From bogus@does.not.exist.com Mon Dec 1 10:37:55 2003 From: bogus@does.not.exist.com () Date: Mon, 1 Dec 2003 16:37:55 +0100 Subject: ESANN'2004 : extended deadline Message-ID: ---------------------------------------------------- | | | ESANN'2004 | | | | 12h European Symposium | | on Artificial Neural Networks | | | | Bruges (Belgium) - April 28-29-30, 2004 | | | Extended deadline | ---------------------------------------------------- Due to numerous requests, we are pleased to announce that the deadline for submitting papers to the ESANN'2004 conference has been extended. New deadline: December 12, 2003. The ESANN'2004 covers most of the topics related to the neural network field (see http://www.dice.ucl.ac.be/esann for details). Six special sessions will also be organized: 1. Neural methods for non-standard data B. Hammer, Univ. Osnabrck, B.J. Jain, Tech. Univ. Berlin (Germany) 2. Soft-computing techniques for time series forecasting I. Rojas, H. Pomares, Univ. Granada (Spain) 3. Neural networks for data mining R. Andonie, Central Washington Univ. (USA) 4. Theory and applications of neural maps U. Seiffert, IPK Gatersleben, T. Villmann, Univ. Leipzig, A. Wismller, Univ. Munich (Germany) 5. Industrial applications of neural networks L.M. Reyneri, Politecnico. di Torino (Italy) 6. Hardware systems for Neural devices P. Fleury, A. Bofill-i-Petit, Univ. Edinburgh (Scotland, UK) Instructions concerning the submission of papers are detailed on the web site of the conference. ======================================================== ESANN - European Symposium on Artificial Neural Networks http://www.dice.ucl.ac.be/esann * For submissions of papers, reviews,... Michel Verleysen Univ. Cath. de Louvain - Microelectronics Laboratory 3, pl. du Levant - B-1348 Louvain-la-Neuve - Belgium tel: +32 10 47 25 51 - fax: + 32 10 47 25 98 mailto:esann at dice.ucl.ac.be * Conference secretariat d-side conference services 24 av. L. Mommaerts - B-1140 Evere - Belgium tel: + 32 2 730 06 11 - fax: + 32 2 730 06 00 mailto:esann at dice.ucl.ac.be ======================================================== From maass at igi.tu-graz.ac.at Tue Dec 2 11:16:27 2003 From: maass at igi.tu-graz.ac.at (Wolfgang Maass) Date: Tue, 02 Dec 2003 17:16:27 +0100 Subject: jobs for Phd-students and Postdocs Message-ID: <3FCCBADB.5060701@igi.tu-graz.ac.at> Applications of PHD-STUDENTS and POSTDOCS for the following research project are encouraged, which will be supervised jointly by Nikos Logothetis (MPI for Biological Cybernetics, Tuebingen, Germany) and Wolfgang Maass (Institute for Theoretical Computer Science, Graz, Austria): MODELING BIOLOGICAL VISION This research project is part of a larger research project COGNITIVE VISION (encouraging interaction with researchers from computer vision) that is funded by the Austrian National Science Foundation (FWF). The goal of this research project is to integrate realistic data from in vivo experiments into computer models of parts of the visual system that are functional in the sense that they can solve complex computational tasks on visual input streams. This project involves methods and insight from both neuroscience (especially dynamics of neural circuits and systems in vivo, visual system of primates, computational neuroscience) and computer science (especially machine learning, computer vision, simulations of complex systems). Applicants are expected to have strong backgrounds in at least one of the research disciplines, and should have also demonstrated in their previous work interest and qualifications for interdisciplinary research. But the most important qualification is excellence in research. Applications, with all necessary background documents attached in pdf (or provided via URLs), should be sent by Dec. 17 to maass at igi.tugraz.at. Prof. Nikos Logothetis Max-Planck Institute for Biological Cybernetics Director; Physiology of Cognitive Processes Spemannstr. 38, D-72076 Tuebingen, Germany http://www.kyb.tuebingen.mpg.de/~nikos Prof. Wolfgang Maass Institut fuer Grundlagen der Informationsverarbeitung Technische Universitaet Graz Inffeldgasse 16b, A-8010 Graz, Austria http://www.igi.tugraz.at/maass From bogus@does.not.exist.com Wed Dec 3 11:03:21 2003 From: bogus@does.not.exist.com () Date: 03 Dec 2003 17:03:21 +0100 Subject: No subject Message-ID: <1070467400.19719.4.camel@horas.physik.uni-bremen.de> Dear Connectionnists, We would like to announce the paper "CODING WITH NOISY NEURONS: STABILITY OF TUNING CURVES DEPENDS STRONGLY ON THE ANALYSIS METHOD" by Axel Etzold, Helmut Schwegler, and Christian W. Eurich, to appear in the "Journal of Neuroscience Methods". A standard evaluation method for neural data is the construction of a neural tuning curves. However, the widely used statistical method of statistical analysis based on on the sample mean and least-squares approximation for the spike count can perform extremely badly if the noise distribution is not exactly normal, which is almost never the case in applications. Here we present a method for constructing neural tuning curves that is especially suited for cases of high noise and the presence of outliers. In contrast to traditional methods employing a point-by-point estimation of a tuning curve, we use all measured data from all different stimulus conditions at once in the construction. Using approximation theory, a tuning curve is identified which best approximates a hypothetical ideal tuning curve across all stimulus conditions. The influence of several types of noise distributions on the stability of the parameters of the tuning curve is investigated. A rank-weighted norm is employed which yields more stable tuning curves than the traditional least mean squares method and at the same time conserves information which would be discarded by a median based method. The theoretical results are applied to responses of cells in rat primary visual cortex. A preprint and additional software for MATLAB are available at http://www.neuro.uni-bremen.de/~web/index.php?id=54&link=/~noisy/noisytuning.html The Matlab package may be used by everyone to generate tuning curves automatically from empirical single-cell data. Best regards, Axel Etzold From mzib at ee.technion.ac.il Wed Dec 3 13:00:58 2003 From: mzib at ee.technion.ac.il (Michael Zibulevsky) Date: Wed, 3 Dec 2003 20:00:58 +0200 (IST) Subject: Matlab code is available: relative Newton method for blind source separation Message-ID: Dear friends, the Matlab code of the relative Newton method for blind source separation is available now. The method significantly outperforms natural gradient descent in batch mode. The structure of the corresponding Hessian matrix allows its fast inversion without assembling. Experiments with sparsely representable signals and images show super-efficient separation. The code is located at http://ie.technion.ac.il/~mcib/relnwt021203.zip Best Regards, Michael =========================================================================== Michael Zibulevsky, Ph.D. Email: mzib at ee.technion.ac.il Department of Electrical Engineering Phone: 972-4-829-4724 Technion - Israel Institute of Technology Haifa 32000, Israel http://ie.technion.ac.il/~mcib/ Fax: 972-4-829-4799 =========================================================================== From brody at cshl.org Thu Dec 4 00:26:49 2003 From: brody at cshl.org (Carlos Brody) Date: Thu, 4 Dec 2003 00:26:49 -0500 (EST) Subject: postdoctoral opening in computational olfaction Message-ID: <16334.50585.19559.191918@sonnabend.cshl.org> [Inquiries about this ad may also be directed to Zach Mainen, who will be giving a tutorial on "Neural Coding and the Olfactory System" at NIPS] Postdoctoral position available in computational olfaction: We are seeking highly qualified candidates with a quantitative background and some experience in neuroscience to participate in a combined computational/experimental project to elucidate the role of the rodent olfactory bulb in odor recognition. The succesful applicant will work mostly on the computational side of the project (Brody lab at CSHL: modeling, data analysis; we also collaborate with John Hopfield at Princeton). Work will be very close to, with possible participation in, the experimental side of the project (Mainen lab at CSHL: quantitative behavior, tetrode recordings from behaving rats, intrinsic optical imaging). If interested, please contact Carlos Brody (brody at cshl.edu), emailing a CV, a brief statement of research interests, and the names of two or more referees. Brody lab web site Mainen lab web site Selected references: Brody and Hopfield, Neuron 2003 Uchida and Mainen, Nature Neuroscience 2003 From schmidler at stat.duke.edu Thu Dec 4 09:37:00 2003 From: schmidler at stat.duke.edu (Scott Schmidler) Date: Thu, 4 Dec 2003 09:37:00 -0500 (EST) Subject: Faculty Postion at Duke University Message-ID: <200312041437.hB4Eb0Yd037309@stat.duke.edu> Duke University Medical Center Faculty Position in Computational Neurobiology Department of Biostatistics and Bioinformatics Department of Neurobiology www.cbcb.duke.edu www.neuro.duke.edu Applications are invited for a tenure-track faculty position at the level of Assistant Professor. We seek innovative investigators using state-of-the-art computational and theoretical approaches to address important questions in cellular neurobiology. Candidates must have a Ph.D., M.D. or equivalent degree and postdoctoral experience demonstrating outstanding achievement and substantial promise. Women and minority group members are encouraged to apply. Send a complete curriculum vitae, a brief statement of research interests and goals, and arrange to have three letters of reference sent, to: Computational Neurobiology Search c/o Dr. Thomas B. Kepler Center for Bioinformatics and Computational Biology Box 90090 Duke University Durham NC 27708 or kepler at duke.edu Duke University is an equal opportunity/Affirmative Action employer. ------------------------------------------------------------------------ Scott C. Schmidler Phone: (919) 684-8064 Assistant Professor Fax: (919) 684-8594 Statistics and Decision Sciences Email: schmidler at stat.duke.edu Duke University WWW: www.stat.duke.edu/~scs From kdharris at andromeda.rutgers.edu Thu Dec 4 18:50:03 2003 From: kdharris at andromeda.rutgers.edu (Ken Harris) Date: Thu, 4 Dec 2003 18:50:03 -0500 Subject: Postdoctoral Positions Message-ID: <005f01c3bac1$561691c0$7db5e6a5@limulus> Two postdoctoral positions, one experimental and one theoretical, are available in the Quantitative Neuroscience Laboratory at Rutgers University, to study the organization of cell assemblies in the auditory cortex of the rat. The theory of the "cell assembly" (Hebb, 1949) has been enormously influential in shaping theories of brain function over the last half century. However, only recently have developments in electrophysiology made it possible to record large enough numbers of neurons simultaneously to put this theory to the test experimentally. In recent work (Harris et al, Nature 2003), we employed a novel "peer prediction" method to characterize assembly activity in populations of simultaneously recorded hippocampal neurons. This method found that neurons are organized into groups showing coordinated activity beyond that predicted from spatial modulation of firing rate, with a synchronization timescale of approximately 25ms. However, several questions remain: is this process specific to hippocampus, or a more general aspect of cortical processing? And how does the timing of assembly activity relate to the temporal structure of a sensory stimulus? We are seeking two postdoctoral fellows to address these questions using large-scale parallel recordings in rat auditory cortex, under temporally controlled stimulus conditions. We seek: 1) An experienced electrophysiologist, to record from large neuronal populations using silicon microelectrodes in auditory cortex. Experience with extracellular recording is preferred. However, specific experience of silicon probes or the auditory system is not assumed. 2) A computational neuroscientist. While a knowledge of neuroscience and familiarity with statistical/machine learning techniques is preferred, prior experience with electrophysiological data is not assumed. This project will provide an exciting opportunity for experimental neuroscientists to learn the advanced data analysis methods that are becoming essential to modern electrophysiology, and for theorists to gain hands-on experience with real physiological data. Interested applicants should send a CV by email. ------------------------ Kenneth D. Harris, Ph.D. Assistant Professor Center for Molecular and Behavioral Neuroscience Rutgers, The State University of New Jersey 197 University Avenue Newark NJ 07102, USA phone: 973 353 1080, x3331 fax: 973 353 1272 email: kdharris at andromeda.rutgers.edu web: http://qneuro.rutgers.edu From mccallum at cs.umass.edu Fri Dec 5 08:56:22 2003 From: mccallum at cs.umass.edu (Andrew McCallum) Date: Fri, 5 Dec 2003 08:56:22 -0500 Subject: Postdoctoral position at UMass: ML and text Message-ID: The following postdoc position is available. If you are interested and are planning to attend the NIPS conference in Vancouver (Dec 9-13) please email me and we can arrange to meet there. Sincerely, Andrew McCallum ---------------------------------------------------------------------- Postdoctoral Fellowship Machine Learning, Natural Language Information Extraction and Data Mining Department of Computer Science University of Massachusetts Amherst http://www.cs.umass.edu The UMass CS department is looking for an exceptional postdoc to work in Machine Learning applied to Natural Language, Information Extraction and Data Mining. We are especially interested in people with expertise in statistical machine learning, graphical models, Bayesian methods, approximate inference, and kernel methods. Previous experience applying these techniques to problems in natural language is not necessary. This is an opportunity to exercise your machine-learning know-how on real data and real problems. UMass offers an attractive environment for research at the intersection of machine learning and textual information---with significant strength in information retrieval (Bruce Croft, James Allan, R. Manmatha), machine learning (Andy Barto, Sridhar Mahadevan, Paul Utgoff, David Jensen, Hava Seigelmann, David Kulp, Robbie Moll, Andy Fagg), their intersection (Andrew McCallum), and other related areas (Victor Lesser, Shlomo Zilberstein, Rod Grupen, Oliver Brock, Al Hansen, and others). We also have strong ties to our statistics department, and other nearby universities. We have large staff and computing infrastructure to support significant projects that will enable you to put a big feather in your cap. Ranked among the top six AI groups in the U.S., UMass has an exciting and highly collaborative CS department. UMass CS will continue to have a vibrant atmosphere, as we are expecting to hire 15 new faculty in the coming few years. Located in idyllic western New England, surrounded by five other colleges, UMass is also within day-trip range of both Boston and New York. The University of Massachusetts is an Affirmative Action/Equal Opportunity employer. Women and members of minority groups are encouraged to apply. http://www.cs.umass.edu/csinfo/join_fac_staff/joinfaculty.html. Prospective candidates should apply with a cover letter, CV, and names and email addresses of 2-3 referees. This should be sent by email to: jean at cs.umass.edu, preferably using plain text, Postscript or PDF formats only. From jst at ecs.soton.ac.uk Fri Dec 5 14:18:08 2003 From: jst at ecs.soton.ac.uk (John S Shawe-Taylor) Date: Fri, 5 Dec 2003 19:18:08 +0000 (GMT) Subject: Expanded Machine Learning Group and RA positions at Southampton Message-ID: The Machine Learning Group at the University of Southampton, England, is being expanded with the addition of three new members. From 1st February it will comprise: Steve Gunn, Manfred Opper, Adam Prugel-Bennett, Craig Saunders and John Shawe-Taylor It forms part of the Image, Speech and Intelligent Systems group headed by John Shawe-Taylor within the School of Electronics and Computer Science - see web page: http://www.isis.ecs.soton.ac.uk There are a number of RA positions being currently advertised (http://www.isis.ecs.soton.ac.uk/vacancies/). John, Steve and Manfred will all be attending NIPS and will happily discuss these openings with anyone interested. In addition (subject to the final green light from the EU) the group will be the coordinator of a new Network of Excellence, 'Pattern Analysis, Statistical Modelling and Computational Learning (PASCAL)', involving 56 partners from Europe and Australia. Information about the project and up-coming events will be advertised on the project website www.pascal-network.org. ---------------------------------------------- John Shawe-Taylor ISIS Group School of Electronics and Computer Science University of Southampton Southampton SO17 1BJ Tel: +44 23 8059 3021 Fax: +44 23 8059 4498 ---------------------------------------------- From smyth at ics.uci.edu Fri Dec 5 11:46:10 2003 From: smyth at ics.uci.edu (Padhraic Smyth) Date: Fri, 05 Dec 2003 08:46:10 -0800 Subject: faculty positions in computer science and statistics at UC Irvine Message-ID: <3FD0B652.9010403@ics.uci.edu> The Computer Science Department and the Statistics Department at UC Irvine are currently recruiting faculty in the areas of scientific computing and in statistics. Both departments are within the newly formed School of Information and Computer Science. The