue Aug 17 08:19:37 2004 From: samengo at cab.cnea.gov.ar (Ines Samengo) Date: Tue, 17 Aug 2004 09:19:37 -0300 Subject: Paper on a subjective distance in the space of stimuli. Message-ID: <4121F7D9.CF0BB1C@cab.cnea.gov.ar> Dear connectionists, the following preprint, to appear in Neural Computation, may be of interest to some of you. Best regards, Ines Samengo. ---------------------------------------------------------------- A subjective distance between stimuli: quantifying the metric structure of representations D. Oliva, I. Samengo, S. Leutgeb, S. Mizumori As subjects perceive the sensory world, different stimuli elicit a number of neural representations. Here, a subjective distance between stimuli is defined, measuring the degree of similarity between the underlying representations. As an example, the subjective distance between different locations in space is calculated from the activity of rodent hippocampal place cells, and lateral septal cells. Such a distance is compared to the real distance, between locations. As the number of sampled neurons increases, the subjective distance shows a tendency to resemble the metrics of real space. http://arXiv.org/abs/q-bio/0408008 -- ______________________________________________________ Ines Samengo samengo at cab.cnea.gov.ar http://www.cab.cnea.gov.ar/users/samengo/samengo.html tel: +54 2944 445100 - fax: +54 2944 445299 Centro Atomico Bariloche (8.400) San Carlos de Bariloche Rio Negro, Argentina ______________________________________________________ From Kari.Torkkola at motorola.com Wed Aug 18 13:20:28 2004 From: Kari.Torkkola at motorola.com (Kari Torkkola) Date: Wed, 18 Aug 2004 10:20:28 -0700 Subject: JOB: Machine learning at Motorola, Phoenix, AZ Message-ID: <41238FDC.2070000@motorola.com> Motorola has an open position in machine learning in metro Phoenix area: Department Description Motorola Labs - Intelligent Systems Research Lab, Phoenix, AZ At Motorola's Intelligent Systems Research Lab we research machine intelligence and contextual understanding to design the next generation mobile and personal devices such as driver assistance systems and intelligent cell phones. We research user needs in these environments and conduct the front-end development to provide the intelligent systems solutions that are implemented across a range of products. Scope of Responsibilities/Expectations This position will be focused on applying an understanding of machine intelligence to the development of software-based intelligent systems for deployment in next-generation automotive, personal, and home devices. The Machine Intelligence Researcher will have the following responsibilities: - Develop and implement techniques that infer the user's state, activity and intention from analysis of device and environment-based sensors, personal data and models of user behavior. - Develop algorithms for user modeling, pattern recognition, and static and sequential sensor data processing. These algorithms might include Support Vector Machines, Bayes Nets, Hidden Markov Models, or Particle Filters, for example. - Proactively identify opportunities for technology development, develop technical proposals and research plans and carry out research. - Work closely with other machine intelligence and human interaction researchers and product sector design engineers. - Keep up with the state of the art in machine learning by following the latest journals and conferences and the Internet. - Publish and present results to peers, developers, management and customers. Specific Knowledge/Skills - PhD in computer science, signal processing, mathematics, statistics, or relevant discipline with 2 years of experience or M.S. with 5 years of experience. - Strong record of research and innovation in the area of pattern recognition and machine learning. - Significant experience in software development, such as Matlab for algorithm development and Java or C/C++ for implementation. - Experience with large real world data sets is desirable. - Experience in mobile device ad-hoc networking technologies and applications of pervasive personal computing would be an advantage. - Good organizational and communication skills, both written and oral. - Ability to interact well with a multi-disciplinary technology team in the creation of new designs and approaches. - Able to work well across a decentralized geographically dispersed organization. - Flexibility in scope of job responsibilities. - Willingness to do light travel. Please submit your resume through http://www.motorolacareers.com Refer to job id 13570. Alternatively, email the resume to | Greg.Kozlowski | at | motorola | dot | com Informal questions can be sent to | Kari.Torkkola | at | motorola | dot | com From claus.neubauer at siemens.com Mon Aug 16 14:24:21 2004 From: claus.neubauer at siemens.com (Neubauer, Claus) Date: Mon, 16 Aug 2004 14:24:21 -0400 Subject: Siemens Corporate Research: position in neural network modeling and machine learning Message-ID: <20B20848358CDA44AB6A2E277D2E1C5E0282AC1B@postoffice.scr.siemens.com> Siemens Corporate Research Inc., Princeton, NJ has an opening for a Research Scientist. In this position, the candidate will be conducting leading-edge research and development related to neural network modeling and machine learning for various medical and industrial applications. Ideal candidates will have a Ph.D. in CS or related fields with a proven record in research, innovative thinking, real world problem solving and fast prototyping. Candidates should have C/C++ or Java proficiency on MS Windows platform. Experience in applying neural network and machine learning techniques in a field such as machine diagnosis, monitoring, predictive maintenance, data mining, decision support, biomedical informatics or computer vision will be a big plus. Candidates need to have strong interpersonal skills, be able to work independently on problems, be an effective team player and be willing to accept challenge and responsibility. We offer a competitive salary and benefits package that reflects our leadership status. For consideration, please email your CV or resume to: _____________________ Claus Neubauer, Ph.D. Program Manager Intelligent Data Analysis & Modeling Siemens Corporate Research 755 College Road East Princeton, NJ 08540, USA Email claus.neubauer at siemens.com For more information, please visit: http://www.scr.siemens.com From amir at ymer.org Tue Aug 31 08:30:21 2004 From: amir at ymer.org (Amir Reza Saffari Azar) Date: Tue, 31 Aug 2004 05:30:21 -0700 Subject: Biological Neural Network Toolbox for MATLAB: Ver 1.0 Message-ID: <20040831123022.30752.qmail@webmail-2-5.mesa1.secureserver.net> I'm pleased to announce the first release of Biological Neural Network (BNN) Toolbox for MATLAB. This package is a free open source software for simulating models of brain and central nervous system, based on MATLAB computational platform. As the name of the toolbox implies, the main goal of this package is to provide users a set of integrated tools to create models of biological neural networks and simulate them easily, without the need of extensive coding. Users can create and simulate a huge network of spiking neurons in less than 10 lines of code (or even in one line, if they give all arguments to the main function) using predefined library functions. It is also possible to create and add new models to the library easily, using template library items. Current Features: 1) Users can create and simulate any kind of BNN with this toolbox. 2) Architectures: Custom, Fully Connected, Multilayer Feedforward, Multilayer Feedforward with General, Lateral, and Local Feedbacks. 3) Spiking Neuron Models: Custom, Linear and Quadratic Integrate-and-Fire, Hodgkin-Huxley, FitzHugh-Nagumo, Morris-Lecar, Canonical Phase, and Izhikevich. 