Joy Bose: Research Related Resources - Computational Neuroscience

General Useful Links

• IEEE pdf express: www.ieee.org/pdfexpress
• Citeseer: citeseer.ist.psu.edu/cs
• Google Scholar: scholar.google.com
• Google Books: books.google.com
• Scholarpedia.org

Very Informative Site

COMPUTATIONAL NEUROSCIENCE on the World Wide Web

For Beginners to the Field

• Scientific American Book of the Brain: Very useful overview
• Scientific American: Memory: from Mind to Molecules
• Jeff Hawkins – On Intelligence: A very interesting read

General Textbooks

• Christopher M. Bishop – Neural Networks for Pattern Recognition: Oxford
• Simon Haykin – Neural Networks: A Comprehensive Foundation, 2nd edition: Prentice Hall.

Books for Prospective Researchers / PhD Students

• Neurocomputing (1 and 2) - Foundations of Research, Anderson and Rosenfield (editors): MIT Press. The seminal (original) papers of NN can be found at this book: Its probably best to search this in the library
• Handbook of Brain Theory and Neural Networks, Michael A. Arbib: MIT Press. This is a sort of neural nets encyclopedia

Websites

• Google Scholar: scholar.google.com
• Citeseer: citeseer.ist.psu.edu. A good place to look for references citations

For My Research

Search for the names below in Google or Google Scholar for more info. See citation indexes in Citeseer.

List of Books (Sorted by Publisher)

Some of these books have their own book sites. You can also try Amazon, Barnes and Noble, or publisher websites.

• Computational Neuroscience: Realistic Modeling for Experimentalists – Erik De Schutter, Robert C. Cannon
• Computational Neuroscience: A Comprehensive Approach – Jianfeng Feng. Chapman and Hall /CRC Press
• Computational Neuroscience: Trends in Research (1998, 1999...) – James M. Bower (Editor). Elsevier
• An Introduction to Dynamical Systems – R. Clark Robinson. Prentice Hall
• Neural Information Processing – Lecture Notes in Control and Information Sciences, vol. 172 – H. Tolle and E. Ersu
• Neurocontrol -- Learning Control Systems Inspired by Neuronal Architectures and Human Problem Solving Strategies, Lecture Notes in Control and Information Sciences, vol. 172, Springer-Verlag, 1992.
• Neural Networks for Modelling and Control of Dynamic Systems. by Magnus Norgaard, Ole Ravn, Niels K. Poulsen and Lars K. Hansen
• Modeling and Using Context. Third International and Interdisciplinary Conference, CONTEXT. 2001, Dundee, UK, July 27-30, 2001, Proceedings
• Brain Dynamics: Synchronization and Activity Patterns in Pulse-Coupled Neural Nets with Delays and Noise. Hermann Haken, H. Haken
• Computational Models for Neuroscience: Human Cortical Information Processing Robert Hecht-Nielsen, Thomas McKenna (Editor)
• Emergent Neural Computational Architectures based on Neuroscience Stefan Wermter, Jim Austin, David Willshaw available at www.his.sunderland.ac.uk/newbook/emernbook.html
• Sequence Learning: Paradigms, Algorithms, and Applications. Edited by: Ron Sun and Lee Giles
• From Computer to Brain. by William W. Lytton. Also a good introductory book
• Analog VLSI and Neural Systems, by Carver Mead. Seminal book
• Cognitive Neuroscience. SarahBanich Marie T. Pink, Marie T. Banich, Neil Cohen (Editor)
• The MIT Encyclopedia of the Cognitive Sciences. Robert Anton Wilson (Editor), Frank Keil (Editor)
• Neurocomputing (1 and 2) - Foundations of Research, MIT Press Anderson and Rosenfield (editors). For all the seminal papers related to NN
• Gateway to Memory: An Introduction to Neural Network Modeling of the Hippocampus and Learning (Issues in Clinical and Cognitive Neuropsychology). By Mark A. Gluck, Catherine E. Myers
• Computational Explorations in Cognitive Neuroscience: Understanding the Mind by Simulating the Brain. Randall C. O'Reilly and Yuko Munakata
• Principles of Neural Science. by Eric R. Kandel, James H. Schwartz, Thomas M. Jessell. Comprehensive leading book on neuroscience
• Frontiers in Cognitive Neuroscience. Edited by Stephen M. Kosslyn and Richard A. Andersen
• Sparse Distributed memory: Pentti Kanerva. Seminal book
• Pulsed Neural Networks, by Wolfgang Maass and Christopher M. Bishop, MIT Press. Very basic book about pulsed NN: covers whole area issues
• Theoretical Neuroscience by Dayan and Abbott (MIT Press). A comprehensive text, provides a thorough treatment of major modeling concepts in computational neuroscience. Also list of exercises etc
• Computational; Neuroscience: Schwartz (editor). Is rather old (published 1990)
• Neurophilosophy: Toward a Unified Science of the Mind-Brain. Patricia Smith Churchland, Patricia S. Churchland
• Neural Codes and Distributed Representations: Foundations of Neural Computation. Edited by Laurence Abbott and Terrence J. Sejnowski
• Computational Neuroscience Series of MIT Press (there are a lot more: see page for details)
• Spikes: Exploring the Neural Code. Fred Rieke, David Warland, Rob de Ruyter van Steveninck and William Bialek. Very interesting reading. How is the neural code formed with spikes?
• Neural Engineering: Computation, Representation, and Dynamics in Neurobiological Systems. Chris Eliasmith and Charles H. Anderson. Very good and novel approach towards engineering systems with neurons. Also nice course with exercises
• Neural Codes and Distributed Representations: Foundations of Neural Computation. Laurence Abbott and Terrence J. Sejnowski (Eds.)
• Methods in Neuronal Modeling - 2nd Edition From Ions to Networks. Christof Koch and Idan Segev (Eds.). More about low level models
• The Computational Brain. Patricia Churchland and Terrence J. Sejnowski
• Working Memory. Alan Baddeley
• NeuroDynamix: Computer Models for Neurophysiology. W. Otto Friesen and Jonathon A. Friesen
• Computational Neuroscience of Vision. Edmund T. Rolls, Gustavo Deco
• Biophysics of Computation: Information Processing in Single Neurons. Christof Koch
• Spikes, Decisions, and Actions - The Dynamical Foundations of Neuroscience: by Hugh Wilson. Great for foundations of dynamical systems built of spiking neurons
• Neural Networks and Brain Function. Edmund T. Rolls and Alessandro Treves. Very good for how different parts of the brain work, and can be modelled by Neural Networks
• Fundamentals of Computational Neuroscience. Thomas P. Trappenberg. Excellent introductory text. Well recommended to all
• Introduction to Theoretical Neurobiology Vol 1/2. Henry C Tuckwell
• Modeling Brain Function : The World of Attractor Neural Networks. By Daniel J. Amit
• Corticonics : Neural Circuits of the Cerebral Cortex. by Moshe Abeles
• Spiking Neuron Models: Single Neurons, Populations, Plasticity. by Wulfram Gerstner and Werner M. Kistler. Very detailed and comprehensive indeed. Must read. Available at http://diwww.epfl.ch/~gerstner/BUCH.html
• Nature Neuroscience Computational Supplement 2000 available at http://www.nature.com/neuro/supplements/index.html