School and the University are growing rapidly and offer excellent opportunities for collaborative research. Current faculty in machine learning, AI, and statistics include Pierre Baldi, Rina Dechter, David Van Dyk, Dennis Kibler, Rick Lathrop, Eric Mjolsness, Michael Pazzani, Padhraic Smyth, Hal Stern, and Max Welling. Several of us will be attending the NIPS conference this coming week in Vancouver and would be happy to talk to candidates who are potentially interested in applying. More details on the positions are included below, with pointers to the relevant Web pages for application information. SCIENTIFIC COMPUTING FACULTY POSITION: The Department of Computer Science at UC Irvine is recruiting a tenure-track assistant professor with expertise in scientific computing. Scientific computing is interpreted broadly to include areas such as scientific and engineering numerical computing, numerical analysis, symbolic algebra, multi-scale and adaptive grid simulation, statistics and operations research, computational science, computer graphics and visualization, high performance computer architectures (vector, parallel and distributed), scientific knowledge representation, and scientific databases (this list is not exhaustive). The selected candidate will find opportunities for synergistic interactions within the School of Information and Computer Science with colleagues in areas such as statistics, machine learning, artificial intelligence, computer science theory, graphics and visualization, databases, as well as with faculty in the sciences in other schools at UCI, in areas such as biology, chemistry, earth sciences, social ecology, and cognitive science. Further information on applying is available at http://www.ics.uci.edu/about/jobs/#scientific_computing STATISTICS FACULTY POSITIONS: The Department of Statistics(http://www.stat.uci.edu/) at the University of California, Irvine (UCI), is recruiting three faculty positions in 2003-04: one with tenure and two tenure-track assistant professorships. We anticipate growing to a full-time faculty in statistics of 6-8 people over the next several years, with several more half-time appointments shared with other units at UCI. It will be a department with a strongly interdisciplinary flavor, focused both on developing methods to solve applied problems and the statistical theory that underlies those methods. The Department is interested in individuals with research interests in all areas of statistics at the present time including computational statistics, bioinformatics and genomic statistics, social science statistics, and mathematical statistics. Further information on applying is available at http://www.ics.uci.edu/about/jobs/statsfaculty.php From fyfe-ci0 at wpmail.paisley.ac.uk Sun Dec 7 06:46:44 2003 From: fyfe-ci0 at wpmail.paisley.ac.uk (Colin Fyfe) Date: Sun, 07 Dec 2003 11:46:44 +0000 Subject: PhD Studentship in Computational Intelligence. Message-ID: PhD Studentship in Computational Intelligence. A funded research studentship is available under the supervision of Professor Colin Fyfe at the University of Paisley, Scotland. The studentship is awarded for 3 years with a stipend of*9000 per annum + fees paid. The topic is the use of techniques from Computational Intelligence to make AI play in computer games truly adaptive and intelligent. The techniques used will include artificial neural networks, evolutionary algorithms, swarm methods and artificial immune systems. Applicants should have a good first degree in a numerate discipline. The studentship is expected to lead to the award of PhD. Recent PhDs successfully supervised by Prof Fyfe have been Prof. Mark Girolami , 1998 :Independent Component Analysis Dr. Darryl Charles , 1999 : factor analysis Prof. Juan Corchado , 1999 : case based reasoning, hybrid systems Dr. Stephen McGlinchey, 2000 : topology preserving maps Dr. Pei Ling Lai , 2000 : canonical correlation analysis Dr. Shang-Jen (David) Chuang , 2001 : forecasting Dr. Donald MacDonald, 2001 : Remote sensed image analysis Dr Emilio Corchado, (Universidad de Salamanca), 2002 : Maximum/Minimum Likelihood Hebbian learning Dr Tzai-Der (Douglas) Wang, 2002: evolution of cooperation Dr ZhenKun Gou, 2003: canonical correlation analysis Dr Jos Koetsier, 2003: context assisted learning Dr Danny Livingstone, 2003: evolution of languages The studentship will start as soon as possible. Interested applicants should send a CV to Colin Fyfe at colin.fyfe at paisley.ac.uk by 5th January 2004. 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If you received this in error, please contact the sender immediately and delete the material from any computer. -------------------------- From pollack at cs.brandeis.edu Mon Dec 8 14:31:50 2003 From: pollack at cs.brandeis.edu (Jordan Pollack) Date: Mon, 08 Dec 2003 14:31:50 -0500 Subject: neural nets and Artificial Life Message-ID: <3FD4D1A6.4090806@cs.brandeis.edu> I am chairing the Ninth International Artificial Life Conference, and we are interested in attracting people who are evolving neural networks, developing theories of brain evolution, language evolution, mind/brain co-evolution, which should be of interests to people in Neural Nets. We are also seeking Neuroscience related papers such as scale-free networks, neutral networks, gene regulatory and developmental networks. Alife9 will be in downtown Boston, September 12-15th 2004. The deadline is 30 January 2004, and MIT Press is publishing. The full CFP is available at http://www.alife9.org Regards to my many friends on Connectionists... Jordan Pollack From bower at uthscsa.edu Mon Dec 8 16:41:49 2003 From: bower at uthscsa.edu (james Bower) Date: Mon, 08 Dec 2003 15:41:49 -0600 Subject: Three Positions in Animal Imaging Message-ID: The Neuroscience Research Group at the Research Imaging Center within The University of Texas Health Science Center - San Antonio Seeks Applicants at the Assistant, Associate, or Full Professor level in Animal Imaging (broadly defined). The Research Imaging Center (RIC) at the University of Texas Health Science Center at San Antonio (UTHSCSA) seeks applicants for faculty positions in its Animal Imaging Division. The RIC is a department-level component of the UTHSCSA School of Medicine and specializes in the application of imaging techniques to human and animal neuroscience. Translational imaging research (complementary use of human and animal models) integrated application of multiple imaging techniques and use of computational models in imaging research are areas of focus. Techniques currently supported for animal imaging include PET, anatomical and functional MRI, MRS, multi-unit electrode recording, and optical reflectance imaging. Techniques currently supported for human imaging include PET, anatomical and functional MRI, MRS, ERPs, and TMS. The Animal Imaging Division seeks a minimum of 3 full-time faculty with diverse backgrounds (e.g. one in MRI, one in PET, one in imaging related electrophysiology) and experience in inter-disciplinary collaborations. One of these positions will be the Chief of the Animal Imaging Division. The Division Chief will assume oversight of a Concord MicroPET, and two MRI/MRS systems: a 4.7T horizontal bore system, and a 7.0T vertical bore system. All three imaging systems are housed within an animal facility immediately adjacent to the RIC's other imaging systems, laboratories, and offices. Send Resume and cover letter to: Peter Fox M.D., Professor and Director, Research Imaging Center, the University of Texas Health Science Center, 7703 Floyd Curl Drive, San Antonio, Texas 78229-3900 The University of Texas Health Science Center San Antonio is an Equal Employment Opportunity/Affirmative Action Employer. All faculty appointments are designated as security sensitive positions. -- James M. Bower Ph.D. Research Imaging Center University of Texas Health Science Center at San Antonio 7703 Floyd Curl Drive San Antonio, TX 78284-6240 Cajal Neuroscience Center University of Texas San Antonio Phone: 210 567 8080 Fax: 210 567 8152 From E.Koning at elsevier.nl Tue Dec 9 02:58:47 2003 From: E.Koning at elsevier.nl (Koning, Esther (ELS)) Date: Tue, 9 Dec 2003 07:58:47 -0000 Subject: CFP - Neurocomputing: Geometrical Methods in Neural Networks and Learning Message-ID: <06372B4E0B1E7D4FAAD2B63276D87002029B447C@elsamsvexch01.elsevier.nl> CALL FOR PAPERS NEUROCOMPUTING - An International Journal Editor-in-Chief: Tom Heskes Journal published by Elsevier Science B.V. - URL: http://www.elsevier.com/locate/neucom Special Issue on "Geometrical Methods in Neural Networks and Learning" Understanding the underlying geometric structure of a network's parameter space is extremely important to designing systems that can effectively navigate the space while learning. Although modern mathematics is needed in the research of neural networks, and there are some very powerful results and techniques in these geometric methods, these are currently scattered in various sources. Over the last decade or so, driven greatly by the work on information geometry, we are seeing the merging of the fields of statistics and geometry applied to neural network and learning. This requires intense collaboration and communication. The interest displayed by the scientific community into these research topics is also testified by several activities such as the special issue on "Non-Gradient Learning Techniques" of the International Journal of Neural Systems (guest editors A. de Carvalho and S.C. Kremer), the Post-NIPS*2000 workshop on "Geometric and Quantum Methods in Learning", organized by S.-i. Amari, A. Assadi and T. Poggio (Colorado, December 2000), the workshop "Uncertainty in geometric computations" held in Sheffield, England, in July 2001, organized by J. Winkler and M. Niranjan (University of Sheffield, UK), the special session of the IJCNN'02 on "Differential & Computational Geometry in Neural Networks" (session chair: E. Bayro-Corrochano, CINVESTAV, Guadalajara, Mexico) held in Honolulu, Hawaii (USA), in May 2002, and the workshop "Information Geometry and its Applications", held in Pescara (Italy), in July 2002, organized by P. Giblisco. For these reasons, the Neurocomputing journal dedicates a Special Issue to the theory and advanced applications of geometric concepts to neural learning and optimization, bringing together contributions well founded in modern mathematics. The topics of the Special Issue are the theoretical and practical aspects of geometrical methods for the design of neural networks making emphasis in geometric learning and optimization. The readers will have for the first time a collection of approaches including differential geometrical methods for learning, the Lie group learning algorithms, the natural (Riemannian) gradient techniques, learning by weight flows on Stiefel-Grassman manifolds, the theories for learning on orthogonal group, neurocomputing using Clifford geometric algebra, the numerical aspects of the solution of the matrix-equations on Lie groups arising in neural learning/optimization and related topics. The Neurocomputing journal invites original contributions for the forthcoming Special Issue on Geometrical Methods in Neural Networks and Learning from a broad scope of areas. Some topics relevant to this special issue include, but are not restricted to: - Neural principal component/subspace analysis; - Neural independent component analysis and blind source separation; - Natural computing (geometrical algorithms that could take place in neural circuitry); - Selection of subspaces for optimal neural data compression; - Neural optimization over the orthogonal group and optimization problems in tensor algebra; - Information geometry; - Provably convergent geometric algorithms for real-time learning; - Geometry of boosting methods; - Geometric Clifford algebra for the generalization of neural networks; - Geometrical methods of unsupervised learning for blind signal processing; - Application of Lie operators and use of differential geometry based learning techniques; - Conformal and horosphere models for neurocomputing; - Tensorial approach for geometrical neural computation and learning; - General graphical model and belief propagation for machine learning; - Geometry of statistical-physical methods for learning. Please submit the electronic copy to http://authors.elsevier.com/journal/neucom including abstract, keywords, a cover page containing the title and Author(s) name(s), corresponding Author's complete address including fax and EMail address, and clear indication to be a submission to the Special Issue on Geometrical Methods in Neural Networks and Learning. -- Scheduling of the Special Issue: Deadline for papers submission: March 1, 2004 End of refereeing process and result issuing: July 30, 2004 Submission of the final manuscript: September 30, 2004 Guest Editors: Simone Fiori Faculty of Engineering, University of Perugia Polo Didattico e Scientifico del Ternano Loc. Pentima bassa, 21, I-05100 Terni (Italy) Fax: +39.0744.492925 EMail: fiori at unipg.it URL: http://www.unipg.it/sfr/ Shun-ichi Amari RIKEN Brain Science Institute Laboratory for Mathematical Neuroscience Wako-shi Hirosawa 2-1, Saitama 351-0198 (Japan) Fax: +81.48467.9687 EMail: amari at brain.riken.go.jp URL: http://www.bsis.brain.riken.go.jp/ From A.Sharkey at dcs.shef.ac.uk Tue Dec 9 10:05:36 2003 From: A.Sharkey at dcs.shef.ac.uk (Amanda Sharkey) Date: Tue, 9 Dec 2003 15:05:36 +0000 (GMT) Subject: Connection Science journal - some changes Message-ID: The editors of Connection Science would like to draw your attention to the revised aims and scope for the journal. Connection Science: A journal of adaptation, neural computing, artificial intelligence and cognition. Connection Science is an interdisciplinary scientific journal with a focus on the mechanisms of adaptation, cognition and intelligent behaviour in both living and artificial systems. The traditional scope of the journal has been broadened from connectionist research and neural computing to encompass work on other adaptive methods (e.g. evolutionary computing) as well as biologically inspired techniques and algorithms in applied domains. Papers should still be related to either the behaviour of humans or other animals or to the underlying mechanisms. Papers submitted to the journal may be practical implementations, theoretical research or philosophical discussions. The submission of robotics research papers on issues raised by the interaction of agents with the environment or with other agents is particularly encouraged. Editor in Chief: Noel Sharkey Editors: Tom Ziemke and Amanda Sharkey http://www.tandf.co.uk/journals From bogus@does.not.exist.com Tue Dec 9 08:33:04 2003 From: bogus@does.not.exist.com () Date: Tue, 9 Dec 2003 21:33:04 +0800 Subject: 5 papers for comments Message-ID: <9CFE75F87A78564887952466CA3F4E4D03713E90@exchange02.staff.main.ntu.edu.sg> From cns at cns.bu.edu Tue Dec 9 10:17:57 2003 From: cns at cns.bu.edu (BU CNS Department) Date: Tue, 09 Dec 2003 10:17:57 -0500 Subject: GRADUATE TRAINING IN THE DEPARTMENT OF COGNITIVE AND NEURAL SYSTEMS (CNS) AT BOSTON UNIVERSITY Message-ID: <3FD5E7A5.9080702@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 2004 admission and financial aid are now being accepted for PhD, MA, and BA/MA degree programs. To obtain a brochure describing CNS programs 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) general test scores. 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. CNS is a world leader 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 producing 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 academic and research advisors. 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 carry out 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, 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 unites 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, and technology), 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 RESEARCH 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 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 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, vision, synaptic processes, pattern recognition, remote sensing, medical database analysis, machine learning, differential equations 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 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 Diego Visual word recognition, psycholinguistics, cognitive semantics, second language acquisition, computational models of cognition Michael E. Hasselmo Associate Professor of Psychology Director of Graduate Studies, Department of Psychology 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 VLSI circuit design: digital, analog, subthreshold analog, biCMOS, CMOS; information processing in neurons, neural net chips, synthetic aperture radar (SAR) processing chips, sonar processing chips; auditory models and experiments 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 Siegfried Martens Research Associate, Department of Cognitive and Neural Systems PhD, Cognitive and Neural Systems, Boston University Learning models, pattern recognition, visualization, remote sensing, sensor fusion 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 Bradley Rhodes Research Associate, Department of Cognitive and Neural Systems PhD, Cognitive and Neural Systems, Boston University Motor control, learning, and adaptation, serial order behavior (timing in particular), attention and memory Michele Rucci Assistant Professor of Cognitive and Neural Systems PhD, Scuola Superiore S.