4) PSP Models: Custom, Two Versions of Alpha-Function, and Dirac Delta Function. 5) Event based computation. 6) Users can select several MATLAB ODE solvers for their model. 7) Custom adaptation models. 8) Static and dynamic external inputs. 9) Custom user and stop functions. 10) Examples and Library templates. Next versions will have an additional user friendly GUI package, will have more library models, and will be more faster than this version. The author would be very grateful for any comments, reviews, discussions, bug reports, and wishes from users and believes that these feedbacks would make this toolbox alive and evolving. If you have any kind of model related to the neuroscience topics, including but not limited to network architectures, neuron models, synapse models, adaptation mechanisms, and if you want the future releases contain these models, feel free to contact with the author. This toolbox is created and developed by personal interests of the author in modeling brain and CNS and is provided to other users as an open source free software under GNU GPL. Feel free to copy, modify, and distribute it according to the license. To obtain the latest version of GPL, please refer to http://www.gnu.org. Links: Email: amir at ymer.org Website: http://www.ymer.org Alt. Website: http://ee.sut.ac.ir/faculty/saffari/res-bnntoolbox.htm ------------------------------- "Before the beginning of great brilliance, there must be chaos" Amir Reza Saffari Azar Alamdari Email: amir at ymer.org Web: http://ymer.org From meeden at cs.swarthmore.edu Tue Aug 31 12:26:04 2004 From: meeden at cs.swarthmore.edu (Lisa Meeden) Date: Tue, 31 Aug 2004 12:26:04 -0400 (EDT) Subject: CFP AAAI Spring Symposium: Developmental Robotics Message-ID: CALL FOR PAPERS AAAI Spring Symposium: Developmental Robotics March 21-23, 2005 at Stanford University Submission deadline October 8, 2004 For details see http://cs.brynmawr.edu/DevRob05/ Developmental robotics is a new approach that focuses on the autonomous self-organization of general-purpose control systems. Developmental robotics is a move away from task-specific methodologies where a robot is designed to solve a particular pre-defined problem. This new approach explores the kinds of perceptual, cognitive, and behavioral capabilities that a robot can discover through self-motivated actions based on its own physical morphology and the dynamic structure of its environment. Initially a developmental system might bootstrap itself with some innate knowledge or behavior, but with experience could create more complex representations and actions, leading to complete Autonomous Mental Development (AMD)[1]. Developmental robotics is different from many learning and evolutionary systems in that the reinforcement signal, teacher target, or fitness function comes from within the system. In this manner, these systems are designed to rely more on mechanisms such as self-motivation, homeostasis, or emotions. We invite contributions on architectures for developmental robotics, examples of developmental behavior in robots, as well as features or mechanisms of developmental processing including, but not limited to: self-organization, self-exploration, self-motivation, categorization, artificial emotional systems, value systems, and anticipation-driven learning. [1] Weng, J., McClelland, J., Pentland, A., Sporns, O., Stockman, I., Sur M., and Thelen, E. (2000). Autonomous Mental Development by Robots and Animals, Science, vol. 291, no. 5504, pp. 599 - 600. Available at http://www.cse.msu.edu/dl/SciencePaper.pdf --- Lisa Meeden Computer Science Dept. Associate Professor Swarthmore College meeden at cs.swarthmore.edu 500 College Ave. http://www.cs.swarthmore.edu/~meeden Swarthmore, PA 19081 610-328-8565 (voice) 610-328-8606 (fax) From intneuro at sbcglobal.net Tue Aug 31 11:17:50 2004 From: intneuro at sbcglobal.net (INTEGRATIVE NEUROSCIENCE) Date: Tue, 31 Aug 2004 08:17:50 -0700 (PDT) Subject: call for papers: JIN special issue honoring Paul Bach-y-Rita, Wisconsin University Medical School Message-ID: <20040831151750.77104.qmail@web81103.mail.yahoo.com> Journal of Integrative Neuroscience (JIN) An Interdisciplinary Journal CALL FOR PAPERS: Non-synaptic Communication in Brains and Integrative functions : a special issue honoring Paul Bach-y-Rita, Wisconsin University Medical School and Biomedical Engineering To appear in: VOLUME 4, ISSUE 4 DECEMBER 2005 The synaptic model of neurocommunication in the brain has dominated the neurosciences for more than a century. Generally, little consideration is given to other modes of neurotransmission in animal and human brains, even though there is indirect evidence that less than half of the communication between cells is by synapses. Non-synaptic diffusion neurotransmission may be the primary information transmission mechanism in certain normal and abnormal functions. Non-synaptic diffusion is vastly more economical than synaptic transmission in regards to space and energy expenditure in the brain, and may play a role in the evolution of species and in a proposed Law of Conservation of Energy and Space in the Brain. In view of the non-synaptic nature of much of the brain's information management, mechanistic concepts, such as comparisons of the brain to a digital computer become less tenable than is conventionally believed. The human brain is much more technically sophisticated than any present or even presently foreseeable electronic device. Even the nervous systems of insects defy simulation on the most advanced computers. "We see with our brains not eyes" .............Paul Bach-y-Rita Paul Bach-y-Rita, M.D. is a professor of rehabilitation medicine and of biomedical engineering at the University of Wisconsin. He is also chief scientist and chairman of the Board of WICAB. His discoveries have enabled the blind to see, the victims of leprosy to feel, and the quadriplegic to enjoy sex. He has researched and published extensively in human-machine interfaces, related neuroscience and Rehabilitation Engineering, brain plasticity, brain neurotransmission, development of instrumentation for home rehabilitation, development of late rehabilitation of brain damaged and of persons with facial paralysis, and functional assessment by computer image analysis. The books that he has written, edited, or co-authored include Nonsynaptic Diffusion Neurotransmission and Late Brain Reorganization, Vitamins: Their Use and Abuse, Brain Mechanisms in Sensory Substitution, Recovery of Function: Theoretical Considerations for Brain Injury Rehabilitation, Traumatic Brain Injury (Comprehensive Neurologic Rehabilitation, Vol 2). He was founding director (starting in 1975) of the San Francisco Rehabilitation Engineering Center. He is the co-inventor of the tongue human-machine interface. Authors should be aware of the following tentative key dates: Proposals to Special Edition Editor (Steve Kercel) due no later than January 20, 2005. (Early submittals are encouraged. Preferred submission channel is e-mail, kercel1 at suscom-maine.net). A proposal consists of an abstract of approximately one page, an estimate of the the expected length of the proposed paper, a list of co-authors (if any), and brief (one page of highlights, with emphasis on connection to Dr. Bach-y-Rita) CV of principal author. The Special Edition Editor expects to issue accept/reject notifications of specific proposals within one month of the date that he receives the proposal. Early submissions will receive a correspondingly early decision. Full manuscript (including illustrations and references) due April 30, 2005. Referee comments will be sent to the authors as soon as practicable. Revised manuscript, accounting for referee and editorial comments due July 31, 2005. The finished edited camera ready copy due September 30, 