9h30-10h15 Intro to computational neuroscience
Presentation of the M1 Course C06
Presentation of the M2 Course-seminar
10h15-10h40 Presentation of the M2 Course CA6
10h40-11h: pause
11h-12h Short illustrative talks:
11h-11h20: "Matching law"
11h20-11h40: " Rescorla-Wagner learning rule"
11h40-12h: "Reinforcement learning"
12h-14h Students choose a paper and read it (and eat...)
14h-15h30: paper presentations and discussion

GENERAL REFERENCES

All the following books are available at the RISC library.
Most of them are also available at the library of Institut Henri Poincaré.

* Computational neuroscience books

Abbott and Dayan, "Theoretical Neuroscience" (MIT Press, 2001)

A nice overview of the field of computational neuroscience, at a level comparable to that of the course.

Tuckwell, "Introduction to Theoretical Neurobiology", Vols. I & II (Cambridge U. Press, 1988)

A more mathematical treatment, with narrower scope and emphasis on single-neuron dynamics and statistics of neural activity.

Koch, "Biophysics of Computation" (Oxford U. Press, 1999)

A detailed presentation of computational aspects of single-neuron behavior, closer to biology than Tuckwell's book (but more restricted in topics also).

Hertz, Krogh, and Palmer, "Introduction to the Theory of Neural Computation" (Addison-Wesley, 1991 - now from: Perseus Book Group and Westview Press)

A good reference book on memory models in the perspective of statistical physics (and on many other neural network models). This book is more advanced mathematically than the three other and a good resource for learning useful statistical physics techniques.

Rieke, Warland, de Ruyter van Steveninck, and Bialek, "Spikes" (MIT Press, 1997)

A nice introduction to the statistical and information theoretic approach to neural coding, with a title length inversely proportional to the number of authors.

* General neurobiology books:

Nicholls, Martin, Wallace, and Fuchs, "From Neurons to Brain" (Sinauer Associates, 2001, 4th ed.)

A readable and well-balanced introductory survey of neurobiology.

Kandel, Schwartz, and Jessel, "Principles of Neural Science" (McGraw-Hill, 4th edition, 2000)

Another successful neurobiology survey text.

Hubel, "Eye, Brain, and Vision" (Scientific American Library, 1988 and 1995)

A delightful introduction to visual processing by the brain, at an undergraduate/interested general reader level.

Johnston and Wu, "Foundations of Cellular Neurophysiology" (MIT Press, 1995)

A comprehensive introduction to the biophysics of neurons, with a quantitative leaning.

Fain, "Molecular and Cellular Physiology of Neurons" (Harvard University Press, 1999)

A nice very read on the physiology of single neurons and synapses, at an introductory level, with a lovely final part on sensory transduction.

* Periodicals:

A number of journals are devoted to computational neuroscience; these include Neural Computation, The Journal of Computational Neuroscience, Network: Computation in Neural Systems, Biological Cybernetics, Neural Networks. Other general or topical science journals also publish computational neuroscience articles; prominently, Nature, Nature Neuroscience, Science, Neuron, PNAS, PloS (free, online), The Journal of Physiology, The Journal of Neuroscience, The Journal of Neurophysiology, Cerebral Cortex, Vision Research, Trends in Neurosciences, Current Opinion in Neurobiology.