-Anna, Pisa, Italy Vision, sensory-motor control and learning, and computational neuroscience 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 Associate 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 Timothy Streeter Research Associate, Department of Cognitive and Neural Systems MS, Physics, University of New Hampshire MA, Cognitive and Neural Systems, Boston University Spatial auditory perception, perceptual adaptation 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) Jeremy Wolfe Adjunct 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 Perception 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, 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 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. Auditory Neuroscience Laboratory The Auditory Neuroscience 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 Auditory Neuroscience Laboratory consists of three adjacent rooms in the basement of 677 Beacon Steet (the home of the CNS Department). One room houses an 8 ft. ? 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. 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; 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. 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 Lab was established in July 2001, with a grant from the Air Force Office of Scientific Research: "Information Fusion for Image Analysis: Neural Models and Technology Development." Initial projects have focused on multi-level fusion and data mining in a geospatial context, in collaboration with the Boston University Center for Remote Sensing. This research and development have built on models of opponent-color visual processing, boundary contour system (BCS) and texture processing, and Adaptive Resonance Theory (ART) pattern learning and recognition, as well as other models of associative learning and prediction. Other projects include collaborations with the New England Medical Center and Boston Medical Center, to develop methods for analysis of large-scale medical databases, currently to predict HIV resistance to antiretroviral therapy. Associated basic research projects are conducted within the joint context of scientific data and technological constraints. 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://cns.bu.edu/ ******************************************************************* From h.jaeger at iu-bremen.de Thu Dec 11 14:38:20 2003 From: h.jaeger at iu-bremen.de (Herbert Jaeger) Date: Thu, 11 Dec 2003 20:38:20 +0100 Subject: CFP: Interdisciplinary College 2004 Message-ID: <3FD8C7AC.9030005@iu-bremen.de> Announcing the Interdisciplinary College 2004 (IK 04) Time: March 5 - 12, 2004 Location: Guenne, a charming out-of-the-world village at the border of lake Moehnesee in central Germany. Website: www.ik2004.de What is IK? The Interdisciplinary College (Interdisziplinaeres Kolleg, IK) is an annual one-week spring school on all brain & intelligence related sciences. It offers a dense, state-of-the-art course program in neurobiology, neural computation, cognitive science and artificial intelligence. It is aimed at students, postgraduates and researchers from academia and industry. By combining humanities, science and technology, the IK endeavours to intensify dialogue and connectedness across the various disciplines. The IK has a long tradition (see website); in its current form it has been organized annually since 1999. All courses are taught in English. The IK 2004 Each IK has a special focus theme. About 30-40 percent of the courses are dedicated to aspects of this theme, which at IK-04 is "body and motion". It is reflected in a number of courses that deal with the following topics: - mathematical modelling of complex dynamical systems - disorders in the human motor system - perception and action in cognitive science - neural networks in motor control - motion planning in robots - navigation strategies in insects and robots - cognitive and neuronal representation of motion patterns - development of motor skills in infants - analysis of motion patterns in sports - didactical use of dance, singing, and motion in language teaching - philosophy of embodied cognition For more detailed information about program, history, conference site, organizers, and registration, please consult www.ik2004.de. ------------------------------------------------------------------ Dr. Herbert Jaeger Professor for Computational Science International University Bremen Campus Ring 12 28759 Bremen, Germany Phone (+49) 421 200 3215 email h.jaeger at iu-bremen.de http://www.iu-bremen.de/directory/faculty/29979/ http://www.ais.fraunhofer.de/INDY/herbert/ ------------------------------------------------------------------ From cindy at bu.edu Mon Dec 15 10:47:39 2003 From: cindy at bu.edu (Cynthia Bradford) Date: Mon, 15 Dec 2003 10:47:39 -0500 Subject: Neural Networks 17(1) Message-ID: <00f101c3c322$c5c8ee50$903dc580@cnspc31> NEURAL NETWORKS 17(1) Contents - Volume 17, Number 1 - 2004 ------------------------------------------------------------------ EDITORIAL: Another exciting year for the INNS/ENNS/JNNS Journal! NEURAL NETWORKS REFEREES USED IN 2003 ***** Neuroscience and Neuropsychology ***** "Self-organizing continuous attractor networks with multiple activity packets and the representation of space" S.M. Stringer, E.T. Rolls, and T.P. Trappenberg ***** Mathematical and Computational Analysis ***** "Combining Hebbian and reinforcement learning in a minibrain model" R.J.C. Bosman, W.A. van Leeuwen, and B. Wemmenhove "Neocognitron capable of incremental learning" Kunihiko Fukushima "Global asymptotic stability of Hopfield neural network involving distributed delays" Hongyong Zhao "Associative memory by recurrent neural networks with delay elements" Seiji Miyoshi, Hiro-Fumi Yanai, and Masato Okada "Steepest descent with momentum for quadratic functions is a version of the conjugate gradient method" Amit Bhaya and Eugenius Kaszkurewicz "A comparative study of two modeling approaches in neural networks" Zong-Ben Xu, Hong Qiao, Jigen Peng, and Bo Zhang "Dynamics of periodic delayed neural networks" Jin Zhou, Zengroung Liu, and Guanrong Chen "Mixed states on neural network with structural learning" Tomoyuki Kimoto and Masato Okada "Practical selection of SVM parameters and noise estimation for SVM regression" Vladimir Cherkassky and Yunqian Ma "Experimentally optimal nu in support vector regression for different noise models and parameter settings" Athanassia Chalimourda, Bernhard Scholkopf, and Alex J. Smola "Discrimination networks for maximum selection" Brijnesh J. Jain and Fritz Wysotzki CURRENT EVENTS ------------------------------------------------------------------ Electronic access: www.elsevier.com/locate/neunet/. Individuals can look up instructions, aims & scope, see news, tables of contents, etc. Those who are at institutions which subscribe to Neural Networks get access to full article text as part of the institutional subscription. Sample copies can be requested for free and back issues can be ordered through the Elsevier customer support offices: nlinfo-f at elsevier.nl usinfo-f at elsevier.com or info at elsevier.co.jp ------------------------------ INNS/ENNS/JNNS Membership includes a subscription to Neural Networks: The International (INNS), European (ENNS), and Japanese (JNNS) Neural Network Societies are associations of scientists, engineers, students, and others seeking to learn about and advance the understanding of the modeling of behavioral and brain processes, and the application of neural modeling concepts to technological problems. Membership in any of the societies includes a subscription to Neural Networks, the official journal of the societies. Application forms should be sent to all the societies you want to apply to (for example, one as a member with subscription and the other one or two as a member without subscription). The JNNS does not accept credit cards or checks; to apply to the JNNS, send in the application form and wait for instructions about remitting payment. The ENNS accepts bank orders in Swedish Crowns (SEK) or credit cards. The INNS does not invoice for payment. ---------------------------------------------------------------------------- Membership Type INNS ENNS JNNS ---------------------------------------------------------------------------- membership with $80 (regular) SEK 660 Y 13,000 Neural Networks (plus Y 2,000 enrollment fee) $20 (student) SEK 460 Y 11,000 (plus Y 2,000 enrollment fee) ---------------------------------------------------------------------------- membership without $30 SEK 200 not available to Neural Networks non-students (subscribe through another society) Y 5,000 student (plus Y 2,000 enrollment fee) ---------------------------------------------------------------------------- Name: _____________________________________ Title: _____________________________________ Address: _____________________________________ _____________________________________ _____________________________________ Phone: _____________________________________ Fax: _____________________________________ Email: _____________________________________ Payment: [ ] Check or money order enclosed, payable to INNS or ENNS OR [ ] Charge my VISA or MasterCard card number ____________________________ expiration date ________________________ INNS Membership 19 Mantua Road Mount Royal NJ 08061 USA 856 423 0162 (phone) 856 423 3420 (fax) innshq at talley.com http://www.inns.org ENNS Membership University of Skovde P.O. Box 408 531 28 Skovde Sweden 46 500 44 83 37 (phone) 46 500 44 83 99 (fax) enns at ida.his.se http://www.his.se/ida/enns JNNS Membership c/o Professor Shozo Yasui Kyushu Institute of Technology Graduate School of Life Science and Engineering 2-4 Hibikino, Wakamatsu-ku Kitakyushu 808-0196 Japan 81 93 695 6108 (phone and fax) jnns at brain.kyutech.ac.jp http://www.jnns.org/ ---------------------------------------------------------------------------- From terry at salk.edu Tue Dec 16 19:08:54 2003 From: terry at salk.edu (Terry Sejnowski) Date: Tue, 16 Dec 2003 16:08:54 -0800 (PST) Subject: NEURAL COMPUTATION 16:1 Message-ID: <200312170008.hBH08sQ59057@purkinje.salk.edu> Neural Computation - Contents - Volume 16, Number 1 - January 1, 2004 ARTICLE Bayesian Computation in Recurrent Neural Circuits Rajesh P. N. Rao LETTERS Probability of Stimulus Detection in a Model Population of Rapidly Adapting Fibers Burak Guclu and Stanley J. Bolanowski A Machine Learning Method for Extracting Symbolic Knowledge from Recurrent Neural Networks A Vahed and C. W. Omlin Orthogonality of Decision Boundaries in Complex-Valued Neural Networks Tohru Nitta On the Asymptotic Distribution of the Least-Squares Estimators in Unidentifiable Models Taichi Hayasaka, Masashi Kitahara and Shiro Usui Asymptotic Properties of the Fisher Kernel Koji Tsuda, Shotaro Akaho, Motoaki Kawanabe and Klaus-Robert Mueller Adaptive Hybrid Learning for Neural Networks Rob Smithies, Said Salhi and Nat Queen Divergence Function, Duality, and Convex Analysis Jun Zhang Linear Response Algorithms for Approximate Inference in Graphical Models Max Welling and Yee Whye Teh ----- 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 Jean-Arcady.Meyer at lip6.fr Wed Dec 17 11:45:17 2003 From: Jean-Arcady.Meyer at lip6.fr (Jean-Arcady Meyer) Date: Wed, 17 Dec 2003 17:45:17 +0100 Subject: Tenure positions at CNRS - Research on animats and robots Message-ID: <00cf01c3c4bd$2c7ae360$41cde384@lip6.fr> In 2004, the French CNRS recruits about 320 tenured scientists: http://www.sg.cnrs.fr/drhchercheurs/concoursch/indexen.html In particular, there are opportunities for=20 * 1 position CR2 (junior research scientist, born in 1971 or after, monthly salary between 1570=88 and 2010=88), in section 07 (competition number 05) in the field of "Simulation and modeling in signal processing and robotics for cognitive sciences". * 2 positions CR1 (experienced research scientist, no age limit, monthly salary between 1650=88 and 2950=88), in section 45 (competition number 02) in the field of "Cognition, language, signal processing: natural and artificial systems" People willing to participate in the corresponding competitive recruitment must send application files before January 16, 2004 to the CNRS. See details in the CNRS site: http://www.sg.cnrs.fr/drhchercheurs/concoursch/indexen.html http://www.sg.cnrs.fr/drhchercheurs/concoursch/pdf/CR2.pdf http://www.sg.cnrs.fr/drhchercheurs/concoursch/pdf/n_cr2.pdf http://www.sg.cnrs.fr/drhchercheurs/concoursch/pdf/CR1.pdf http://www.sg.cnrs.fr/drhchercheurs/concoursch/pdf/n_cr1.pdf People wishing to be specifically recruited within the AnimatLab in Paris (http://animatlab.lip6.fr ) in order to contribute to the research on animats that is done there, should contact Dr. Jean-Arcady Meyer (jean-arcady.meyer at lip6.fr).=20 From nk at cs.aue.auc.dk Thu Dec 18 11:41:20 2003 From: nk at cs.aue.auc.dk (Norbert Kruger) Date: Thu, 18 Dec 2003 17:41:20 +0100 Subject: Workshop on Coding of Visual Information in the Brain Message-ID: <3FE1D8B0.6060605@cs.aue.auc.dk> Workshop on Coding of Visual Information in the Brain June 1, 2004, Isle of Skye, Scotland Satellite event of the Early Cognitive Vision Workshop (28.5.-1.6.2004) http://www.cn.stir.ac.uk/ecovision-ws/ Call for Contributions How is visual Information coded in the human brain? How are statistical properties of natural images related to the internal representations/coding? What is the prior knowledge the human visual system is equipped with? In what sense does the actual task influence the internal state? What is the goal of the early visual processes and how can we achieve integration? What is the functional role of the temporal structure of neural firing patterns? These questions are relevant for research concerning the modelling of biological visual systems as well as building artificial systems. The workshop 'Coding of Visual Information in the Brain' has the aim to bring together scientists involved in neurophysiology, psychology and computer vision to discuss these issues under a multi-disciplinary perspective. As well as the contributed talks and posters, a number of leading scientists with strong interest in bridging the gap between human and artificial vision will be giving invited talks. The workshop will follow the tradition of the 'Information Theory and the Brain' workshops held in Stirling 1995 and in Newquay 1997. However, in contrast to its predecessors it is more focussed on vision. The workshop will be organised as a satellite event of the Early Cognitive Vision Workshop that will be held from May 28 to June 1 2004 (see http://www.cn.stir.ac.uk/ecovision-ws/). Please submit a one-page abstract, preferably by email to Peter Hancock (pjbh1 at psych.stir.ac.uk) or Norbert Krueger (nk at cs.aue.auc.dk) by 23.1.2004. Organising Committee Peter Hancock (Stirling, Scotland) Norbert Krueger (Esbjerg, Denmark) Florentin Woergoetter (Stirling, Scotland) Roland Baddeley (Sussex, England) Laurenz Wiskott (Berlin, Germany) James Elder (York, Canada) Invited Speakers James Elder (York, Canada) Christoph von der Malsburg (Bochum, Germany) Guy Orban (Brussel, Belgium) Roger Watt (Stirling, Scotland) From arno at salk.edu Wed Dec 17 11:11:45 2003 From: arno at salk.edu (Arnaud Delorme) Date: Wed, 17 Dec 2003 08:11:45 -0800 Subject: Orientation selectivity using fast feed-forward inhibition: paper and Neuron simulation files Message-ID: <3FE08041.1030708@salk.edu> The following article Delorme, A. (2003) Early Cortical Orientation Selectivity: How Fast Shunting Inhibition Decodes the Order of Spike Latencies. /Journal of Computational Neuroscience/, 15, 357-365. Author's PDF , journal's link . and the associated Neuron simulation files (documented) are available at http://www.sccn.ucsd.edu/~arno/model.html --------------------------- Article abstract: Following a flashed stimulus, I show that a simple neurophysiological mechanism in the primary visual system can generate orientation selectivity based on the first incoming spikes. A biological model of the lateral geniculate nucleus generates an asynchronous wave of spikes, with the most strongly activated neurons firing first. Geniculate activation leads to both the direct excitation of a cortical pyramidal cell and disynaptic feed-forward inhibition. The mechanism provides automatic gain control, so the cortical neurons respond over a wide range of stimulus contrasts. It also demonstrates the biological plausibility of a new computationally efficient neural code: latency rank order coding. -- *Arnaud Delorme, Ph.D.