2005. Dr. Stephen W. Kercel 2 Brian Drive Brunswick ME 04011 USA Phone: (207) 729-4504 FAX: (207) 729-6226 E-mail: kercel1 at suscom-maine.net From cgunay at emory.edu Sun Aug 29 23:32:24 2004 From: cgunay at emory.edu (Cengiz Gunay) Date: Sun, 29 Aug 2004 23:32:24 -0400 (EDT) Subject: Ph.D. dissertation: Hierarchical learning of conjunctive concepts in spiking neural nets In-Reply-To: References: Message-ID: Dear connectionists, My Ph.D. dissertation titled "Hierarchical learning of conjunctive concepts in spiking neural networks", together with related publications, is available from the web page: http://www.cacs.louisiana.edu/~cxg9789/Neuroidal Below you can find the abstract for the dissertation. Abstract -------- The temporal correlation hypothesis proposes that synchronous activity in different regions of the brain describes integral entities (von der Malsburg, 1981; Singer and Gray, 1995). This temporal binding approach is a possible solution to the longstanding binding problem of representing composite objects (Rosenblatt, 1961). To complement the dynamic nature of temporal binding, a recruitment learning method has been proposed for providing long-term storage (Feldman, 1982; Valiant, 1994). We improve the recruitment method to use a more biologically realistic and computationally powerful spiking neuron model. However, using continuous-time spiking neurons and brain-like connectivity assumptions poses new problems in hierarchical recruitment. First, we propose timing parameter constraints for recruitment over asymmetrically connected delay lines. We verify these constraints using simulations. These constraints are useful for both building abstract networks and providing insight into bio-mechanisms that ensure signal integrity in the brain. As a second problem, we calculate the required feedforward excitatory and lateral inhibitory connection densities for stable propagation of activity in hierarchical structures of the network. We give analytic solutions using a stochastic population model of a simplified layered network. Our approach is independent of the network size, but depends on lateral inhibition and noisy feedforward delays. --- Thanks, Cengiz Gunay Postdoctoral Fellow, Dept. of Biology Emory University, Atlanta, GA, USA. -- cgunay at emory.edu cengique at users.sf.net cengique at yahoo.com Lab: +1-404-727-4103 Home/Cell: +1-337-255-3660 http://www.cacs.louisiana.edu/~cxg9789 ICQ# 21104923, cengique at jabber.org -- From moodylab at ICSI.Berkeley.EDU Mon Aug 2 23:06:18 2004 From: moodylab at ICSI.Berkeley.EDU (Moody Lab) Date: Mon, 2 Aug 2004 20:06:18 -0700 (PDT) Subject: Postdoc -- Reinforcement Learning & Finance Message-ID: INTERNATIONAL COMPUTER SCIENCE INSTITUTE Berkeley & Portland Post-Doc / Research Scientist in Machine Learning & Computational Finance Preferred Start Dates: September - December 2004 DESCRIPTION: The International Computer Science Institute (ICSI) invites applications for a one to two year Post-Doctoral Fellow or Research Scientist position that is part of a project directed by Prof. John Moody and funded by the National Science Foundation entitled "Risk, Reward and Reinforcement". This interdisciplinary investigation is exploring powerful, new algorithms for Direct Reinforcement and the application of these algorithms to games, multi-agent systems and important, real-world financial problems. Activities include fundamental algorithms research, extensive simulation and empirical testing. Substantial financial market data resources under development at ICSI are available for application prototype development. The goals are to create highly effective and efficient algorithms for Direct Reinforcement that can discover robust solutions to challenging, dynamic, real-world problems. ICSI is an independent, nonprofit research institute with headquarters in Berkeley, California. It is closely affiliated with the University of California at Berkeley. ICSI is funded by the U.S. and several European governments, and brings together top researchers from participating countries. This ICSI project will be based in Portland, Oregon, which offers exceptional quality of life and was recently named America's "Best Big City". See http://www.moneymag.com/best/bplive/portland.html . The successful candidate will have opportunities to interact with researchers at ICSI, UC Berkeley, and other leading Northwest and West Coast universities. QUALIFICATIONS: Candidates must have a Ph.D. or comparable research experience in computer science, an engineering, physical or mathematical science or a quantitative social science such as economics or finance. Strong mathematical, statistical and computational skills are required. Ideally, applicants should have expertise in two or more of the following topics: machine learning (especially reinforcement learning), Monte Carlo methods, nonparametric statistics, time series analysis, optimization, control engineering or quantitative finance. Preference will be given to candidates who are about to complete or have completed a Ph.D. within the past three years. Exceptionally well-qualified non- Ph.D. candidates with three to five years of relevant professional experience may also be considered. APPLICATION PROCEDURE: Interested individuals should email a curriculum vitae, up to three representative publications, names / phones / emails of three to five references and a cover note describing research interests, professional goals and availability. Please submit materials to: Cordelia Nwaekwe, Assistant to Professor Moody Email: moodylab at icsi.berkeley.edu URL: www.icsi.berkeley.edu/~moody/ Applications submitted on or before August 31, 2004 will receive priority consideration. We will continue considering candidates until the position is filled. Applicants should be available to begin a one year position between September 1, 2004 and January 1, 2005. Extension to a second year and beyond will depend upon performance in year one and procurement of additional funding. ICSI is an equal opportunity employer; minorities and women are encouraged to apply. From zoubin+cs at gatsby.ucl.ac.uk Tue Aug 3 13:44:33 2004 From: zoubin+cs at gatsby.ucl.ac.uk (zoubin+cs@gatsby.ucl.ac.uk) Date: Tue, 3 Aug 2004 18:44:33 +0100 Subject: Three Faculty Positions in CS at University College London Message-ID: <16655.52993.992548.62606@wald.gatsby.ucl.ac.uk> UNIVERSITY COLLEGE LONDON Department of Computer Science Three Lecturer / Senior Lecturer Posts (UK Lecturer is roughly equivalent to US Assistant Professor) We are seeking talented researchers whose interests are aligned with our existing departmental strengths. One such focus is in the application and theory of Machine Learning and Artificial Intelligence. A candidate with these strengths will be expected to play a leading role in the research and teaching of ML/AI in the Department, and especially in the development of our MSc programme in Intelligent Systems (see http://www.cs.ucl.ac.uk/pg/is/). A successful candidate will have the opportunity to interact with members of the Gatsby Unit at UCL (see http://www.gatsby.ucl.ac.uk) and may possible hold an honorary appointment there. The strengths of the Gatsby Unit lie in Machine Learning and Theoretical Neuroscience. You can find out more about us at http://www.cs.ucl.ac.uk . Further details of the posts and the application procedure can be found at http://www.cs.ucl.ac.uk/vacancies . The closing date for applications is Thursday, 30 September 2004. From paulv at ling.ed.ac.uk Fri Aug 6 07:10:01 2004 From: paulv at ling.ed.ac.uk (Paul Vogt) Date: Fri, 06 Aug 2004 12:10:01 +0100 Subject: CFP: Adaptive Behavior: Special Issue on Language Acquisition and Evolution Message-ID: <41136709.50707@ling.ed.ac.uk> Call for Papers: Language Acquisition and Evolution Special Issue: Adaptive Behavior Guest editor: Paul Vogt Submission deadline: 15 November 2004 URL: http://www.ling.ed.ac.uk/~paulv/ab-cfp.html It is widely believed that language has evolved through mutual interactive behaviour of individuals within an ecological niche, through individual adaptations and self-organisation. Humans communicate with each other about events that happen in their environment. When novel events occur, they might construct new internal representations of these events - either by learning from other's behaviour or by inventing new behaviour. They can then transmit this newly constructed knowledge to other humans. By subsequent local interactions between individuals, self-organisation can guide the emergence of a global structure called language as has repeatedly been shown by several computer models. Many computational studies on the evolution of language have primarily focused on the idea that language is a complex dynamical adaptive system, as outlined above. Central to these studies is the cultural evolution of language, i.e. language is thought to have evolved based on cultural transmissions rather than on biological adaptations. Cultural transmission of language is impossible without the ability to learn language. This special issue is inspired by a recent Symposium on Language Evolution and Acquisition held at the 2004 Human Behavior & Evolution Society conference, and focuses on the relation between language origins, acquisition and evolution. Two main themes to be explored are how could language acquisition mechanisms have evolved, and the impact that particular acquisition skills may have had on the evolution of language itself. /Adaptive Behavior/ solicits papers that present synthetic studies that explicitly focuses on the interface between language origins and/or evolution, and language acquisition. The models should involve either computer simulations or robotic platforms. However, those papers that integrate models with psychological, linguistic or biological data are particularly welcome. Papers in this special issue should not exceed the equivalent length of 10 journal pages. See the web-site of the Adaptive Behavior (http://www.isab.org.uk/journal/) for further instructions. Topics include (though not restricted): * Evolution of o language acquisition skills. o joint attention. o corrective feedback. * Phonetics. * Lexicon formation. * Meaning inference. * Symbol grounding in language. * Emergence of syntax or grammar. * Language change. * Language diversity. If you intend to submit a paper, please send a tentative title and abstract to the guest editor (Paul Vogt, paulv at ling.ed.ac.uk). (This would help to speed up the selection of reviewers.) If you are uncertain whether your paper would satisfy the topic of this special issue, or if you wish further information, please contact the guest editor too. Important dates: * *15 November 2004: Submission deadline.* * 15 February 2005: Notification of acceptance. * 15 April 2005: Revised versions due. * 30 May 2005: Authors notified (for revised papers). * Late 2005: Special issue appears. -- Dr. Paul Vogt, Research Fellow Language Evolution and Computation Research Unit School of Philosophy, Psychology and Language Sciences University of Edinburgh Phone: +44 (0)131 6503960 Fax: +44 (0)131 6503962 URL: http://www.ling.ed.ac.uk/~paulv From ahu at cs.stir.ac.uk Fri Aug 6 11:03:19 2004 From: ahu at cs.stir.ac.uk (Dr. Amir Hussain) Date: Fri, 6 Aug 2004 16:03:19 +0100 Subject: Final Call for Participation: BICS'2004, Stirling, Scotland, UK Message-ID: <003401c47bc6$89c77db0$c16d6e42@DrAmir> Brain Inspired Cognitive Systems (BICS-2004): Final Call for Participation University of Stirling, Scotland, UK August 29 - September 1, 2004 Share the latest research, developments and ideas in the wide arena of disciplines encompassed under the heading of BICS-2004, including: First International ICSC Symposium on Cognitive Neuro Science (CNS) Chair: Prof. Igor Aleksander, Imperial College London, U.K Second International ICSC Symposium on Biologically Inspired Systems (BIS) Chair: Prof. Leslie Smith, University of Stirling, U.K. Third International ICSC Symposium on Neural Computation (NC) Chair: Dr. Amir Hussain, University of Stirling, U.K. Conference Sponsors: The Institution of Electrical Engineers (IEE) University of Stirling, Scotland, UK Imperial College London, UK ICSC Interdisciplinary Research, Canada Workshop: Information coding in early sensory stages Plenary Debate : Machine Consciousness: Does it Make Sense? Tutorial : Models of Consciousness: The world scene Prof I Aleksander, Imperial College London Tutorial: Implementing neural models in silicon Prof L S Smith, University of Stirling, Scotland Tutorial: Neural Networks for Adaptive Speech Enhancement Dr A. Hussain, University of Stirling, Scotland Plenary Lecture : Fifteen years of Neuromorphic Engineering: progress, problems, and prospects; Prof R. Douglas, ETH Zurich, Switzerland Plenary Lecture: Self-Organisation in the Nervous System: the Establishment of Nerve Connections by an Inductive Mechanism; Prof David Willshaw, University of Edinburgh, Scotland Plenary Lecture: Computation, cognition, and control Dr. O Holland, University of Essex, U.K. Plenary Lecture: Neural Nets: the hype and the reality, from an industrial perspective Prof G Hesketh, Rolls-Royce, UK Plenary Lecture: Disentangling signals blindly from nonlinear mixtures Prof E Oja, Helsinki University of Technology, Finland Plenary Lecture: Attention and Consciousness as Control System Components in the Brain Prof John G Taylor, King's College, U.K and contributed papers on: Audition and Robotics (BIS) Neural Modelling (BIS) Neuromorphic Approaches (BIS) Neuromorphic and spiking networks: BSS (BIS) Novel approaches (BIS) Vision (BIS) Computational Neural Network Models (NC) Neural Network Applications (NC) Software and Hardware Implementations (NC) Neurological Analysis (CNS) Representation and Modelling (CNS) Attention and Emotion (CNS) Agent Consciousness (CNS) Venue: beautiful campus University of Stirling, Scotland, with an excellent centre to visit Scotland from. BICS2004 is being held in Stirling, a historic city located in the heart of Scotland. The conference venue and accommodation are all on the University campus, which is convenient for visiting the ancient castle and Wallace monument, or for going further a field and exploring the beautiful countryside. For the full programme: HYPERLINK "http://www.icsc-naiso.org/conferences/bics2004/bics-cfp.html"http://www icsc-naiso.org/conferences/bics2004/bics-cfp.html Registration on page: HYPERLINK "http://www.cs.stir.ac.uk/~lss/BICS2004/registration1.html"http://www.cs stir.ac.uk/~lss/BICS2004/registration1.html NOTE: Authors of selected papers will be invited to submit an extended version of their paper for publication in a special issue of the Neurocomputing Journal, published by Elsevier Science B.V. (HYPERLINK "http://www.elsevier.nl/locate/neucom"http://www.elsevier.nl/locate/neuc om) - Dr. Amir Hussain Senior Lecturer in Computing Science University of Stirling Stirling FK9 4LA, UK Email: HYPERLINK "mailto:ahu at cs.stir.ac.uk"ahu at cs.stir.ac.uk HYPERLINK "http://www.cs.stir.ac.uk/~ahu"http://www.cs.stir.ac.uk/~ahu Tel/Fax: (+44) 01786 - 467437 / 464551 -- The University of Stirling is a university established in Scotland by charter at Stirling, FK9 4LA. Privileged/Confidential Information may be contained in this message. If you are not the addressee indicated in this message (or responsible for delivery of the message to such person), you may not disclose, copy or deliver this message to anyone and any action taken or omitted to be taken in reliance on it, is prohibited and may be unlawful. In such case, you should destroy this message and