This document is intended to help newcomers to get into computational neuroscience. Note that this is a living document and it will regularly be updated. Offers of help to complete this are very welcome!
Computational modelling/theoretical neuroscience
- Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems, Peter Dayan and LF Abbott
- Methods in Neuronal Modeling: from Ions to Networks, C. Koch and I. Segev (eds.)
- Principles of Computational Modelling in Neuroscience, David Sterratt, Bruce Graham, Andrew Gillies and David Willshaw (eds.)
- Neuronal Dynamics - from single neurons to networks and models of cognition, Wulfram Gerstner, Werner M. Kistler, Richard Naud and Liam Paninski (freely available online!)
- Computational Neuroscience: Realistic Modeling for Experimentalists. E. De Schutter (ed.)
- Introduction To The Theory Of Neural Computation, John A. Hertz, Anders S. Krogh and Richard G. Palmer
- Vision: A Computational Investigation into the Human Representation and Processing of Visual Information, David Marr
- The handbook of brain theory and neural networks, Michael A. Arbib (ed.)
- Atick, J.J., 1992. Could information theory provide an ecological theory of sensory processing?. Network: Computation in neural systems, 3(2), pp.213-251.
- Oztop, E., Kawato, M. and Arbib, M., 2006. Mirror neurons and imitation: A computationally guided review. Neural Networks, 19(3), pp.254-271.
- Bower, J.M., 2013. 20 years of computational neuroscience. New York: Springer.
- Brette, R., Rudolph, M., Carnevale, T., Hines, M., Beeman, D., Bower, J.M., Diesmann, M., Morrison, A., Goodman, P.H., Harris Jr, F.C. and Zirpe, M., 2007. Simulation of networks of spiking neurons: a review of tools and strategies. Journal of computational neuroscience, 23(3), pp.349-398.
- Hodgkin, A.L. and Huxley, A.F., 1952. A quantitative description of membrane current and its application to conduction and excitation in nerve. The Journal of physiology, 117(4), p.500.
- McCulloch, W.S. and Pitts, W., 1943. A logical calculus of the ideas immanent in nervous activity. The bulletin of mathematical biophysics, 5(4), pp.115-133.
- Donald O.Hebb, The Organization of Behavior, New York: Wiley, Introduction and Chapter 4, "The first stage of perception: growth of the assembly," pp. xi-xix, 60-78.
- Lashley, K.S., 1950. In search of the engram.
- Von Neumann, J. and Kurzweil, R., 2012. The computer and the brain. Yale University Press.
- Rosenblatt, F., 1958. The perceptron: a probabilistic model for information storage and organization in the brain. Psychological review, 65(6), p.386
- Marr, D. and Poggio, T., 1976. Cooperative computation of stereo disparity. Science, 194(4262), pp.283-287.
- Grossberg, S., 1982. How does a brain build a cognitive code? In Studies of mind and brain (pp. 1-52). Springer Netherlands.
- Ackley, D.H., Hinton, G.E. and Sejnowski, T.J., 1985. A learning algorithm for Boltzmann machines. Cognitive science, 9(1), pp.147-169.
Open Source Brain projects
See here for a list of OSB projects which contain tutorials, exercises, etc. in computational neuroscience.
An overview of the main target simulators for models in Open Source Brain can be found here.
- Markup Languages
Libraries: Data analysis and scientific computing
Libraries: Data visualization
Libraries: Machine learning
- ModelDB: model database for computational neuroscience (ModelDB)
- Open Source Brain (OSB)
- Digitally Reconstructed Neuron Database (NeuroMorpho)
- Neuroscience Information Framework (NIF)
- Brain Operation Database System (BODB)
- BioModels Database (BioModels)
- Organization for Computational Neurosciences (OCNS)
- International Neuroinformatics Coordinating Facility (INCF)
Institutions, Laboratories and Research Groups
A more comprehensive list of labs, centers and researchers can be found here.
Mailing Lists, Blogs and News