* Computational Neurobiology Lab, Salk Institute 10010 North Torrey Pines Road La Jolla, CA 92037 USA *Tel* : /(+1)-858-458-1927 ext 15/ *Fax* : /(+1)-858-458-1847/ *Web page *: www.sccn.ucsd.edu/~arno *To think upon*: The longing to produce great inspirations didn't produce anything but more longing. /Sophie Kerr/ From cindy at bu.edu Wed Dec 17 09:28:38 2003 From: cindy at bu.edu (Cynthia Bradford) Date: Wed, 17 Dec 2003 09:28:38 -0500 Subject: 8th ICCNS: Final Call for Abstracts Message-ID: <000001c3c4aa$0f9986b0$903dc580@cnspc31> Apologies if you receive more than one copy of this email. ***** FINAL CALL FOR ABSTRACTS ***** Submission Deadline: January 30, 2004 EIGHTH INTERNATIONAL CONFERENCE ON COGNITIVE AND NEURAL SYSTEMS May 19-22, 2004 http://cns.bu.edu/meetings/ Boston University 677 Beacon Street Boston, Massachusetts 02215 Sponsored by Boston University's Center for Adaptive Systems and Department of Cognitive and Neural Systems with financial support from the Office of Naval Research CONFIRMED SPEAKERS: Tutorial Lecture Series: Stephen Grossberg Keynote Lectures: John Anderson and Miguel Nicolelis Invited Speakers: Ehud Ahissar, Alan D. Baddeley, Moshe Bar, Gail A. Carpenter, Stephen Goldinger, Daniel Kersten, Stephen M. Kosslyn, Tai-Sing Lee, Eve Marder, Bartlett W. Mel, Jeffrey D. Schall, Chantal Stern, Mriganka Sur, Joseph Z. Tsien, William H. Warren Jr., Jeremy Wolfe. Please visit the web site for conference details, including: --the abstract submission guidelines for contributed lectures and posters --the registration form --a schedule of the confirmed speakers and their lecture titles --information about graduate student and postdoctoral travel fellowships --local lodging options From golden at utdallas.edu Fri Dec 19 08:49:44 2003 From: golden at utdallas.edu (Richard Golden) Date: Fri, 19 Dec 2003 07:49:44 -0600 (CST) Subject: Math Psych Meeting Announcements! Message-ID: Please post this announcement to your mailing list. Thanks! Richard Golden ================================================================== The 37th Meeting of the Society for Mathematical Psychology will be held at the University of Michigan (July 29, 2004 through August 1, 2004). Professor Shun-ichi Amari (Riken Brain Science Institute, Japan) [Co-Editor In Chief of the Journal "Neural Networks"] will be giving a plenary talk! The Tutorial workshop will begin at 8:30am on July 29, 2004 and is entitled "Differential Geometry with Applications to Measurement and Statistics". In mid-January 2004 you should be receiving a packet of materials if you are a current member in good standing in the Society for Mathematical Psychology. Most of these materials as well as more detailed information about the conference and the workshop may be found as: http://www.cogs.indiana.edu/socmathpsych Thanks, Richard Golden Secretary-Treasurer, SMP From editors at jmlg.org Fri Dec 19 13:45:02 2003 From: editors at jmlg.org (editors@jmlg.org) Date: Fri, 19 Dec 2003 13:45:02 -0500 Subject: Journal of Machine Learning Gossip Message-ID: Dear connectionists, On the occasion of the final NIPS paper submission, the Journal of Machine Learning Gossip (http://www.jmlg.org) would like to offer its services to the machine learning community. At http://www.jmlg.org/software/pssq-page.htm you can download the most recent tool from our Extreme Programming Team which allows to (font) compress any paper to any number of pages with little visual difference. No warranty is provided whatsoever and no liability is accepted for the use of this program. If your paper gets rejected because you squished it too much then you work shorter hours, produce less and write genuinely shorter papers. You have been warned. Note that at http://www.jmlg.org you can find also information on other aspects of academic life in the machine learning community and more useful tools. Best regards Editors of www.jmlg.org From mvanross at inf.ed.ac.uk Sun Dec 21 07:28:45 2003 From: mvanross at inf.ed.ac.uk (Mark van Rossum) Date: Sun, 21 Dec 2003 12:28:45 +0000 (GMT) Subject: 4-Year Doctoral Training (Ph.D.) Neuroinformatics in Edinburgh Message-ID: 4-Year Doctoral Training (Ph.D.) Neuroinformatics We invite applications for the EPSRC/MRC funded Ph.D. programme to the Neuroinformatics Doctoral Training Centre at the University of Edinburgh. The programme is made up of 3 themes: 1) Computational and Cognitive Neuroscience - analytical, computational and experimental study of information processing in the nervous system. 2) Neuromorphic Engineering and Robotics - Artificial sensor perception and analysis, neuromorphic modelling, mixed-mode VLSI and spiking computation, neurorobotics. 3) Simulation, Analysis, Visualisation and Data Handling - software systems and computational techniques for neuroscience and neural engineering. The 4-year programme in Neuroinformatics, established in 2002, consists of an introductory year with training in neuroscience, informatics and lab-based research projects, followed by 3 years of Ph.D. research related to one of the above subjects. The programme has a strong interdisciplinary character and is ideal for students who want to apply their skills to neuroinformatics problems. Students with a strong background in computer science, mathematics, physics or engineering are particularly welcome to apply, but motivated students with other backgrounds will also be considered. We will be accepting an average of 10 students per year. Students will be attached initially to the Institute for Adaptive and Neural Computation in the School of Informatics, the UK's largest and highest-quality academic computer-science group. The Ph.D. project can be done in collaboration with many affiliated institutes. Edinburgh has a strong research community in all of the areas listed above and leads the UK in integrating these into a coherent programme in neuroinformatics. Edinburgh has been voted as 'best place to live in Britain', and has many exciting cultural and student activities. The stipend is set in the region of 10,000 pounds in the first year and 13,000 pounds per annum in years 2-4. Studentships cover full tuition fees and research and training costs. Full studentships are available to UK students only. Partial funding is available for EU students. Applicants who are not citizens or longstanding residents of the EU will need to find their own funding. For full application details and further information please consult the website: http://www.anc.ed.ac.uk/neuroinformatics. Applications are welcome at any time; those received by March 15th 2004 will receive priority treatment. From cns at cnsorg.org Mon Dec 22 14:43:15 2003 From: cns at cnsorg.org (CNS - Organization for Computational Neurosciences) Date: Mon, 22 Dec 2003 11:43:15 -0800 Subject: REMINDER: CNS*2004 Deadline submission coming up! Message-ID: <1072122195.3fe749536591b@webmail.mydomain.com> REMINDER: CNS *2004 paper submission deadline is January 19th, 2004 CALL FOR PAPERS: SUBMISSION DEADLINE: January 19, 2004. midnight; submission open December 1, 2004 Thirteenth Annual Computational Neuroscience Meeting CNS*2004 July 18 - July 20, 2004 (workshops: July 21-22, 2004) Baltimore, USA http://www.cnsorg.org Info at cns at cnsorg.org The annual Computational Neuroscience Meeting will be held at the historic Radisson Plaza Lord hotel in Baltimore, MD from July 18th - 20th, 2004. The main meeting will be followed by two days of workshops on July 21st and 22nd. In conjunction, the "2004 Annual Symposium, University of Maryland Program in Neuroscience: Computation in the Olfactory System" will be held as a satellite symposium to CNS*04 on Saturday, July 17th. NOTICE: NEW PAPER SUBMISSION PROCEDURE! As in the years before papers presented at the CNS*04 meeting can be published as a paper in a special issue of the journal Neurocomputing and in a proceedings book. Authors who would like to see their CNS*04 presentation published will have to submit a COMPLETE manuscript for review during this call (deadline January 19, 2004). You will also have the option to instead submit an extended summary but this cannot be included in the journal. Both types of submissions will be reviewed but full manuscripts will get back reviewers' comments and will have to be revised with final submission shortly after the meeting. The decision of who gets to speak at the conference is independent of the type of submission, both full manuscripts and extended summaries qualify. More details on the review process can be found below. 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. PAPER SUBMISSION The paper submission procedure is again completely electronic this year. Papers for the meeting can be submitted ONLY through the web site at http://www.neuroinf.org/CNS.shtml Papers can be submitted either as a full manuscript to be published in the journal Neurocomputing (max 6 typeset pages) or as an extended summary (1 to 6 pages). You will need to submit both kinds of papers in pdf format and the 100 word abstract as text. You will also need to select two categories which describe your paper and which will guide the selection of reviewers. All submissions will be acknowledged by email generated by the neuroinf.org web robot (may be considered junk mail by a spam filter) 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 machine learning). We will notify authors of meeting acceptance before begin March. The second stage of review involves evaluation by two independent reviewers of full manuscripts submitted to the journal Neurocomputing (all) and those extended summaries which requested an oral presentation. Full manuscripts will be reviewed as real journal publications: each paper will have an action editor and two independent reviewers. The paper may be rejected for publication if it contains no novel content or is considered to contain grave errors. We hope that this will apply to a small number of papers only but we also need to respect a limit of maximum 200 published papers which may enforce more strict criteria. Paper rejection at this stage does not exclude poster presentation at the meeting itself as we assume that these authors will benefit from the feedback they can receive at the meeting. Accepted papers will receive comments for improvements and corrections from the reviewers. Submissions of the revised papers will be due in August. Criteria for selection as an oral presentation include perceived quality, the novelty of the research and the diversity and coherence of the overall program. 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. 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 begin of May. 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 200 papers will be published in the proceedings volume. For reference, papers presented at CNS*02 can be found in volumes 52-54 of Neurocomputing (2003). INVITED SPEAKERS Mary Kennedy (California Institute of Technology, USA) Miguel Nicolelis (Duke University, USA) TBA ORGANIZING COMMITTEE The CNS meeting is organized by the CNS Organization (http://www.cnsorg.org) presided by Christiane Linster (Cornell University, USA). Program chair: Erik De Schutter (University of Antwerp, Belgium) Local organizer: Asaf Keller (University of Maryland School of Medicine, USA) Workshop organizer: Adrienne Fairhall (Princeton University, USA) Government Liaison: Dennis Glanzman (NIMH/NIH, USA) and Yuan Liu (NINDS/NIH, USA) Program Committee : Nicolas Brunel (Universite Paris Rene Descartes, France) Alain Destexhe (CNRS Gif-sur-Yvette, France) Bill Holmes (Ohio University, USA) Hidetoshi Ikeno (Himeji Institute of Technology, Japan) Don H. Johnson (Rice University, USA) Leslie M. Kay (University of Chicago, USA) Barry Richmond (NIMH, USA) Eytan Ruppin (Tel Aviv University, Israel) Frances Skinner (Toronto Western Research Institute, Canada) ******************************************** Organization for Computational Neurosciences ******************************************** ----- End forwarded message ----- ******************************************** Organization for Computational Neurosciences ******************************************** From jean-marc.vesin at epfl.ch Mon Dec 22 12:26:24 2003 From: jean-marc.vesin at epfl.ch (JM Vesin) Date: Mon, 22 Dec 2003 18:26:24 +0100 Subject: JASP special issue on brain-computer interfaces Message-ID: <004001c3bb47$d8260bb0$e579b280@epfl.ch> Dear Colleague, You are a very active researcher in the field of brain-computer interfaces. This is why we take the liberty to draw your attention to a scheduled special issue on trends in brain-computer interfaces which will appear in the EURASIP Journal on Applied Signal Processing (JASP). The goal of this special issue is to present a broad overview of state of the art approaches to brain-computer communication with emphasis on signal processing issues. Topics of interest include, but are not limited to: EEG-based BCI systems Cortical activity based BCI systems BCI systems based on MEG, fMRI, . Pre-processing and feature extraction techniques for BCI systems Neural activity processing Protocols and evaluation methodologies for BCI systems Machine learning applied to BCI systems Applications of BCI systems in rehabilitation, entertainment, robotics, etc. Manuscript due data: January 31st 2004 Notification of acceptance: May 30th 2004 Final manuscript due: August 31st, 2004 Publication: Q1 2005 Guest editors: Dr. Jean-Marc Vesin Signal Processing Institute Swiss Federal Institute of Technology - EPFL CH-1015 Lausanne Email: Jean-Marc.Vesin at epfl.ch Prof. Touradj Ebrahimi Signal Processing Institute Swiss Federal Institute of Technology - EPFL CH-1015 Lausanne Email: Touradj.Ebrahimi at epfl.ch From rsun at rpi.edu Wed Dec 24 15:06:27 2003 From: rsun at rpi.edu (Professor Ron Sun) Date: Wed, 24 Dec 2003 15:06:27 -0500 (EST) Subject: Graduate assistantships available Message-ID: I am looking for a few Ph.D students. The Ph.D program of the Cognitive Science department at RPI is accepting applications. Graduate assistantships and other forms of financial support for graduate students are available. Prospective graduate students with interests in Cognitive Science, especially in learning and skill acquisition and in the relation between cognition and sociality, are encouraged to apply. Prospective applicants should have background in computer science (the equivalent of a BS in computer science), and have some prior exposure to artificial intelligence, connectionist models (neural networks), multi-agent systems, and other related areas. Students with a Master's degree already completed are preferred. RPI is a top-tier research university. This new department has identified the Ph.D program and research as its primary missions. The department is conducting research in a number of areas: computational cognitive modeling, human and machine learning, multi-agent interactions, neural networks and connectionist models, human and machine reasoning, artificial intelligence, cognitive engineering, and so on. See the Web page below regarding my research: http://wwww.cogsci.rpi.edu/~rsun For the application procedure, see http://www.cogsci.rpi.edu/ The application deadline is Jan.15, 2004. If you decide to apply, follow the official procedure as outlined on the Web page. Send me a short email (in plain text, ASCII) after you have completed the application. =================================================================== Professor Ron Sun Cognitive Science Department Rensselaer Polytechnic Institute 110 Eighth Street, Carnegie 302A Troy, NY 12180, USA phone: 518-276-3409 fax: 518-276-8268 email: rsun at rpi.edu web: http://www.cogsci.rpi.edu/~rsun =================================================================== From bogus@does.not.exist.com Wed Dec 24 05:33:14 2003 From: bogus@does.not.exist.com () Date: Wed, 24 Dec 2003 02:33:14 -0800 Subject: Jobs at Amazon.com in Seattle Message-ID: <6380910D0D66CA4C898665521C695D4D01C5C4D1@ex-mail-sea-01.ant.amazon.com> From pooyapakarian at ipm.ir Sun Dec 28 22:18:40 2003 From: pooyapakarian at ipm.ir (Pooya Pakarian) Date: Sun, 28 Dec 2003 19:18:40 -0800 Subject: Wagon wheel illusion Message-ID: Wagon-wheel illusion under steady illumination: real or illusory? Pooya Pakarian, Mohammad Taghi Yasamy Perception 2003, volume 32, number 11, pages 1307 - 1310 Abstract. Wheels turning in the movies sometimes appear to rotate backwards. This is called the wagon-wheel illusion (WWI). The mechanism of this illusion is based on the intermittent nature of light in films and other stroboscopic presentations, which renders them as a series of snapshots rather than a continuous visual data stream. However, there have been claims that this illusion is seen even in continuous light, which would suggest that the visual system itself may sample a continuous visual data stream. We examined the rate of this putative sampling and its variations across individuals while in different psychological states. We obtained two results: (i) WWI occurred in stroboscopic lights as expected, (ii) WWI was never reported by our subjects under continuous lights, such as sunlight and lamps with DC power source. Thus, WWI cannot be taken as evidence for discreteness of conscious visual perception. This article can be downloaded from http://www.perceptionweb.com/perc1103/ or easily just by contacting the corresponding author. ( pooyapakarian at ipm.ir, pooyapakarian at yahoo.com ) Pooya Pakarian,MD School of Cognitive Sciences(SCS) Institute for studies in theoretical Physics and Mathematics(IPM) Niavaran Sq., Tehran, Iran. P.O.Box 19395-5746 From jcid at tsc.uc3m.es Mon Dec 29 07:44:34 2003 From: jcid at tsc.uc3m.es (jcid@tsc.uc3m.es) Date: Mon, 29 Dec 2003 13:44:34 +0100 Subject: Visiting Professor at Carlos III University in Madrid. Message-ID: <40025407de.407de40025@tsc.uc3m.es> University Carlos III de Madrid Department of Signal Theory and Communications Visiting professor The Department of Signal Theory and Communications, University Carlos III de Madrid, Spain, invites applications for a Visiting Professor starting mid. Feb, 2004, to participate as a teacher in an english- speaking group of a course about decision and estimation theory (see program in http://www.uc3m.es/uc3m/gral/ES/ESCU2/0710719.html) for a degree on Telecommunication Engineer. Candidates with interests in decision making, estimation theory and neural networks are encouraged to apply. We seek applicants who have a strong research program and are committed to excellent teaching. Evaluation of candidates will begin January 12, 2004, and will continue until the position is filled. Applicants should submit an e-mail letter and a cv (pdf format) to: Jesus Cid-Sueiro (jcid at tsc.uc3m.es). From