kindly notify the sender by reply email. Please advise immediately if you or your employer do not consent to Internet email for messages of this kind. Opinions, conclusions and other information in this message that do not relate to the official business of the University of Stirling shall be understood as neither given nor endorsed by it. From gasser at cs.indiana.edu Mon Aug 9 13:01:31 2004 From: gasser at cs.indiana.edu (Michael Gasser) Date: Mon, 9 Aug 2004 12:01:31 -0500 (EST) Subject: Computational linguistics faculty position: Indiana University Message-ID: (This position is for a "computational linguist" very broadly construed. Connectionist researchers are encouraged to apply. They would find plenty of like-minded colleagues and students at Indiana. --Mike Gasser) -------------------------------------------------------------------- Indiana University, Bloomington, Indiana. Faculty position beginning Fall, 2005 As one of a series of new appointments, the Cognitive Science Program at Indiana University seeks applicants with a developing strong record of research in computational linguistics, broadly defined. We are looking for someone with vision, energy, and a desire to explore new forms of interdisciplinary study. Areas of specialty could include, but are not limited to: computational, statistical, psychological, experimental, and developmental approaches. The right candidate is more important than the specific disciplinary background. Although we anticipate appointment at the junior rank, more senior appointments are also possible for exceptional applicants. Applicants should send full dossiers, including letters of recommendation and sample of papers. Indiana University is an equal opportunity/affirmative action employer. Applications from women and minority group members are especially encouraged. Please send materials to Professor Richard Shiffrin, Computational Linguistics Search Committee, Cognitive Science Program, 1033 E. Third St., Sycamore 0014, Bloomington, IN 47405. Applications received by December 1, 2004 are assured full consideration. Please see our website: http://www.cogs.indiana.edu for information regarding additional open faculty positions. If you have questions about this position, you may contact Michael Gasser at gasser at indiana.edu. From maass at igi.tugraz.at Mon Aug 9 17:09:50 2004 From: maass at igi.tugraz.at (Wolfgang Maass) Date: Mon, 09 Aug 2004 23:09:50 +0200 Subject: Phd /Postdoc position in biological vision Message-ID: <4117E81E.4050802@igi.tugraz.at> A position for a Phd-student or Postdoc is available in our research project COMPUTER MODELS FOR BIOLOGICAL VISION SYSTEMS This is a subproject within a larger research project on COGNITIVE VISION, see http://www.acin.tuwien.ac.at/groups/robtec/fsp/fsp.htm Research for this subproject is carried out by our Institute in collaboration with the Department for the Physiology of Cognitive Processes (Director Nikos Logothetis) at the MPI for Biological Cybernetics in T=FCbingen, see http://www.kyb.tuebingen.mpg.de/lo/. The research in this subproject will focus on the design of theoretical models as well as computer models on several spatial scales, with biologically realistic anatomy and dynamics. These models will serve as testbed for the exploration of learning algorithms that may endow such models with partial visual function for movement analysis and object recognition. In addition these models will serve as links to experimental neuroscientists at the MPI T=FCbingen for the design of new experiments and the integration of new experimental data on movement analysis and object recogntion in primates.. These models will also serve as link to researchers from computer vision in the larger COGNITIVE VISION project, where we will compare empirically successful approaches for generic object recognition in computer vision and associated learning algorithms with biological data and models. We are looking for a highly qualified and strongly motivated student/postdoc with experience in areas such as computer vision, machine learning, computer simulations, computational neuroscience, programming. Courses and seminars for Phd-students are carried out in English, leading to a Phd in Computer Science at the Graz University of Technology. Applications should be sent by August 16 to Wolfgang Maass maass at igi.tugraz.at -- Prof. Wolfgang Maass Institut fuer Grundlagen der Informationsverarbeitung Technische Universitaet Graz Inffeldgasse 16b , A-8010 Graz, Austria Tel.: ++43/316/873-5811 Fax ++43/316/873-5805 http://www.igi.tugraz.at/maass/Welcome.html From mcgl-ci0 at wpmail.paisley.ac.uk Tue Aug 10 05:19:44 2004 From: mcgl-ci0 at wpmail.paisley.ac.uk (Stephen McGlinchey) Date: Tue, 10 Aug 2004 10:19:44 +0100 Subject: CGAIDE Special Session on Neural Networks - Submission deadline extended till 31 August 2004 Message-ID: Due to popular demand, we have extended the deadlines for paper submission and acceptance notification for the CGAIDE 2004 International Conference on Computer Games: Artificial Intelligence, Design and Education. This conference includes a special session on neural networks. Papers should now be submited by 31st August 2004. C A L L F O R P A P E R S Special Session On NEURAL NETWORKS IN COMPUTER GAMES AND SIMULATION as part of International Conference on Computer Games: Artificial Intelligence, Design and Education (CGAIDE) 8-10 November 2004 Hosted at the Microsoft Campus, Reading, UK http://www.scit.wlv.ac.uk/~cm1822/cgaide.htm The main objectives of this special session are: * To provide a forum for presenting and discussing the application of neural networks in computer games and simulations * To promote collaboration between the computer games and computational intelligence research communities. Neural Networks (NN) in in Computer Games and Simulations =========================================================== We invite submission of papers presenting recent research on Artificial Neural Networks applied to any aspect of computer games technology or simulation. The scope of the session may include topics from the following non-exclusive list. Autonomous control of game agents. Processing of game content data. Real-time feature extraction from game data. Simulation or anaylisis of emotions / intelligence. Automatic analysis of human player behaviours. Synthesis of dynamic game content. Strategic game applications (e.g. Go and Chess) Optimising search spaces. Submissions are encouraged from any other related application of neural networks in games or simulation. Full papers should be sent to stephen.mcglinchey at paisley.ac.uk by the submission deadline. Send a full paper - not previously published - in Word format (no smaller than 10-point format) to include author, address, e-mail, keywords and abstract (200 words max) in one of the following categories: Regular paper max. 5 pages Extended Paper max. 8 pages Critical Review paper max. 10 pages Important dates: Draft paper submission : 31 August 2004 Notification of acceptance : 20 September 2004 Camera-ready submission deadline : 4 October 2004 Please send enquiries to: Stephen McGlinchey (stephen.mcglinchey at paisley.ac.uk) School of Computing University of Paisley Paisley, Scotland or Darryl Charles (dk.charles at ulster.ac.uk) School of Computing and Information Engineering University of Ulster Coleraine, Northern Ireland. From dirk at bioss.sari.ac.uk Wed Aug 11 14:31:57 2004 From: dirk at bioss.sari.ac.uk (Dirk Husmeier) Date: Wed, 11 Aug 2004 19:31:57 +0100 Subject: PhD and postdoc positions in computational systems biology Message-ID: <411A661D.602B25A3@bioss.ac.uk> I would be grateful if you could bring the following webpage to the attention of suitable candidates: http://www.bioss.sari.ac.uk/~dirk/jobs/jobAdvert.pdf This is a job advert