List of Researchers

• Klaus Schulten
• Daniel Amit
• Arun Jagota
• Gerstner
• Edmund Rolls
• Terrence Sejnowski
• Peter Andras
• ... (many more)

List of Journals

• Advances in NIPS
• Annual Reviews Neuroscience
• Neural Networks
• Neural Computation
• Journal of Neuroscience
• Journal of Cognitive Neuroscience
• ... (many more)

Great Institutes / Schools / Departments

• Santa Fe Institute
• UCL
• MIT
• Cold Spring Harbour Labs
• HUJI Israel

Annual Conferences

• NIPS (Top)
• CNS (Computational Neuroscience Society)
• ICANN
• IJCNN
• ... (long list of conference names)

Simulators

• NEURON
• GENESIS
• NeuroML
• SpikeNNS
• MATLAB toolbox

Workshops and Seminar Series

• Telluride Neuromorphic Engineering Workshop
• UCL (Gatsby Unit)
• MIT Journal Clubs

Study Material Links

• Pitt Neuro Course
• UMD Teaching Page
• GENESIS Lecture Series

Fields of Study

• Neurodynamics
• Cognitive Science
• Neural Engineering
• Artificial Intelligence
• Neurophysiology
• Neuroinformatics

Mailing Lists and Discussion Groups

• comp-neuro@neuroinf.org
• comp.ai.neural-nets
• bionet.neuroscience

Societies

• Computational Neuroscience Society
• IEEE Computational Intelligence Society
• Society for Neuroscience (SFN)
• International Neural Networks Society