bogus@does.not.exist.com Mon Dec 1 10:37:55 2003 From: bogus@does.not.exist.com () Date: Mon, 1 Dec 2003 16:37:55 +0100 Subject: ESANN'2004 : extended deadline Message-ID: ---------------------------------------------------- | | | ESANN'2004 | | | | 12h European Symposium | | on Artificial Neural Networks | | | | Bruges (Belgium) - April 28-29-30, 2004 | | | Extended deadline | ---------------------------------------------------- Due to numerous requests, we are pleased to announce that the deadline for submitting papers to the ESANN'2004 conference has been extended. New deadline: December 12, 2003. The ESANN'2004 covers most of the topics related to the neural network field (see http://www.dice.ucl.ac.be/esann for details). Six special sessions will also be organized: 1. Neural methods for non-standard data B. Hammer, Univ. Osnabrck, B.J. Jain, Tech. Univ. Berlin (Germany) 2. Soft-computing techniques for time series forecasting I. Rojas, H. Pomares, Univ. Granada (Spain) 3. Neural networks for data mining R. Andonie, Central Washington Univ. (USA) 4. Theory and applications of neural maps U. Seiffert, IPK Gatersleben, T. Villmann, Univ. Leipzig, A. Wismller, Univ. Munich (Germany) 5. Industrial applications of neural networks L.M. Reyneri, Politecnico. di Torino (Italy) 6. Hardware systems for Neural devices P. Fleury, A. Bofill-i-Petit, Univ. Edinburgh (Scotland, UK) Instructions concerning the submission of papers are detailed on the web site of the conference. ======================================================== ESANN - European Symposium on Artificial Neural Networks http://www.dice.ucl.ac.be/esann * For submissions of papers, reviews,... Michel Verleysen Univ. Cath. de Louvain - Microelectronics Laboratory 3, pl. du Levant - B-1348 Louvain-la-Neuve - Belgium tel: +32 10 47 25 51 - fax: + 32 10 47 25 98 mailto:esann at dice.ucl.ac.be * Conference secretariat d-side conference services 24 av. L. Mommaerts - B-1140 Evere - Belgium tel: + 32 2 730 06 11 - fax: + 32 2 730 06 00 mailto:esann at dice.ucl.ac.be ======================================================== From maass at igi.tu-graz.ac.at Tue Dec 2 11:16:27 2003 From: maass at igi.tu-graz.ac.at (Wolfgang Maass) Date: Tue, 02 Dec 2003 17:16:27 +0100 Subject: jobs for Phd-students and Postdocs Message-ID: <3FCCBADB.5060701@igi.tu-graz.ac.at> Applications of PHD-STUDENTS and POSTDOCS for the following research project are encouraged, which will be supervised jointly by Nikos Logothetis (MPI for Biological Cybernetics, Tuebingen, Germany) and Wolfgang Maass (Institute for Theoretical Computer Science, Graz, Austria): MODELING BIOLOGICAL VISION This research project is part of a larger research project COGNITIVE VISION (encouraging interaction with researchers from computer vision) that is funded by the Austrian National Science Foundation (FWF). The goal of this research project is to integrate realistic data from in vivo experiments into computer models of parts of the visual system that are functional in the sense that they can solve complex computational tasks on visual input streams. This project involves methods and insight from both neuroscience (especially dynamics of neural circuits and systems in vivo, visual system of primates, computational neuroscience) and computer science (especially machine learning, computer vision, simulations of complex systems). Applicants are expected to have strong backgrounds in at least one of the research disciplines, and should have also demonstrated in their previous work interest and qualifications for interdisciplinary research. But the most important qualification is excellence in research. Applications, with all necessary background documents attached in pdf (or provided via URLs), should be sent by Dec. 17 to maass at igi.tugraz.at. Prof. Nikos Logothetis Max-Planck Institute for Biological Cybernetics Director; Physiology of Cognitive Processes Spemannstr. 38, D-72076 Tuebingen, Germany http://www.kyb.tuebingen.mpg.de/~nikos Prof. Wolfgang Maass Institut fuer Grundlagen der Informationsverarbeitung Technische Universitaet Graz Inffeldgasse 16b, A-8010 Graz, Austria http://www.igi.tugraz.at/maass From bogus@does.not.exist.com Wed Dec 3 11:03:21 2003 From: bogus@does.not.exist.com () Date: 03 Dec 2003 17:03:21 +0100 Subject: No subject Message-ID: <1070467400.19719.4.camel@horas.physik.uni-bremen.de> Dear Connectionnists, We would like to announce the paper "CODING WITH NOISY NEURONS: STABILITY OF TUNING CURVES DEPENDS STRONGLY ON THE ANALYSIS METHOD" by Axel Etzold, Helmut Schwegler, and Christian W. Eurich, to appear in the "Journal of Neuroscience Methods". A standard evaluation method for neural data is the construction of a neural tuning curves. However, the widely used statistical method of statistical analysis based on on the sample mean and least-squares approximation for the spike count can perform extremely badly if the noise distribution is not exactly normal, which is almost never the case in applications. Here we present a method for constructing neural tuning curves that is especially suited for cases of high noise and the presence of outliers. In contrast to traditional methods employing a point-by-point estimation of a tuning curve, we use all measured data from all different stimulus conditions at once in the construction. Using approximation theory, a tuning curve is identified which best approximates a hypothetical ideal tuning curve across all stimulus conditions. The influence of several types of noise distributions on the stability of the parameters of the tuning curve is investigated. A rank-weighted norm is employed which yields more stable tuning curves than the traditional least mean squares method and at the same time conserves information which would be discarded by a median based method. The theoretical results are applied to responses of cells in rat primary visual cortex. A preprint and additional software for MATLAB are available at http://www.neuro.uni-bremen.de/~web/index.php?id=54&link=/~noisy/noisytuning.html The Matlab package may be used by everyone to generate tuning curves automatically from empirical single-cell data. Best regards, Axel Etzold From mzib at ee.technion.ac.il Wed Dec 3 13:00:58 2003 From: mzib at ee.technion.ac.il (Michael Zibulevsky) Date: Wed, 3 Dec 2003 20:00:58 +0200 (IST) Subject: Matlab code is available: relative Newton method for blind source separation Message-ID: Dear friends, the Matlab code of the relative Newton method for blind source separation is available now. The method significantly outperforms natural gradient descent in batch mode. The structure of the corresponding Hessian matrix allows its fast inversion without assembling. Experiments with sparsely representable signals and images show super-efficient separation. The code is located at http://ie.technion.ac.il/~mcib/relnwt021203.zip Best Regards, Michael =========================================================================== Michael Zibulevsky, Ph.D. Email: mzib at ee.technion.ac.il Department of Electrical Engineering Phone: 972-4-829-4724 Technion - Israel Institute of Technology Haifa 32000, Israel http://ie.technion.ac.il/~mcib/ Fax: 972-4-829-4799 =========================================================================== From brody at cshl.org Thu Dec 4 00:26:49 2003 From: brody at cshl.org (Carlos Brody) Date: Thu, 4 Dec 2003 00:26:49 -0500 (EST) Subject: postdoctoral opening in computational olfaction Message-ID: <16334.50585.19559.191918@sonnabend.cshl.org> [Inquiries about this ad may also be directed to Zach Mainen, who will be giving a tutorial on "Neural Coding and the Olfactory System" at NIPS] Postdoctoral position available in computational olfaction: We are seeking highly qualified candidates with a quantitative background and some experience in neuroscience to participate in a combined computational/experimental project to elucidate the role of the rodent olfactory bulb in odor recognition. The succesful applicant will work mostly on the computational side of the project (Brody lab at CSHL: modeling, data analysis; we also collaborate with John Hopfield at Princeton). Work will be very close to, with possible participation in, the experimental side of the project (Mainen lab at CSHL: quantitative behavior, tetrode recordings from behaving rats, intrinsic optical imaging). If interested, please contact Carlos Brody (brody at cshl.edu), emailing a CV, a brief statement of research interests, and the names of two or more referees. Brody lab web site Mainen lab web site Selected references: Brody and Hopfield, Neuron 2003 Uchida and Mainen, Nature Neuroscience 2003 From schmidler at stat.duke.edu Thu Dec 4 09:37:00 2003 From: schmidler at stat.duke.edu (Scott Schmidler) Date: Thu, 4 Dec 2003 09:37:00 -0500 (EST) Subject: Faculty Postion at Duke University Message-ID: <200312041437.hB4Eb0Yd037309@stat.duke.edu> Duke University Medical Center Faculty Position in Computational Neurobiology Department of Biostatistics and Bioinformatics Department of Neurobiology www.cbcb.duke.edu www.neuro.duke.edu Applications are invited for a tenure-track faculty position at the level of Assistant Professor. We seek innovative investigators using state-of-the-art computational and theoretical approaches to address important questions in cellular neurobiology. Candidates must have a Ph.D., M.D. or equivalent degree and postdoctoral experience demonstrating outstanding achievement and substantial promise. Women and minority group members are encouraged to apply. Send a complete curriculum vitae, a brief statement of research interests and goals, and arrange to have three letters of reference sent, to: Computational Neurobiology Search c/o Dr. Thomas B. Kepler Center for Bioinformatics and Computational Biology Box 90090 Duke University Durham NC 27708 or kepler at duke.edu Duke University is an equal opportunity/Affirmative Action employer. ------------------------------------------------------------------------ Scott C. Schmidler Phone: (919) 684-8064 Assistant Professor Fax: (919) 684-8594 Statistics and Decision Sciences Email: schmidler at stat.duke.edu Duke University WWW: www.stat.duke.edu/~scs From kdharris at andromeda.rutgers.edu Thu Dec 4 18:50:03 2003 From: kdharris at andromeda.rutgers.edu (Ken Harris) Date: Thu, 4 Dec 2003 18:50:03 -0500 Subject: Postdoctoral Positions Message-ID: <005f01c3bac1$561691c0$7db5e6a5@limulus> Two postdoctoral positions, one experimental and one theoretical, are available in the Quantitative Neuroscience Laboratory at Rutgers University, to study the organization of cell assemblies in the auditory cortex of the rat. The theory of the "cell assembly" (Hebb, 1949) has been enormously influential in shaping theories of brain function over the last half century. However, only recently have developments in electrophysiology made it possible to record large enough numbers of neurons simultaneously to put this theory to the test experimentally. In recent work (Harris et al, Nature 2003), we employed a novel "peer prediction" method to characterize assembly activity in populations of simultaneously recorded hippocampal neurons. This method found that neurons are organized into groups showing coordinated activity beyond that predicted from spatial modulation of firing rate, with a synchronization timescale of approximately 25ms. However, several questions remain: is this process specific to hippocampus, or a more general aspect of cortical processing? And how does the timing of assembly activity relate to the temporal structure of a sensory stimulus? We are seeking two postdoctoral fellows to address these questions using large-scale parallel recordings in rat auditory cortex, under temporally controlled stimulus conditions. We seek: 1) An experienced electrophysiologist, to record from large neuronal populations using silicon microelectrodes in auditory cortex. Experience with extracellular recording is preferred. However, specific experience of silicon probes or the auditory system is not assumed. 2) A computational neuroscientist. While a knowledge of neuroscience and familiarity with statistical/machine learning techniques is preferred, prior experience with electrophysiological data is not assumed. This project will provide an exciting opportunity for experimental neuroscientists to learn the advanced data analysis methods that are becoming essential to modern electrophysiology, and for theorists to gain hands-on experience with real physiological data. Interested applicants should send a CV by email. ------------------------ Kenneth D. Harris, Ph.D. Assistant Professor Center for Molecular and Behavioral Neuroscience Rutgers, The State University of New Jersey 197 University Avenue Newark NJ 07102, USA phone: 973 353 1080, x3331 fax: 973 353 1272 email: kdharris at andromeda.rutgers.edu web: http://qneuro.rutgers.edu From mccallum at cs.umass.edu Fri Dec 5 08:56:22 2003 From: mccallum at cs.umass.edu (Andrew McCallum) Date: Fri, 5 Dec 2003 08:56:22 -0500 Subject: Postdoctoral position at UMass: ML and text Message-ID: The following postdoc position is available. If you are interested and are planning to attend the NIPS conference in Vancouver (Dec 9-13) please email me and we can arrange to meet there. Sincerely, Andrew McCallum ---------------------------------------------------------------------- Postdoctoral Fellowship Machine Learning, Natural Language Information Extraction and Data Mining Department of Computer Science University of Massachusetts Amherst http://www.cs.umass.edu The UMass CS department is looking for an exceptional postdoc to work in Machine Learning applied to Natural Language, Information Extraction and Data Mining. We are especially interested in people with expertise in statistical machine learning, graphical models, Bayesian methods, approximate inference, and kernel methods. Previous experience applying these techniques to problems in natural language is not necessary. This is an opportunity to exercise your machine-learning know-how on real data and real problems. UMass offers an attractive environment for research at the intersection of machine learning and textual information---with significant strength in information retrieval (Bruce Croft, James Allan, R. Manmatha), machine learning (Andy Barto, Sridhar Mahadevan, Paul Utgoff, David Jensen, Hava Seigelmann, David Kulp, Robbie Moll, Andy Fagg), their intersection (Andrew McCallum), and other related areas (Victor Lesser, Shlomo Zilberstein, Rod Grupen, Oliver Brock, Al Hansen, and others). We also have strong ties to our statistics department, and other nearby universities. We have large staff and computing infrastructure to support significant projects that will enable you to put a big feather in your cap. Ranked among the top six AI groups in the U.S., UMass has an exciting and highly collaborative CS department. UMass CS will continue to have a vibrant atmosphere, as we are expecting to hire 15 new faculty in the coming few years. Located in idyllic western New England, surrounded by five other colleges, UMass is also within day-trip range of both Boston and New York. The University of Massachusetts is an Affirmative Action/Equal Opportunity employer. Women and members of minority groups are encouraged to apply. http://www.cs.umass.edu/csinfo/join_fac_staff/joinfaculty.html. Prospective candidates should apply with a cover letter, CV, and names and email addresses of 2-3 referees. This should be sent by email to: jean at cs.umass.edu, preferably using plain text, Postscript or PDF formats only. From jst at ecs.soton.ac.uk Fri Dec 5 14:18:08 2003 From: jst at ecs.soton.ac.uk (John S Shawe-Taylor) Date: Fri, 5 Dec 2003 19:18:08 +0000 (GMT) Subject: Expanded Machine Learning Group and RA positions at Southampton Message-ID: The Machine Learning Group at the University of Southampton, England, is being expanded with the addition of three new members. From 1st February it will comprise: Steve Gunn, Manfred Opper, Adam Prugel-Bennett, Craig Saunders and John Shawe-Taylor It forms part of the Image, Speech and Intelligent Systems group headed by John Shawe-Taylor within the School of Electronics and Computer Science - see web page: http://www.isis.ecs.soton.ac.uk There are a number of RA positions being currently advertised (http://www.isis.ecs.soton.ac.uk/vacancies/). John, Steve and Manfred will all be attending NIPS and will happily discuss these openings with anyone interested. In addition (subject to the final green light from the EU) the group will be the coordinator of a new Network of Excellence, 'Pattern Analysis, Statistical Modelling and Computational Learning (PASCAL)', involving 56 partners from Europe and Australia. Information about the project and up-coming events will be advertised on the project website www.pascal-network.org. ---------------------------------------------- John Shawe-Taylor ISIS Group School of Electronics and Computer Science University of Southampton Southampton SO17 1BJ Tel: +44 23 8059 3021 Fax: +44 23 8059 4498 ---------------------------------------------- From smyth at ics.uci.edu Fri Dec 5 11:46:10 2003 From: smyth at ics.uci.edu (Padhraic Smyth) Date: Fri, 05 Dec 2003 08:46:10 -0800 Subject: faculty positions in computer science and statistics at UC Irvine Message-ID: <3FD0B652.9010403@ics.uci.edu> The Computer Science Department and the Statistics Department at UC Irvine are currently recruiting faculty in the areas of scientific computing and in statistics. Both departments are within the newly formed School of Information and Computer Science. The