for 6 research positions in systems biology to investigate regulatory and signalling networks controlling bacterial disease development. Positions 5 (postdoctoral researcher in genetic network analysis) and 6 (PhD student in structural genomics) are ideally suited for candidates with a strong mathematical and computational background, who are interested in applying machine learning methods to computational molecular biology. Many thanks and best regards Dirk -- Dirk Husmeier Biomathematics & Statistics Scotland (BioSS) JCMB, The King's Buildings, Edinburgh EH9 3JZ, United Kingdom http://www.bioss.sari.ac.uk/~dirk From j.odoherty at fil.ion.ucl.ac.uk Thu Aug 12 08:49:44 2004 From: j.odoherty at fil.ion.ucl.ac.uk (John O'Doherty) Date: Thu, 12 Aug 2004 13:49:44 +0100 Subject: Post-doctoral position in fMRI of reward and decision making Message-ID: <200408121349.44654.j.odoherty@fil.ion.ucl.ac.uk> Post-doctoral position in fMRI of reward and decision making A post-doctoral position is available to investigate the neural mechanisms of reward-learning, choice and decision making in the human brain. The post will involve the application of computational models to fMRI data, as well as the design and conduct of fMRI experiments. This position would ideally suit a candidate with a background in computational neuroscience who is interested in gaining experience of brain imaging. The project will be carried out using fMRI facilities at the Broad Center for the Biological Sciences at Caltech. Please send a curriculum vitae and brief cover letter to John O'Doherty, j.odoherty at fil.ion.ucl.ac.uk. The position is for two years with a start date from January 2005. The California Institute of Technology is an Equal Opportunity/Affirmative Action Employer and encourages the applications of qualified women, minorities, veterans and disabled persons. -- -------------- Dr John O'Doherty Wellcome Department of Imaging Neuroscience Institute of Neurology University College London London WC1N 3BG Tel: +44 207 8337479 Fax: +44 207 8131420 e-mail: j.odoherty at fil.ion.ucl.ac.uk web: http://www.fil.ion.ucl.ac.uk/~jdoherty From terry at salk.edu Fri Aug 13 13:37:20 2004 From: terry at salk.edu (Terry Sejnowski) Date: Fri, 13 Aug 2004 10:37:20 -0700 (PDT) Subject: NEURAL COMPUTATION 16:9 In-Reply-To: <200406261632.i5QGWPO06371@dax.salk.edu> Message-ID: <200408131737.i7DHbKn81419@kepler.snl.salk.edu> Neural Computation - Contents - Volume 16, Number 9 - September 1, 2004 NOTES A Note on the Applied Use of MDL Approximations Daniel J. Navarro Optimal Reduced-Set Vectors for Support Vector Machines with a Quadratic Kernel Thorsten Thies and Frank Weber LETTERS Stochastic Reasoning, Free Energy, and Information Geometry Shiro Ikeda, Toshiyuki Tanaka, and Shun-ichi Amari Blind Separation of Positive Sources by Globally Convergent Gradient Search Erkki Oja and Mark Plumbley A New Concept for Separability Problems in Blind Source Separation Fabian J. Theis Modeling Mental Navigation in Scenes with Multiple Objects Patrick Byrne and Suzanna Becker Failure of Motor Learning for Large Initial Errors Terence D. Sanger Fair Attribution of Functional Contribution in Artificial and Biological Networks Alon Keinan, Ben Sandbank, Claus, C. Hilgetag, Isaac Meilijson, and Eytan Ruppin Recurrent Network with Large Representational Capacity Drazen Domijan A Solution for Two-Dimensional Mazes with Use of Chaotic Dynamics in a Recurrent Neural Network Model Yoshikazu Suemitsu and Shigetoshi Nara Online Adaptive Decision Trees (OADT) Jayanta Basak ----- ON-LINE - http://neco.mitpress.org/ SUBSCRIPTIONS - 2004 - VOLUME 16 - 12 ISSUES Electronic only USA Canada* Others USA Canada* Student/Retired $60 $64.20 $108 $54 $57.78 Individual $95 $101.65 $143 $85 $90.95 Institution $635 $679.45 $689 $572 $612.04 * includes 7% GST MIT Press Journals, 5 Cambridge Center, Cambridge, MA 02142-9902. Tel: (617) 253-2889 FAX: (617) 577-1545 journals-orders at mit.edu ----- From jyoshimi at ucsd.edu Tue Aug 17 02:55:30 2004 From: jyoshimi at ucsd.edu (Jeff Yoshimi) Date: Mon, 16 Aug 2004 23:55:30 -0700 Subject: Simbrain 1.0.5 Released Message-ID: <6DC3630C-F01A-11D8-8A30-000393A6E67A@ucsd.edu> A new version of Simbrain (http://simbrain.sourceforge.net/) has been released. This is an interim release, to make recent changes available prior to beginning work on the next iteration, which will involve a major redesign and integration with Snarli (http://snarli.sourceforge.net/) Primary areas of improvement in 1.0.5 are as follows: (1) complete rewrite of the world component, which now allows worlds to be edited in the GUI and includes more sophisticated objects, (2) complete rewrite of the gauges, which have been separately released as the program "HiSee" (http://hisee.sourceforge.net/), (3) updates to the network interface, right-click popup menus in particular, (4) a documentation rewrite. Other improvements include: recurrent connections show in the GUI, improved control over input and output nodes, ability to round off activation values and set precision, new simulations and organization to simulation directory, new documentation viewer, and numerous bug fixes. Your comments and suggestions would be appreciated as we enter the next phase of development. As always, we are seeking developers and help. - Jeff From samengo at cab.cnea.gov.ar Tue Aug 17 08:19:37 2004 From: samengo at cab.cnea.gov.ar (Ines Samengo) Date: Tue, 17 Aug 2004 09:19:37 -0300 Subject: Paper on a subjective distance in the space of stimuli. Message-ID: <4121F7D9.CF0BB1C@cab.cnea.gov.ar> Dear connectionists, the following preprint, to appear in Neural Computation, may be of interest to some of you. Best regards, Ines Samengo. ---------------------------------------------------------------- A subjective distance between stimuli: quantifying the metric structure of representations D. Oliva, I. Samengo, S. Leutgeb, S. Mizumori As subjects perceive the sensory world, different stimuli elicit a number of neural representations. Here, a subjective distance between stimuli is defined, measuring the degree of similarity between the underlying representations. As an example, the subjective distance between different locations in space is calculated from the activity of rodent hippocampal place cells, and lateral septal cells. Such a distance is compared to the real distance, between locations. As the number of sampled neurons increases, the subjective distance shows a tendency to resemble the metrics of real space. http://arXiv.org/abs/q-bio/0408008 -- ______________________________________________________ Ines Samengo samengo at cab.cnea.gov.ar http://www.cab.cnea.gov.ar/users/samengo/samengo.html tel: +54 2944 445100 - fax: +54 2944 445299 Centro Atomico Bariloche (8.400) San Carlos de Bariloche Rio Negro, Argentina ______________________________________________________ From Kari.Torkkola at motorola.com Wed Aug 18 13:20:28 2004 From: Kari.Torkkola at motorola.com (Kari Torkkola) Date: Wed, 18 Aug 2004 10:20:28 -0700 Subject: JOB: Machine learning at Motorola, Phoenix, AZ Message-ID: <41238FDC.2070000@motorola.com> Motorola has an open position in machine learning in metro Phoenix area: Department Description Motorola Labs - Intelligent Systems Research Lab, Phoenix, AZ At Motorola's Intelligent Systems Research Lab we research machine intelligence and contextual understanding to design the next generation mobile and personal devices such as driver assistance systems and intelligent cell phones. We research user needs in these environments and conduct the front-end development to provide the intelligent systems solutions that are implemented across a range of products. Scope of Responsibilities/Expectations This position will be focused on applying an understanding of machine intelligence to the