MVA, Course by J.-P. Nadal: General bibliography

Jean-Pierre.Nadal [at]

phys.ens.fr

Laboratoire de Physique l'Ens

Ecole Normale Supérieure

24, rue Lhomond - 75005 Paris

and

Centre d'Analyse et de Mathématique Sociales

Ecole des Hautes Etudes en Sciences Sociales

54, bd. Raspail - 75006 Paris

Back to the course main page.

This page: Short bibliography and some important references

Most, if not all, books mentionned here may be found either online or at the IHP (Institut Henri Poincaré, 11 rue Pierre et Marie Curie, 75005 Paris), and at the RISC (Relais d'Information sur les Sciences de la Cognition, Ecole Normale Supérieure, 75005 Paris).

D. Amit, Modeling brain function (Cambridge Univ. Press, 1989) J. Hertz, A. Krogh & R. G. Palmer, Introduction to the theory of neural computation (Addison-Wesley, 1991) V. N. Vapnik, The nature of statistical learning theory (Springer, 1995, 2nd edition 2000) (online here) P. Dayan and LF Abbott, Theoretical Neuroscience (MIT Press 2001, 2nd edition 2005) - book online here. A nice overview of the field of computational neuroscience with a focus on Bayesian/information theoretic modeling approaches. Methods and Models in Neurophysics, Les Houches, Volume 80, 2005, Edited by C.C. Chow, B. Gutkin, D. Hansel, C. Meunier and J. Dalibard. See in particular Chap. 10: N. Brunel, Network models of memory (available here). B. Ermentrout and D. Terman, "Mathematical Foundations of Neuroscience" (Springer, 2010) (book with mathematical details on the the dynamics of neural activity) - online here. W. Gerstner, W. M. Kistler, R. Naud and L. Paninski, Neuronal Dynamics - From single neurons to networks and models of cognition, Cambridge University Press 2014 - book online with additional teaching material. In French: La cognition. Du neurone à la société, introduction aux sciences cognitives visant un public d'étudiants niveau master, ouvrage collectif sous la direction de Daniel Andler, Thérèse Collins et Catherine Tallon-Baudry, Collection Folio essais (n. 636), Série XL, Gallimard, 2018.

Blahut, R. E., Principles and Practice of Information Theory, Addison-Wesley 1988.
Cover, T. M. and Thomas, J. A., Information Theory, Wiley, 1991, 2nd edition 2006 (see Wiley online library).

Nicholls, Martin, Brown, Diamond, Weisblat and Fuchs, "From Neuron to Brain" (Sinauer Associates, 5th ed., 2011) (see Table of content here).
On the organization of the brain: M. Abeles, Corticonics (Cambridge Univ. Press, 1991)
Kandel, Schwartz, and Jessel, "Principles of Neural Science" (McGraw-Hill, 5th edition, 2012)

D. O. Hebb, The organization of behavior (Wiley, New-York, 1949) - available on Google Scholar, here.
On D. O. Hebb: R. E. Brown & P. M. Milner, "The Legacy Of Donald O. Hebb: More Than The Hebb Synapse", Nature reviews Neuroscience (2003)
W.S. McCulloch, W. A. Pitts, A logical calculus of the ideas immanent in nervous activity, Bull. Math. Biophys. 5 (1943) 115-133 (paper here)

H. B. Barlow, Possible principles underlying the transformations of sensory messages, 1961 (paper here). Horace Basil Barlow, born 8 December 1921, died 5 July 2020 - see Horace Barlow. Scientist of vision, Nature neuroscience, 07 September 2020.
F. Rosenblatt, 1958, "The perceptron: a probabilistic model for information storage and organization in the brain", paper on semanticscholar, here.
D. J. Willshaw, O. P. Buneman & H. C. Longuet-Higgins Non holographic associative memory, Nature 1969 (paper here)
M. Minsky, S. Papert, Perceptrons (Cambridge, MIT Press, 1969).

Articles (20th century)
J.J. Hopfield, Neural networks as physical systems with emergent computational abilities, Proc. Natl. Acad. Sci. USA, 79, 2554 (1982)

E. Gardner Maximum storage capacity of neural networks, Europhys. Letter 4, 481 (1987)

D. Amit, The Hebbian paradigm reintegrated: local reverberations as internal representations, Behavioral and Brain Sciences (BBS), vol. 4 (1995) 617-626 (paper here)

J. J. Atick, Could information theory provide an ecological theory of sensory processing, Network 3 (1992) 213-251

W. Bialek, F. Rieke, R. de Ruyter van Steveninck and D. Warland, Reading a neural code, Science 252 (1991) 1854-57
H. Gutfreund et G. Toulouse, Biology and Computation: a physicist's choice (World Scientific, 1994) [a selection of key papers]

Short reviews on two main topics of the course: modeling memory, sensory coding.
Recent (21st century) papers:
see references (that will be) given as course material for each class of the current academic year (eCampus website of the course for registered students).