School and the University are growing rapidly and offer excellent opportunities for collaborative research. Current faculty in machine learning, AI, and statistics include Pierre Baldi, Rina Dechter, David Van Dyk, Dennis Kibler, Rick Lathrop, Eric Mjolsness, Michael Pazzani, Padhraic Smyth, Hal Stern, and Max Welling. Several of us will be attending the NIPS conference this coming week in Vancouver and would be happy to talk to candidates who are potentially interested in applying. More details on the positions are included below, with pointers to the relevant Web pages for application information. SCIENTIFIC COMPUTING FACULTY POSITION: The Department of Computer Science at UC Irvine is recruiting a tenure-track assistant professor with expertise in scientific computing. Scientific computing is interpreted broadly to include areas such as scientific and engineering numerical computing, numerical analysis, symbolic algebra, multi-scale and adaptive grid simulation, statistics and operations research, computational science, computer graphics and visualization, high performance computer architectures (vector, parallel and distributed), scientific knowledge representation, and scientific databases (this list is not exhaustive). The selected candidate will find opportunities for synergistic interactions within the School of Information and Computer Science with colleagues in areas such as statistics, machine learning, artificial intelligence, computer science theory, graphics and visualization, databases, as well as with faculty in the sciences in other schools at UCI, in areas such as biology, chemistry, earth sciences, social ecology, and cognitive science. Further information on applying is available at http://www.ics.uci.edu/about/jobs/#scientific_computing STATISTICS FACULTY POSITIONS: The Department of Statistics(http://www.stat.uci.edu/) at the University of California, Irvine (UCI), is recruiting three faculty positions in 2003-04: one with tenure and two tenure-track assistant professorships. We anticipate growing to a full-time faculty in statistics of 6-8 people over the next several years, with several more half-time appointments shared with other units at UCI. It will be a department with a strongly interdisciplinary flavor, focused both on developing methods to solve applied problems and the statistical theory that underlies those methods. The Department is interested in individuals with research interests in all areas of statistics at the present time including computational statistics, bioinformatics and genomic statistics, social science statistics, and mathematical statistics. Further information on applying is available at http://www.ics.uci.edu/about/jobs/statsfaculty.php From fyfe-ci0 at wpmail.paisley.ac.uk Sun Dec 7 06:46:44 2003 From: fyfe-ci0 at wpmail.paisley.ac.uk (Colin Fyfe) Date: Sun, 07 Dec 2003 11:46:44 +0000 Subject: PhD Studentship in Computational Intelligence. Message-ID: PhD Studentship in Computational Intelligence. A funded research studentship is available under the supervision of Professor Colin Fyfe at the University of Paisley, Scotland. The studentship is awarded for 3 years with a stipend of*9000 per annum + fees paid. The topic is the use of techniques from Computational Intelligence to make AI play in computer games truly adaptive and intelligent. The techniques used will include artificial neural networks, evolutionary algorithms, swarm methods and artificial immune systems. Applicants should have a good first degree in a numerate discipline. The studentship is expected to lead to the award of PhD. Recent PhDs successfully supervised by Prof Fyfe have been Prof. Mark Girolami , 1998 :Independent Component Analysis Dr. Darryl Charles , 1999 : factor analysis Prof. Juan Corchado , 1999 : case based reasoning, hybrid systems Dr. Stephen McGlinchey, 2000 : topology preserving maps Dr. Pei Ling Lai , 2000 : canonical correlation analysis Dr. Shang-Jen (David) Chuang , 2001 : forecasting Dr. Donald MacDonald, 2001 : Remote sensed image analysis Dr Emilio Corchado, (Universidad de Salamanca), 2002 : Maximum/Minimum Likelihood Hebbian learning Dr Tzai-Der (Douglas) Wang, 2002: evolution of cooperation Dr ZhenKun Gou, 2003: canonical correlation analysis Dr Jos Koetsier, 2003: context assisted learning Dr Danny Livingstone, 2003: evolution of languages The studentship will start as soon as possible. Interested applicants should send a CV to Colin Fyfe at colin.fyfe at paisley.ac.uk by 5th January 2004. 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If you received this in error, please contact the sender immediately and delete the material from any computer. -------------------------- From pollack at cs.brandeis.edu Mon Dec 8 14:31:50 2003 From: pollack at cs.brandeis.edu (Jordan Pollack) Date: Mon, 08 Dec 2003 14:31:50 -0500 Subject: neural nets and Artificial Life Message-ID: <3FD4D1A6.4090806@cs.brandeis.edu> I am chairing the Ninth International Artificial Life Conference, and we are interested in attracting people who are evolving neural networks, developing theories of brain evolution, language evolution, mind/brain co-evolution, which should be of interests to people in Neural Nets. We are also seeking Neuroscience related papers such as scale-free networks, neutral networks, gene regulatory and developmental networks. Alife9 will be in downtown Boston, September 12-15th 2004. The deadline is 30 January 2004, and MIT Press is publishing. The full CFP is available at http://www.alife9.org Regards to my many friends on Connectionists... Jordan Pollack From bower at uthscsa.edu Mon Dec 8 16:41:49 2003 From: bower at uthscsa.edu (james Bower) Date: Mon, 08 Dec 2003 15:41:49 -0600 Subject: Three Positions in Animal Imaging Message-ID: The Neuroscience Research Group at the Research Imaging Center within The University of Texas Health Science Center - San Antonio Seeks Applicants at the Assistant, Associate, or Full Professor level in Animal Imaging (broadly defined). The Research Imaging Center (RIC) at the University of Texas Health Science Center at San Antonio (UTHSCSA) seeks applicants for faculty positions in its Animal Imaging Division. The RIC is a department-level component of the UTHSCSA School of Medicine and specializes in the application of imaging techniques to human and animal neuroscience. Translational imaging research (complementary use of human and animal models) integrated application of multiple imaging techniques and use of computational models in imaging research are areas of focus. Techniques currently supported for animal imaging include PET, anatomical and functional MRI, MRS, multi-unit electrode recording, and optical reflectance imaging. Techniques currently supported for human imaging include PET, anatomical and functional MRI, MRS, ERPs, and TMS. The Animal Imaging Division seeks a minimum of 3 full-time faculty with diverse backgrounds (e.g. one in MRI, one in PET, one in imaging related electrophysiology) and experience in inter-disciplinary collaborations. One of these positions will be the Chief of the Animal Imaging Division. The Division Chief will assume oversight of a Concord MicroPET, and two MRI/MRS systems: a 4.7T horizontal bore system, and a 7.0T vertical bore system. All three imaging systems are housed within an animal facility immediately adjacent to the RIC's other imaging systems, laboratories, and offices. Send Resume and cover letter to: Peter Fox M.D., Professor and Director, Research Imaging Center, the University of Texas Health Science Center, 7703 Floyd Curl Drive, San Antonio, Texas 78229-3900 The University of Texas Health Science Center San Antonio is an Equal Employment Opportunity/Affirmative Action Employer. All faculty appointments are designated as security sensitive positions. -- James M. Bower Ph.D. Research Imaging Center University of Texas Health Science Center at San Antonio 7703 Floyd Curl Drive San Antonio, TX 78284-6240 Cajal Neuroscience Center University of Texas San Antonio Phone: 210 567 8080 Fax: 210 567 8152 From E.Koning at elsevier.nl Tue Dec 9 02:58:47 2003 From: E.Koning at elsevier.nl (Koning, Esther (ELS)) Date: Tue, 9 Dec 2003 07:58:47 -0000 Subject: CFP - Neurocomputing: Geometrical Methods in Neural Networks and Learning Message-ID: <06372B4E0B1E7D4FAAD2B63276D87002029B447C@elsamsvexch01.elsevier.nl> CALL FOR PAPERS NEUROCOMPUTING - An International Journal Editor-in-Chief: Tom Heskes Journal published by Elsevier Science B.V. - URL: http://www.elsevier.com/locate/neucom Special Issue on "Geometrical Methods in Neural Networks and Learning" Understanding the underlying geometric structure of a network's parameter space is extremely important to designing systems that can effectively navigate the space while learning. Although modern mathematics is needed in the research of neural networks, and there are some very powerful results and techniques in these geometric methods, these are currently scattered in various sources. Over the last decade or so, driven greatly by the work on information geometry, we are seeing the merging of the fields of statistics and geometry applied to neural network and learning. This requires intense collaboration and communication. The interest displayed by the scientific community into these research topics is also testified by several activities such as the special issue on "Non-Gradient Learning Techniques" of the International Journal of Neural Systems (guest editors A. de Carvalho and S.C. Kremer), the Post-NIPS*2000 workshop on "Geometric and Quantum Methods in Learning", organized by S.-i. Amari, A. Assadi and T. Poggio (Colorado, December 2000), the workshop "Uncertainty in geometric computations" held in Sheffield, England, in July 2001, organized by J. Winkler and M. Niranjan (University of Sheffield, UK), the special session of the IJCNN'02 on "Differential & Computational Geometry in Neural Networks" (session chair: E. Bayro-Corrochano, CINVESTAV, Guadalajara, Mexico) held in Honolulu, Hawaii (USA), in May 2002, and the workshop "Information Geometry and its Applications", held in Pescara (Italy), in July 2002, organized by P. Giblisco. For these reasons, the Neurocomputing journal dedicates a Special Issue to the theory and advanced applications of geometric concepts to neural learning and optimization, bringing together contributions well founded in modern mathematics. The topics of the Special Issue are the theoretical and practical aspects of geometrical methods for the design of neural networks making emphasis in geometric learning and optimization. The readers will have for the first time a collection of approaches including differential geometrical methods for learning, the Lie group learning algorithms, the natural (Riemannian) gradient techniques, learning by weight flows on Stiefel-Grassman manifolds, the theories for learning on orthogonal group, neurocomputing using Clifford geometric algebra, the numerical aspects of the solution of the matrix-equations on Lie groups arising in neural learning/optimization and related topics. The Neurocomputing journal invites original contributions for the forthcoming Special Issue on Geometrical Methods in Neural Networks and Learning from a broad scope of areas. Some topics relevant to this special issue include, but are not restricted to: - Neural principal component/subspace analysis; - Neural independent component analysis and blind source separation; - Natural computing (geometrical algorithms that could take place in neural circuitry); - Selection of subspaces for optimal neural data compression; - Neural optimization over the orthogonal group and optimization problems in tensor algebra; - Information geometry; - Provably convergent geometric algorithms for real-time learning; - Geometry of boosting methods; - Geometric Clifford algebra for the generalization of neural networks; - Geometrical methods of unsupervised learning for blind signal processing; - Application of Lie operators and use of differential geometry based learning techniques; - Conformal and horosphere models for neurocomputing; - Tensorial approach for geometrical neural computation and learning; - General graphical model and belief propagation for machine learning; - Geometry of statistical-physical methods for learning. Please submit the electronic copy to http://authors.elsevier.com/journal/neucom including abstract, keywords, a cover page containing the title and Author(s) name(s), corresponding Author's complete address including fax and EMail address, and clear indication to be a submission to the Special Issue on Geometrical Methods in Neural Networks and Learning. -- Scheduling of the Special Issue: Deadline for papers submission: March 1, 2004 End of refereeing process and result issuing: July 30, 2004 Submission of the final manuscript: September 30, 2004 Guest Editors: Simone Fiori Faculty of Engineering, University of Perugia Polo Didattico e Scientifico del Ternano Loc. Pentima bassa, 21, I-05100 Terni (Italy) Fax: +39.0744.492925 EMail: fiori at unipg.it URL: http://www.unipg.it/sfr/ Shun-ichi Amari RIKEN Brain Science Institute Laboratory for Mathematical Neuroscience Wako-shi Hirosawa 2-1, Saitama 351-0198 (Japan) Fax: +81.48467.9687 EMail: amari at brain.riken.go.jp URL: http://www.bsis.brain.riken.go.jp/ From A.Sharkey at dcs.shef.ac.uk Tue Dec 9 10:05:36 2003 From: A.Sharkey at dcs.shef.ac.uk (Amanda Sharkey) Date: Tue, 9 Dec 2003 15:05:36 +0000 (GMT) Subject: Connection Science journal - some changes Message-ID: The editors of Connection Science would like to draw your attention to the revised aims and scope for the journal. Connection Science: A journal of adaptation, neural computing, artificial intelligence and cognition. Connection Science is an interdisciplinary scientific journal with a focus on the mechanisms of adaptation, cognition and intelligent behaviour in both living and artificial systems. The traditional scope of the journal has been broadened from connectionist research and neural computing to encompass work on other adaptive methods (e.g. evolutionary computing) as well as biologically inspired techniques and algorithms in applied domains. Papers should still be related to either the behaviour of humans or other animals or to the underlying mechanisms. Papers submitted to the journal may be practical implementations, theoretical research or philosophical discussions. The submission of robotics research papers on issues raised by the interaction of agents with the environment or with other agents is particularly encouraged. Editor in Chief: Noel Sharkey Editors: Tom Ziemke and Amanda Sharkey http://www.tandf.co.uk/journals From bogus@does.not.exist.com Tue Dec 9 08:33:04 2003 From: bogus@does.not.exist.com () Date: Tue, 9 Dec 2003 21:33:04 +0800 Subject: 5 papers for comments Message-ID: <9CFE75F87A78564887952466CA3F4E4D03713E90@exchange02.staff.main.ntu.edu.sg> From cns at cns.bu.edu Tue Dec 9 10:17:57 2003 From: cns at cns.bu.edu (BU CNS Department) Date: Tue, 09 Dec 2003 10:17:57 -0500 Subject: GRADUATE TRAINING IN THE DEPARTMENT OF COGNITIVE AND NEURAL SYSTEMS (CNS) AT BOSTON UNIVERSITY Message-ID: <3FD5E7A5.9080702@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 2004 admission and financial aid are now being accepted for PhD, MA, and BA/MA degree programs. To obtain a brochure describing CNS programs 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) general test scores. 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. CNS is a world leader 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 producing 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 academic and research advisors. 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 carry out 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, 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 unites 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, and technology), 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 RESEARCH 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 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 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, vision, synaptic processes, pattern recognition, remote sensing, medical database analysis, machine learning, differential equations 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 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 Diego Visual word recognition, psycholinguistics, cognitive semantics, second language acquisition, computational models of cognition Michael E. Hasselmo Associate Professor of Psychology Director of Graduate Studies, Department of Psychology 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 VLSI circuit design: digital, analog, subthreshold analog, biCMOS, CMOS; information processing in neurons, neural net chips, synthetic aperture radar (SAR) processing chips, sonar processing chips; auditory models and experiments 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 Siegfried Martens Research Associate, Department of Cognitive and Neural Systems PhD, Cognitive and Neural Systems, Boston University Learning models, pattern recognition, visualization, remote sensing, sensor fusion 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 Bradley Rhodes Research Associate, Department of Cognitive and Neural Systems PhD, Cognitive and Neural Systems, Boston University Motor control, learning, and adaptation, serial order behavior (timing in particular), attention and memory Michele Rucci Assistant Professor of Cognitive and Neural Systems PhD, Scuola Superiore S.