development of software-based intelligent systems for deployment in next-generation automotive, personal, and home devices. The Machine Intelligence Researcher will have the following responsibilities: - Develop and implement techniques that infer the user's state, activity and intention from analysis of device and environment-based sensors, personal data and models of user behavior. - Develop algorithms for user modeling, pattern recognition, and static and sequential sensor data processing. These algorithms might include Support Vector Machines, Bayes Nets, Hidden Markov Models, or Particle Filters, for example. - Proactively identify opportunities for technology development, develop technical proposals and research plans and carry out research. - Work closely with other machine intelligence and human interaction researchers and product sector design engineers. - Keep up with the state of the art in machine learning by following the latest journals and conferences and the Internet. - Publish and present results to peers, developers, management and customers. Specific Knowledge/Skills - PhD in computer science, signal processing, mathematics, statistics, or relevant discipline with 2 years of experience or M.S. with 5 years of experience. - Strong record of research and innovation in the area of pattern recognition and machine learning. - Significant experience in software development, such as Matlab for algorithm development and Java or C/C++ for implementation. - Experience with large real world data sets is desirable. - Experience in mobile device ad-hoc networking technologies and applications of pervasive personal computing would be an advantage. - Good organizational and communication skills, both written and oral. - Ability to interact well with a multi-disciplinary technology team in the creation of new designs and approaches. - Able to work well across a decentralized geographically dispersed organization. - Flexibility in scope of job responsibilities. - Willingness to do light travel. Please submit your resume through http://www.motorolacareers.com Refer to job id 13570. Alternatively, email the resume to | Greg.Kozlowski | at | motorola | dot | com Informal questions can be sent to | Kari.Torkkola | at | motorola | dot | com From claus.neubauer at siemens.com Mon Aug 16 14:24:21 2004 From: claus.neubauer at siemens.com (Neubauer, Claus) Date: Mon, 16 Aug 2004 14:24:21 -0400 Subject: Siemens Corporate Research: position in neural network modeling and machine learning Message-ID: <20B20848358CDA44AB6A2E277D2E1C5E0282AC1B@postoffice.scr.siemens.com> Siemens Corporate Research Inc., Princeton, NJ has an opening for a Research Scientist. In this position, the candidate will be conducting leading-edge research and development related to neural network modeling and machine learning for various medical and industrial applications. Ideal candidates will have a Ph.D. in CS or related fields with a proven record in research, innovative thinking, real world problem solving and fast prototyping. Candidates should have C/C++ or Java proficiency on MS Windows platform. Experience in applying neural network and machine learning techniques in a field such as machine diagnosis, monitoring, predictive maintenance, data mining, decision support, biomedical informatics or computer vision will be a big plus. Candidates need to have strong interpersonal skills, be able to work independently on problems, be an effective team player and be willing to accept challenge and responsibility. We offer a competitive salary and benefits package that reflects our leadership status. For consideration, please email your CV or resume to: _____________________ Claus Neubauer, Ph.D. Program Manager Intelligent Data Analysis & Modeling Siemens Corporate Research 755 College Road East Princeton, NJ 08540, USA Email claus.neubauer at siemens.com For more information, please visit: http://www.scr.siemens.com From amir at ymer.org Tue Aug 31 08:30:21 2004 From: amir at ymer.org (Amir Reza Saffari Azar) Date: Tue, 31 Aug 2004 05:30:21 -0700 Subject: Biological Neural Network Toolbox for MATLAB: Ver 1.0 Message-ID: <20040831123022.30752.qmail@webmail-2-5.mesa1.secureserver.net> I'm pleased to announce the first release of Biological Neural Network (BNN) Toolbox for MATLAB. This package is a free open source software for simulating models of brain and central nervous system, based on MATLAB computational platform. As the name of the toolbox implies, the main goal of this package is to provide users a set of integrated tools to create models of biological neural networks and simulate them easily, without the need of extensive coding. Users can create and simulate a huge network of spiking neurons in less than 10 lines of code (or even in one line, if they give all arguments to the main function) using predefined library functions. It is also possible to create and add new models to the library easily, using template library items. Current Features: 1) Users can create and simulate any kind of BNN with this toolbox. 2) Architectures: Custom, Fully Connected, Multilayer Feedforward, Multilayer Feedforward with General, Lateral, and Local Feedbacks. 3) Spiking Neuron Models: Custom, Linear and Quadratic Integrate-and-Fire, Hodgkin-Huxley, FitzHugh-Nagumo, Morris-Lecar, Canonical Phase, and Izhikevich. 4) PSP Models: Custom, Two Versions of Alpha-Function, and Dirac Delta Function. 5) Event based computation. 6) Users can select several MATLAB ODE solvers for their model. 7) Custom adaptation models. 8) Static and dynamic external inputs. 9) Custom user and stop functions. 10) Examples and Library templates. Next versions will have an additional user friendly GUI package, will have more library models, and will be more faster than this version. The author would be very grateful for any comments, reviews, discussions, bug reports, and wishes from users and believes that these feedbacks would make this toolbox alive and evolving. If you have any kind of model related to the neuroscience topics, including but not limited to network architectures, neuron models, synapse models, adaptation mechanisms, and if you want the future releases contain these models, feel free to contact with the author. This toolbox is created and developed by personal interests of the author in modeling brain and CNS and is provided to other users as an open source free software under GNU GPL. Feel free to copy, modify, and distribute it according to the license. To obtain the latest version of GPL, please refer to http://www.gnu.org. Links: Email: amir at ymer.org Website: http://www.ymer.org Alt. Website: http://ee.sut.ac.ir/faculty/saffari/res-bnntoolbox.htm ------------------------------- "Before the beginning of great brilliance, there must be chaos" Amir Reza Saffari Azar Alamdari Email: amir at ymer.org Web: http://ymer.org From meeden at cs.swarthmore.edu Tue Aug 31 12:26:04 2004 From: meeden at cs.swarthmore.edu (Lisa Meeden) Date: Tue, 31 Aug 2004 12:26:04 -0400 (EDT) Subject: CFP AAAI Spring Symposium: Developmental Robotics Message-ID: CALL FOR PAPERS AAAI Spring Symposium: Developmental Robotics March 21-23, 2005 at Stanford University Submission deadline October 8, 2004 For details see http://cs.brynmawr.edu/DevRob05/ Developmental robotics is a new approach that focuses on the autonomous self-organization of general-purpose control systems. Developmental robotics is a move away from task-specific methodologies where a robot is designed to solve a particular pre-defined problem. This new approach explores the kinds of perceptual, cognitive, and behavioral capabilities that a robot can discover through self-motivated actions based on its own physical morphology and the dynamic structure of its environment. Initially a developmental system might bootstrap