-Anna, Pisa, Italy Vision, sensory-motor control and learning, and computational neuroscience 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 Associate 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 Timothy Streeter Research Associate, Department of Cognitive and Neural Systems MS, Physics, University of New Hampshire MA, Cognitive and Neural Systems, Boston University Spatial auditory perception, perceptual adaptation 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) Jeremy Wolfe Adjunct 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 Perception 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, 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 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. Auditory Neuroscience Laboratory The Auditory Neuroscience 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 Auditory Neuroscience Laboratory consists of three adjacent rooms in the basement of 677 Beacon Steet (the home of the CNS Department). One room houses an 8 ft. ? 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. 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; 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. 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 Lab was established in July 2001, with a grant from the Air Force Office of Scientific Research: "Information Fusion for Image Analysis: Neural Models and Technology Development." Initial projects have focused on multi-level fusion and data mining in a geospatial context, in collaboration with the Boston University Center for Remote Sensing. This research and development have built on models of opponent-color visual processing, boundary contour system (BCS) and texture processing, and Adaptive Resonance Theory (ART) pattern learning and recognition, as well as other models of associative learning and prediction. Other projects include collaborations with the New England Medical Center and Boston Medical Center, to develop methods for analysis of large-scale medical databases, currently to predict HIV resistance to antiretroviral therapy. Associated basic research projects are conducted within the joint context of scientific data and technological constraints. 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://cns.bu.edu/ ******************************************************************* From h.jaeger at iu-bremen.de Thu Dec 11 14:38:20 2003 From: h.jaeger at iu-bremen.de (Herbert Jaeger) Date: Thu, 11 Dec 2003 20:38:20 +0100 Subject: CFP: Interdisciplinary College 2004 Message-ID: <3FD8C7AC.9030005@iu-bremen.de> Announcing the Interdisciplinary College 2004 (IK 04) Time: March 5 - 12, 2004 Location: Guenne, a charming out-of-the-world village at the border of lake Moehnesee in central Germany. Website: www.ik2004.de What is IK? The Interdisciplinary College (Interdisziplinaeres Kolleg, IK) is an annual one-week spring school on all brain & intelligence related sciences. It offers a dense, state-of-the-art course program in neurobiology, neural computation, cognitive science and artificial intelligence. It is aimed at students, postgraduates and researchers from academia and industry. By combining humanities, science and technology, the IK endeavours to intensify dialogue and connectedness across the various disciplines. The IK has a long tradition (see website); in its current form it has been organized annually since 1999. All courses are taught in English. The IK 2004 Each IK has a special focus theme. About 30-40 percent of the courses are dedicated to aspects of this theme, which at IK-04 is "body and motion". It is reflected in a number of courses that deal with the following topics: - mathematical modelling of complex dynamical systems - disorders in the human motor system - perception and action in cognitive science - neural networks in motor control - motion planning in robots - navigation strategies in insects and robots - cognitive and neuronal representation of motion patterns - development of motor skills in infants - analysis of motion patterns in sports - didactical use of dance, singing, and motion in language teaching - philosophy of embodied cognition For more detailed information about program, history, conference site, organizers, and registration, please consult www.ik2004.de. ------------------------------------------------------------------ Dr. Herbert Jaeger Professor for Computational Science International University Bremen Campus Ring 12 28759 Bremen, Germany Phone (+49) 421 200 3215 email h.jaeger at iu-bremen.de http://www.iu-bremen.de/directory/faculty/29979/ http://www.ais.fraunhofer.de/INDY/herbert/ ------------------------------------------------------------------ From cindy at bu.edu Mon Dec 15 10:47:39 2003 From: cindy at bu.edu (Cynthia Bradford) Date: Mon, 15 Dec 2003 10:47:39 -0500 Subject: Neural Networks 17(1) Message-ID: <00f101c3c322$c5c8ee50$903dc580@cnspc31> NEURAL NETWORKS 17(1) Contents - Volume 17, Number 1 - 2004 ------------------------------------------------------------------ EDITORIAL: Another exciting year for the INNS/ENNS/JNNS Journal! NEURAL NETWORKS REFEREES USED IN 2003 ***** Neuroscience and Neuropsychology ***** "Self-organizing continuous attractor networks with multiple activity packets and the representation of space" S.M. Stringer, E.T. Rolls, and T.P. Trappenberg ***** Mathematical and Computational Analysis ***** "Combining Hebbian and reinforcement learning in a minibrain model" R.J.C. Bosman, W.A. van Leeuwen, and B. Wemmenhove "Neocognitron capable of incremental learning" Kunihiko Fukushima "Global asymptotic stability of Hopfield neural network involving distributed delays" Hongyong Zhao "Associative memory by recurrent neural networks with delay elements" Seiji Miyoshi, Hiro-Fumi Yanai, and Masato Okada "Steepest descent with momentum for quadratic functions is a version of the conjugate gradient method" Amit Bhaya and Eugenius Kaszkurewicz "A comparative study of two modeling approaches in neural networks" Zong-Ben Xu, Hong Qiao, Jigen Peng, and Bo Zhang "Dynamics of periodic delayed neural networks" Jin Zhou, Zengroung Liu, and Guanrong Chen "Mixed states on neural network with structural learning" Tomoyuki Kimoto and Masato Okada "Practical selection of SVM parameters and noise estimation for SVM regression" Vladimir Cherkassky and Yunqian Ma "Experimentally optimal nu in support vector regression for different noise models and parameter settings" Athanassia Chalimourda, Bernhard Scholkopf, and Alex J. Smola "Discrimination networks for maximum selection" Brijnesh J. Jain and Fritz Wysotzki CURRENT EVENTS ------------------------------------------------------------------ Electronic access: www.elsevier.com/locate/neunet/. Individuals can look up instructions, aims & scope, see news, tables of contents, etc. Those who are at institutions which subscribe to Neural Networks get access to full article text as part of the institutional subscription. Sample copies can be requested for free and back issues can be ordered through the Elsevier customer support offices: nlinfo-f at elsevier.nl usinfo-f at elsevier.com or info at elsevier.co.jp ------------------------------ INNS/ENNS/JNNS Membership includes a subscription to Neural Networks: The International (INNS), European (ENNS), and Japanese (JNNS) Neural Network Societies are associations of scientists, engineers, students, and others seeking to learn about and advance the understanding of the modeling of behavioral and brain processes, and the application of neural modeling concepts to technological problems. Membership in any of the societies includes a subscription to Neural Networks, the official journal of the societies. Application forms should be sent to all the societies you want to apply to (for example, one as a member with subscription and the other one or two as a member without subscription). The JNNS does not accept credit cards or checks; to apply to the JNNS, send in the application form and wait for instructions about remitting payment. The ENNS accepts bank orders in Swedish Crowns (SEK) or credit cards. The INNS does not invoice for payment. ---------------------------------------------------------------------------- Membership Type INNS ENNS JNNS ---------------------------------------------------------------------------- membership with $80 (regular) SEK 660 Y 13,000 Neural Networks (plus Y 2,000 enrollment fee) $20 (student) SEK 460 Y 11,000 (plus Y 2,000 enrollment fee) ---------------------------------------------------------------------------- membership without $30 SEK 200 not available to Neural Networks non-students (subscribe through another society) Y 5,000 student (plus Y 2,000 enrollment fee) ---------------------------------------------------------------------------- Name: _____________________________________ Title: _____________________________________ Address: _____________________________________ _____________________________________ _____________________________________ Phone: _____________________________________ Fax: _____________________________________ Email: _____________________________________ Payment: [ ] Check or money order enclosed, payable to INNS or ENNS OR [ ] Charge my VISA or MasterCard card number ____________________________ expiration date ________________________ INNS Membership 19 Mantua Road Mount Royal NJ 08061 USA 856 423 0162 (phone) 856 423 3420 (fax) innshq at talley.com http://www.inns.org ENNS Membership University of Skovde P.O. Box 408 531 28 Skovde Sweden 46 500 44 83 37 (phone) 46 500 44 83 99 (fax) enns at ida.his.se http://www.his.se/ida/enns JNNS Membership c/o Professor Shozo Yasui Kyushu Institute of Technology Graduate School of Life Science and Engineering 2-4 Hibikino, Wakamatsu-ku Kitakyushu 808-0196 Japan 81 93 695 6108 (phone and fax) jnns at brain.kyutech.ac.jp http://www.jnns.org/ ---------------------------------------------------------------------------- From terry at salk.edu Tue Dec 16 19:08:54 2003 From: terry at salk.edu (Terry Sejnowski) Date: Tue, 16 Dec 2003 16:08:54 -0800 (PST) Subject: NEURAL COMPUTATION 16:1 Message-ID: <200312170008.hBH08sQ59057@purkinje.salk.edu> Neural Computation - Contents - Volume 16, Number 1 - January 1, 2004 ARTICLE Bayesian Computation in Recurrent Neural Circuits Rajesh P. N. Rao LETTERS Probability of Stimulus Detection in a Model Population of Rapidly Adapting Fibers Burak Guclu and Stanley J. Bolanowski A Machine Learning Method for Extracting Symbolic Knowledge from Recurrent Neural Networks A Vahed and C. W. Omlin Orthogonality of Decision Boundaries in Complex-Valued Neural Networks Tohru Nitta On the Asymptotic Distribution of the Least-Squares Estimators in Unidentifiable Models Taichi Hayasaka, Masashi Kitahara and Shiro Usui Asymptotic Properties of the Fisher Kernel Koji Tsuda, Shotaro Akaho, Motoaki Kawanabe and Klaus-Robert Mueller Adaptive Hybrid Learning for Neural Networks Rob Smithies, Said Salhi and Nat Queen Divergence Function, Duality, and Convex Analysis Jun Zhang Linear Response Algorithms for Approximate Inference in Graphical Models Max Welling and Yee Whye Teh ----- 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 Jean-Arcady.Meyer at lip6.fr Wed Dec 17 11:45:17 2003 From: Jean-Arcady.Meyer at lip6.fr (Jean-Arcady Meyer) Date: Wed, 17 Dec 2003 17:45:17 +0100 Subject: Tenure positions at CNRS - Research on animats and robots Message-ID: <00cf01c3c4bd$2c7ae360$41cde384@lip6.fr> In 2004, the French CNRS recruits about 320 tenured scientists: http://www.sg.cnrs.fr/drhchercheurs/concoursch/indexen.html In particular, there are opportunities for=20 * 1 position CR2 (junior research scientist, born in 1971 or after, monthly salary between 1570=88 and 2010=88), in section 07 (competition number 05) in the field of "Simulation and modeling in signal processing and robotics for cognitive sciences". * 2 positions CR1 (experienced research scientist, no age limit, monthly salary between 1650=88 and 2950=88), in section 45 (competition number 02) in the field of "Cognition, language, signal processing: natural and artificial systems" People willing to participate in the corresponding competitive recruitment must send application files before January 16, 2004 to the CNRS. See details in the CNRS site: http://www.sg.cnrs.fr/drhchercheurs/concoursch/indexen.html http://www.sg.cnrs.fr/drhchercheurs/concoursch/pdf/CR2.pdf http://www.sg.cnrs.fr/drhchercheurs/concoursch/pdf/n_cr2.pdf http://www.sg.cnrs.fr/drhchercheurs/concoursch/pdf/CR1.pdf http://www.sg.cnrs.fr/drhchercheurs/concoursch/pdf/n_cr1.pdf People wishing to be specifically recruited within the AnimatLab in Paris (http://animatlab.lip6.fr ) in order to contribute to the research on animats that is done there, should contact Dr. Jean-Arcady Meyer (jean-arcady.meyer at lip6.fr).=20 From nk at cs.aue.auc.dk Thu Dec 18 11:41:20 2003 From: nk at cs.aue.auc.dk (Norbert Kruger) Date: Thu, 18 Dec 2003 17:41:20 +0100 Subject: Workshop on Coding of Visual Information in the Brain Message-ID: <3FE1D8B0.6060605@cs.aue.auc.dk> Workshop on Coding of Visual Information in the Brain June 1, 2004, Isle of Skye, Scotland Satellite event of the Early Cognitive Vision Workshop (28.5.-1.6.2004) http://www.cn.stir.ac.uk/ecovision-ws/ Call for Contributions How is visual Information coded in the human brain? How are statistical properties of natural images related to the internal representations/coding? What is the prior knowledge the human visual system is equipped with? In what sense does the actual task influence the internal state? What is the goal of the early visual processes and how can we achieve integration? What is the functional role of the temporal structure of neural firing patterns? These questions are relevant for research concerning the modelling of biological visual systems as well as building artificial systems. The workshop 'Coding of Visual Information in the Brain' has the aim to bring together scientists involved in neurophysiology, psychology and computer vision to discuss these issues under a multi-disciplinary perspective. As well as the contributed talks and posters, a number of leading scientists with strong interest in bridging the gap between human and artificial vision will be giving invited talks. The workshop will follow the tradition of the 'Information Theory and the Brain' workshops held in Stirling 1995 and in Newquay 1997. However, in contrast to its predecessors it is more focussed on vision. The workshop will be organised as a satellite event of the Early Cognitive Vision Workshop that will be held from May 28 to June 1 2004 (see http://www.cn.stir.ac.uk/ecovision-ws/). Please submit a one-page abstract, preferably by email to Peter Hancock (pjbh1 at psych.stir.ac.uk) or Norbert Krueger (nk at cs.aue.auc.dk) by 23.1.2004. Organising Committee Peter Hancock (Stirling, Scotland) Norbert Krueger (Esbjerg, Denmark) Florentin Woergoetter (Stirling, Scotland) Roland Baddeley (Sussex, England) Laurenz Wiskott (Berlin, Germany) James Elder (York, Canada) Invited Speakers James Elder (York, Canada) Christoph von der Malsburg (Bochum, Germany) Guy Orban (Brussel, Belgium) Roger Watt (Stirling, Scotland) From arno at salk.edu Wed Dec 17 11:11:45 2003 From: arno at salk.edu (Arnaud Delorme) Date: Wed, 17 Dec 2003 08:11:45 -0800 Subject: Orientation selectivity using fast feed-forward inhibition: paper and Neuron simulation files Message-ID: <3FE08041.1030708@salk.edu> The following article Delorme, A. (2003) Early Cortical Orientation Selectivity: How Fast Shunting Inhibition Decodes the Order of Spike Latencies. /Journal of Computational Neuroscience/, 15, 357-365. Author's PDF , journal's link . and the associated Neuron simulation files (documented) are available at http://www.sccn.ucsd.edu/~arno/model.html --------------------------- Article abstract: Following a flashed stimulus, I show that a simple neurophysiological mechanism in the primary visual system can generate orientation selectivity based on the first incoming spikes. A biological model of the lateral geniculate nucleus generates an asynchronous wave of spikes, with the most strongly activated neurons firing first. Geniculate activation leads to both the direct excitation of a cortical pyramidal cell and disynaptic feed-forward inhibition. The mechanism provides automatic gain control, so the cortical neurons respond over a wide range of stimulus contrasts. It also demonstrates the biological plausibility of a new computationally efficient neural code: latency rank order coding. -- *Arnaud Delorme, Ph.D.