itself with some innate knowledge or behavior, but with experience could create more complex representations and actions, leading to complete Autonomous Mental Development (AMD)[1]. Developmental robotics is different from many learning and evolutionary systems in that the reinforcement signal, teacher target, or fitness function comes from within the system. In this manner, these systems are designed to rely more on mechanisms such as self-motivation, homeostasis, or emotions. We invite contributions on architectures for developmental robotics, examples of developmental behavior in robots, as well as features or mechanisms of developmental processing including, but not limited to: self-organization, self-exploration, self-motivation, categorization, artificial emotional systems, value systems, and anticipation-driven learning. [1] Weng, J., McClelland, J., Pentland, A., Sporns, O., Stockman, I., Sur M., and Thelen, E. (2000). Autonomous Mental Development by Robots and Animals, Science, vol. 291, no. 5504, pp. 599 - 600. Available at http://www.cse.msu.edu/dl/SciencePaper.pdf --- Lisa Meeden Computer Science Dept. Associate Professor Swarthmore College meeden at cs.swarthmore.edu 500 College Ave. http://www.cs.swarthmore.edu/~meeden Swarthmore, PA 19081 610-328-8565 (voice) 610-328-8606 (fax) From intneuro at sbcglobal.net Tue Aug 31 11:17:50 2004 From: intneuro at sbcglobal.net (INTEGRATIVE NEUROSCIENCE) Date: Tue, 31 Aug 2004 08:17:50 -0700 (PDT) Subject: call for papers: JIN special issue honoring Paul Bach-y-Rita, Wisconsin University Medical School Message-ID: <20040831151750.77104.qmail@web81103.mail.yahoo.com> Journal of Integrative Neuroscience (JIN) An Interdisciplinary Journal CALL FOR PAPERS: Non-synaptic Communication in Brains and Integrative functions : a special issue honoring Paul Bach-y-Rita, Wisconsin University Medical School and Biomedical Engineering To appear in: VOLUME 4, ISSUE 4 DECEMBER 2005 The synaptic model of neurocommunication in the brain has dominated the neurosciences for more than a century. Generally, little consideration is given to other modes of neurotransmission in animal and human brains, even though there is indirect evidence that less than half of the communication between cells is by synapses. Non-synaptic diffusion neurotransmission may be the primary information transmission mechanism in certain normal and abnormal functions. Non-synaptic diffusion is vastly more economical than synaptic transmission in regards to space and energy expenditure in the brain, and may play a role in the evolution of species and in a proposed Law of Conservation of Energy and Space in the Brain. In view of the non-synaptic nature of much of the brain's information management, mechanistic concepts, such as comparisons of the brain to a digital computer become less tenable than is conventionally believed. The human brain is much more technically sophisticated than any present or even presently foreseeable electronic device. Even the nervous systems of insects defy simulation on the most advanced computers. "We see with our brains not eyes" .............Paul Bach-y-Rita Paul Bach-y-Rita, M.D. is a professor of rehabilitation medicine and of biomedical engineering at the University of Wisconsin. He is also chief scientist and chairman of the Board of WICAB. His discoveries have enabled the blind to see, the victims of leprosy to feel, and the quadriplegic to enjoy sex. He has researched and published extensively in human-machine interfaces, related neuroscience and Rehabilitation Engineering, brain plasticity, brain neurotransmission, development of instrumentation for home rehabilitation, development of late rehabilitation of brain damaged and of persons with facial paralysis, and functional assessment by computer image analysis. The books that he has written, edited, or co-authored include Nonsynaptic Diffusion Neurotransmission and Late Brain Reorganization, Vitamins: Their Use and Abuse, Brain Mechanisms in Sensory Substitution, Recovery of Function: Theoretical Considerations for Brain Injury Rehabilitation, Traumatic Brain Injury (Comprehensive Neurologic Rehabilitation, Vol 2). He was founding director (starting in 1975) of the San Francisco Rehabilitation Engineering Center. He is the co-inventor of the tongue human-machine interface. Authors should be aware of the following tentative key dates: Proposals to Special Edition Editor (Steve Kercel) due no later than January 20, 2005. (Early submittals are encouraged. Preferred submission channel is e-mail, kercel1 at suscom-maine.net). A proposal consists of an abstract of approximately one page, an estimate of the the expected length of the proposed paper, a list of co-authors (if any), and brief (one page of highlights, with emphasis on connection to Dr. Bach-y-Rita) CV of principal author. The Special Edition Editor expects to issue accept/reject notifications of specific proposals within one month of the date that he receives the proposal. Early submissions will receive a correspondingly early decision. Full manuscript (including illustrations and references) due April 30, 2005. Referee comments will be sent to the authors as soon as practicable. Revised manuscript, accounting for referee and editorial comments due July 31, 2005. The finished edited camera ready copy due September 30, 2005. Dr. Stephen W. Kercel 2 Brian Drive Brunswick ME 04011 USA Phone: (207) 729-4504 FAX: (207) 729-6226 E-mail: kercel1 at suscom-maine.net From cgunay at emory.edu Sun Aug 29 23:32:24 2004 From: cgunay at emory.edu (Cengiz Gunay) Date: Sun, 29 Aug 2004 23:32:24 -0400 (EDT) Subject: Ph.D. dissertation: Hierarchical learning of conjunctive concepts in spiking neural nets In-Reply-To: References: Message-ID: Dear connectionists, My Ph.D. dissertation titled "Hierarchical learning of conjunctive concepts in spiking neural networks", together with related publications, is available from the web page: http://www.cacs.louisiana.edu/~cxg9789/Neuroidal Below you can find the abstract for the dissertation. Abstract -------- The temporal correlation hypothesis proposes that synchronous activity in different regions of the brain describes integral entities (von der Malsburg, 1981; Singer and Gray, 1995). This temporal binding approach is a possible solution to the longstanding binding problem of representing composite objects (Rosenblatt, 1961). To complement the dynamic nature of temporal binding, a recruitment learning method has been proposed for providing long-term storage (Feldman, 1982; Valiant, 1994). We improve the recruitment method to use a more biologically realistic and computationally powerful spiking neuron model. However, using continuous-time spiking neurons and brain-like connectivity assumptions poses new problems in hierarchical recruitment. First, we propose timing parameter constraints for recruitment over asymmetrically connected delay lines. We verify these constraints using simulations. These constraints are useful for both building abstract networks and providing insight into bio-mechanisms that ensure signal integrity in the brain. As a second problem, we calculate the required feedforward excitatory and lateral inhibitory connection densities for stable propagation of activity in hierarchical structures of the network. We give analytic solutions using a stochastic population model of a simplified layered network. Our approach is independent of the network size, but depends on lateral inhibition and noisy feedforward delays. --- Thanks, Cengiz Gunay Postdoctoral Fellow, Dept. of Biology Emory University, Atlanta, GA, USA. -- cgunay at emory.edu cengique at users.sf.net cengique at yahoo.com Lab: +1-404-727-4103 Home/Cell: +1-337-255-3660 http://www.cacs.louisiana.edu/~cxg9789 ICQ# 21104923, cengique at jabber.org --