* Computational Neurobiology Lab, Salk Institute 10010 North Torrey Pines Road La Jolla, CA 92037 USA *Tel* : /(+1)-858-458-1927 ext 15/ *Fax* : /(+1)-858-458-1847/ *Web page *: www.sccn.ucsd.edu/~arno *To think upon*: The longing to produce great inspirations didn't produce anything but more longing. /Sophie Kerr/ From cindy at bu.edu Wed Dec 17 09:28:38 2003 From: cindy at bu.edu (Cynthia Bradford) Date: Wed, 17 Dec 2003 09:28:38 -0500 Subject: 8th ICCNS: Final Call for Abstracts Message-ID: <000001c3c4aa$0f9986b0$903dc580@cnspc31> Apologies if you receive more than one copy of this email. ***** FINAL CALL FOR ABSTRACTS ***** Submission Deadline: January 30, 2004 EIGHTH INTERNATIONAL CONFERENCE ON COGNITIVE AND NEURAL SYSTEMS May 19-22, 2004 http://cns.bu.edu/meetings/ Boston University 677 Beacon Street Boston, Massachusetts 02215 Sponsored by Boston University's Center for Adaptive Systems and Department of Cognitive and Neural Systems with financial support from the Office of Naval Research CONFIRMED SPEAKERS: Tutorial Lecture Series: Stephen Grossberg Keynote Lectures: John Anderson and Miguel Nicolelis Invited Speakers: Ehud Ahissar, Alan D. Baddeley, Moshe Bar, Gail A. Carpenter, Stephen Goldinger, Daniel Kersten, Stephen M. Kosslyn, Tai-Sing Lee, Eve Marder, Bartlett W. Mel, Jeffrey D. Schall, Chantal Stern, Mriganka Sur, Joseph Z. Tsien, William H. Warren Jr., Jeremy Wolfe. Please visit the web site for conference details, including: --the abstract submission guidelines for contributed lectures and posters --the registration form --a schedule of the confirmed speakers and their lecture titles --information about graduate student and postdoctoral travel fellowships --local lodging options From golden at utdallas.edu Fri Dec 19 08:49:44 2003 From: golden at utdallas.edu (Richard Golden) Date: Fri, 19 Dec 2003 07:49:44 -0600 (CST) Subject: Math Psych Meeting Announcements! Message-ID: Please post this announcement to your mailing list. Thanks! Richard Golden ================================================================== The 37th Meeting of the Society for Mathematical Psychology will be held at the University of Michigan (July 29, 2004 through August 1, 2004). Professor Shun-ichi Amari (Riken Brain Science Institute, Japan) [Co-Editor In Chief of the Journal "Neural Networks"] will be giving a plenary talk! The Tutorial workshop will begin at 8:30am on July 29, 2004 and is entitled "Differential Geometry with Applications to Measurement and Statistics". In mid-January 2004 you should be receiving a packet of materials if you are a current member in good standing in the Society for Mathematical Psychology. Most of these materials as well as more detailed information about the conference and the workshop may be found as: http://www.cogs.indiana.edu/socmathpsych Thanks, Richard Golden Secretary-Treasurer, SMP From editors at jmlg.org Fri Dec 19 13:45:02 2003 From: editors at jmlg.org (editors@jmlg.org) Date: Fri, 19 Dec 2003 13:45:02 -0500 Subject: Journal of Machine Learning Gossip Message-ID: Dear connectionists, On the occasion of the final NIPS paper submission, the Journal of Machine Learning Gossip (http://www.jmlg.org) would like to offer its services to the machine learning community. At http://www.jmlg.org/software/pssq-page.htm you can download the most recent tool from our Extreme Programming Team which allows to (font) compress any paper to any number of pages with little visual difference. No warranty is provided whatsoever and no liability is accepted for the use of this program. If your paper gets rejected because you squished it too much then you work shorter hours, produce less and write genuinely shorter papers. You have been warned. Note that at http://www.jmlg.org you can find also information on other aspects of academic life in the machine learning community and more useful tools. Best regards Editors of www.jmlg.org From mvanross at inf.ed.ac.uk Sun Dec 21 07:28:45 2003 From: mvanross at inf.ed.ac.uk (Mark van Rossum) Date: Sun, 21 Dec 2003 12:28:45 +0000 (GMT) Subject: 4-Year Doctoral Training (Ph.D.) Neuroinformatics in Edinburgh Message-ID: 4-Year Doctoral Training (Ph.D.) Neuroinformatics We invite applications for the EPSRC/MRC funded Ph.D. programme to the Neuroinformatics Doctoral Training Centre at the University of Edinburgh. The programme is made up of 3 themes: 1) Computational and Cognitive Neuroscience - analytical, computational and experimental study of information processing in the nervous system. 2) Neuromorphic Engineering and Robotics - Artificial sensor perception and analysis, neuromorphic modelling, mixed-mode VLSI and spiking computation, neurorobotics. 3) Simulation, Analysis, Visualisation and Data Handling - software systems and computational techniques for neuroscience and neural engineering. The 4-year programme in Neuroinformatics, established in 2002, consists of an introductory year with training in neuroscience, informatics and lab-based research projects, followed by 3 years of Ph.D. research related to one of the above subjects. The programme has a strong interdisciplinary character and is ideal for students who want to apply their skills to neuroinformatics problems. Students with a strong background in computer science, mathematics, physics or engineering are particularly welcome to apply, but motivated students with other backgrounds will also be considered. We will be accepting an average of 10 students per year. Students will be attached initially to the Institute for Adaptive and Neural Computation in the School of Informatics, the UK's largest and highest-quality academic computer-science group. The Ph.D. project can be done in collaboration with many affiliated institutes. Edinburgh has a strong research community in all of the areas listed above and leads the UK in integrating these into a coherent programme in neuroinformatics. Edinburgh has been voted as 'best place to live in Britain', and has many exciting cultural and student activities. The stipend is set in the region of 10,000 pounds in the first year and 13,000 pounds per annum in years 2-4. Studentships cover full tuition fees and research and training costs. Full studentships are available to UK students only. Partial funding is available for EU students. Applicants who are not citizens or longstanding residents of the EU will need to find their own funding. For full application details and further information please consult the website: http://www.anc.ed.ac.uk/neuroinformatics. Applications are welcome at any time; those received by March 15th 2004 will receive priority treatment. From cns at cnsorg.org Mon Dec 22 14:43:15 2003 From: cns at cnsorg.org (CNS - Organization for Computational Neurosciences) Date: Mon, 22 Dec 2003 11:43:15 -0800 Subject: REMINDER: CNS*2004 Deadline submission coming up! Message-ID: <1072122195.3fe749536591b@webmail.mydomain.com> REMINDER: CNS *2004 paper submission deadline is January 19th, 2004 CALL FOR PAPERS: SUBMISSION DEADLINE: January 19, 2004. midnight; submission open December 1, 2004 Thirteenth Annual Computational Neuroscience Meeting CNS*2004 July 18 - July 20, 2004 (workshops: July 21-22, 2004) Baltimore, USA http://www.cnsorg.org Info at cns at cnsorg.org The annual Computational Neuroscience Meeting will be held at the historic Radisson Plaza Lord hotel in Baltimore, MD from July 18th - 20th, 2004. The main meeting will be followed by two days of workshops on July 21st and 22nd. In conjunction, the "2004 Annual Symposium, University of Maryland Program in Neuroscience: Computation in the Olfactory System" will be held as a satellite symposium to CNS*04 on Saturday, July 17th. NOTICE: NEW PAPER SUBMISSION PROCEDURE! As in the years before papers presented at the CNS*04 meeting can be published as a paper in a special issue of the journal Neurocomputing and in a proceedings book. Authors who would like to see their CNS*04 presentation published will have to submit a COMPLETE manuscript for review during this call (deadline January 19, 2004). You will also have the option to instead submit an extended summary but this cannot be included in the journal. Both types of submissions will be reviewed but full manuscripts will get back reviewers' comments and will have to be revised with final submission shortly after the meeting. The decision of who gets to speak at the conference is independent of the type of submission, both full manuscripts and extended summaries qualify. More details on the review process can be found below. 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. PAPER SUBMISSION The paper submission procedure is again completely electronic this year. Papers for the meeting can be submitted ONLY through the web site at http://www.neuroinf.org/CNS.shtml Papers can be submitted either as a full manuscript to be published in the journal Neurocomputing (max 6 typeset pages) or as an extended summary (1 to 6 pages). You will need to submit both kinds of papers in pdf format and the 100 word abstract as text. You will also need to select two categories which describe your paper and which will guide the selection of reviewers. All submissions will be acknowledged by email generated by the neuroinf.org web robot (may be considered junk mail by a spam filter) 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 machine learning). We will notify authors of meeting acceptance before begin March. The second stage of review involves evaluation by two independent reviewers of full manuscripts submitted to the journal Neurocomputing (all) and those extended summaries which requested an oral presentation. Full manuscripts will be reviewed as real journal publications: each paper will have an action editor and two independent reviewers. The paper may be rejected for publication if it contains no novel content or is considered to contain grave errors. We hope that this will apply to a small number of papers only but we also need to respect a limit of maximum 200 published papers which may enforce more strict criteria. Paper rejection at this stage does not exclude poster presentation at the meeting itself as we assume that these authors will benefit from the feedback they can receive at the meeting. Accepted papers will receive comments for improvements and corrections from the reviewers. Submissions of the revised papers will be due in August. Criteria for selection as an oral presentation include perceived quality, the novelty of the research and the diversity and coherence of the overall program. 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. 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 begin of May. 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 200 papers will be published in the proceedings volume. For reference, papers presented at CNS*02 can be found in volumes 52-54 of Neurocomputing (2003). INVITED SPEAKERS Mary Kennedy (California Institute of Technology, USA) Miguel Nicolelis (Duke University, USA) TBA ORGANIZING COMMITTEE The CNS meeting is organized by the CNS Organization (http://www.cnsorg.org) presided by Christiane Linster (Cornell University, USA). Program chair: Erik De Schutter (University of Antwerp, Belgium) Local organizer: Asaf Keller (University of Maryland School of Medicine, USA) Workshop organizer: Adrienne Fairhall (Princeton University, USA) Government Liaison: Dennis Glanzman (NIMH/NIH, USA) and Yuan Liu (NINDS/NIH, USA) Program Committee : Nicolas Brunel (Universite Paris Rene Descartes, France) Alain Destexhe (CNRS Gif-sur-Yvette, France) Bill Holmes (Ohio University, USA) Hidetoshi Ikeno (Himeji Institute of Technology, Japan) Don H. Johnson (Rice University, USA) Leslie M. Kay (University of Chicago, USA) Barry Richmond (NIMH, USA) Eytan Ruppin (Tel Aviv University, Israel) Frances Skinner (Toronto Western Research Institute, Canada) ******************************************** Organization for Computational Neurosciences ******************************************** ----- End forwarded message ----- ******************************************** Organization for Computational Neurosciences ******************************************** From jean-marc.vesin at epfl.ch Mon Dec 22 12:26:24 2003 From: jean-marc.vesin at epfl.ch (JM Vesin) Date: Mon, 22 Dec 2003 18:26:24 +0100 Subject: JASP special issue on brain-computer interfaces Message-ID: <004001c3bb47$d8260bb0$e579b280@epfl.ch> Dear Colleague, You are a very active researcher in the field of brain-computer interfaces. This is why we take the liberty to draw your attention to a scheduled special issue on trends in brain-computer interfaces which will appear in the EURASIP Journal on Applied Signal Processing (JASP). The goal of this special issue is to present a broad overview of state of the art approaches to brain-computer communication with emphasis on signal processing issues. Topics of interest include, but are not limited to: EEG-based BCI systems Cortical activity based BCI systems BCI systems based on MEG, fMRI, . Pre-processing and feature extraction techniques for BCI systems Neural activity processing Protocols and evaluation methodologies for BCI systems Machine learning applied to BCI systems Applications of BCI systems in rehabilitation, entertainment, robotics, etc. Manuscript due data: January 31st 2004 Notification of acceptance: May 30th 2004 Final manuscript due: August 31st, 2004 Publication: Q1 2005 Guest editors: Dr. Jean-Marc Vesin Signal Processing Institute Swiss Federal Institute of Technology - EPFL CH-1015 Lausanne Email: Jean-Marc.Vesin at epfl.ch Prof. Touradj Ebrahimi Signal Processing Institute Swiss Federal Institute of Technology - EPFL CH-1015 Lausanne Email: Touradj.Ebrahimi at epfl.ch From rsun at rpi.edu Wed Dec 24 15:06:27 2003 From: rsun at rpi.edu (Professor Ron Sun) Date: Wed, 24 Dec 2003 15:06:27 -0500 (EST) Subject: Graduate assistantships available Message-ID: I am looking for a few Ph.D students. The Ph.D program of the Cognitive Science department at RPI is accepting applications. Graduate assistantships and other forms of financial support for graduate students are available. Prospective graduate students with interests in Cognitive Science, especially in learning and skill acquisition and in the relation between cognition and sociality, are encouraged to apply. Prospective applicants should have background in computer science (the equivalent of a BS in computer science), and have some prior exposure to artificial intelligence, connectionist models (neural networks), multi-agent systems, and other related areas. Students with a Master's degree already completed are preferred. RPI is a top-tier research university. This new department has identified the Ph.D program and research as its primary missions. The department is conducting research in a number of areas: computational cognitive modeling, human and machine learning, multi-agent interactions, neural networks and connectionist models, human and machine reasoning, artificial intelligence, cognitive engineering, and so on. See the Web page below regarding my research: http://wwww.cogsci.rpi.edu/~rsun For the application procedure, see http://www.cogsci.rpi.edu/ The application deadline is Jan.15, 2004. If you decide to apply, follow the official procedure as outlined on the Web page. Send me a short email (in plain text, ASCII) after you have completed the application. =================================================================== Professor Ron Sun Cognitive Science Department Rensselaer Polytechnic Institute 110 Eighth Street, Carnegie 302A Troy, NY 12180, USA phone: 518-276-3409 fax: 518-276-8268 email: rsun at rpi.edu web: http://www.cogsci.rpi.edu/~rsun =================================================================== From bogus@does.not.exist.com Wed Dec 24 05:33:14 2003 From: bogus@does.not.exist.com () Date: Wed, 24 Dec 2003 02:33:14 -0800 Subject: Jobs at Amazon.com in Seattle Message-ID: <6380910D0D66CA4C898665521C695D4D01C5C4D1@ex-mail-sea-01.ant.amazon.com> From pooyapakarian at ipm.ir Sun Dec 28 22:18:40 2003 From: pooyapakarian at ipm.ir (Pooya Pakarian) Date: Sun, 28 Dec 2003 19:18:40 -0800 Subject: Wagon wheel illusion Message-ID: Wagon-wheel illusion under steady illumination: real or illusory? Pooya Pakarian, Mohammad Taghi Yasamy Perception 2003, volume 32, number 11, pages 1307 - 1310 Abstract. Wheels turning in the movies sometimes appear to rotate backwards. This is called the wagon-wheel illusion (WWI). The mechanism of this illusion is based on the intermittent nature of light in films and other stroboscopic presentations, which renders them as a series of snapshots rather than a continuous visual data stream. However, there have been claims that this illusion is seen even in continuous light, which would suggest that the visual system itself may sample a continuous visual data stream. We examined the rate of this putative sampling and its variations across individuals while in different psychological states. We obtained two results: (i) WWI occurred in stroboscopic lights as expected, (ii) WWI was never reported by our subjects under continuous lights, such as sunlight and lamps with DC power source. Thus, WWI cannot be taken as evidence for discreteness of conscious visual perception. This article can be downloaded from http://www.perceptionweb.com/perc1103/ or easily just by contacting the corresponding author. ( pooyapakarian at ipm.ir, pooyapakarian at yahoo.com ) Pooya Pakarian,MD School of Cognitive Sciences(SCS) Institute for studies in theoretical Physics and Mathematics(IPM) Niavaran Sq., Tehran, Iran. P.O.Box 19395-5746 From jcid at tsc.uc3m.es Mon Dec 29 07:44:34 2003 From: jcid at tsc.uc3m.es (jcid@tsc.uc3m.es) Date: Mon, 29 Dec 2003 13:44:34 +0100 Subject: Visiting Professor at Carlos III University in Madrid. Message-ID: <40025407de.407de40025@tsc.uc3m.es> University Carlos III de Madrid Department of Signal Theory and Communications Visiting professor The Department of Signal Theory and Communications, University Carlos III de Madrid, Spain, invites applications for a Visiting Professor starting mid. Feb, 2004, to participate as a teacher in an english- speaking group of a course about decision and estimation theory (see program in http://www.uc3m.es/uc3m/gral/ES/ESCU2/0710719.html) for a degree on Telecommunication Engineer. Candidates with interests in decision making, estimation theory and neural networks are encouraged to apply. We seek applicants who have a strong research program and are committed to excellent teaching. Evaluation of candidates will begin January 12, 2004, and will continue until the position is filled. Applicants should submit an e-mail letter and a cv (pdf format) to: Jesus Cid-Sueiro (jcid at tsc.uc3m.es).