Alexandre POUGET (University of Rochester)
Neural Coding and Decoding

Thursdays 4:15pm - 6:15 pm, January 10 - February 21.

Zhaoping LI and Peter DAYAN (University College London)
Introduction to Computational Neuroscience

Xiao-Jing WANG (Brandeis University)
Single neuron and network dynamics

January Friday 18, 2pm-4pm: Single neuron dynamics and computation I
January Friday 25, 2pm-4pm: Single neuron dynamics and computation II
February Friday 1, 2pm-4pm: Network rhythms I
February Friday 8, 2pm-4pm: Network rhythms II
February Monday 18, 2pm-4pm, lecture given by Idan SEGEV (Jerusalem): The Neuron Doctrine: From Cajal to Rall
March Friday 8, 2pm-4pm: Working memory I
March Friday 15, 10am-12am: Working memory II

Misha TSODYKS (Weizmann Institute of Science)
Plasticity, and coding by neural assemblies

February Friday 1, 4:15pm-6:15pm: Transmission via neocortical synapses - short term plasticity
February Friday 8, 10am-12am: Transmission via neocortical synapses - long term plasticity
March Friday 1rst, 2pm-4pm: Attractor networks. Discrete and continuous attractors
March Friday 8, 10am-12am: Population activity and orientation selectivity in the visual cortex
March Monday 11, 2pm-4pm: Population activity, perception and perceptual learning in the visual system
March Friday 15, 2pm-4pm: Neural synchrony and feature processing in recurrent networks

Michel TALAGRAND (Department of Mathematics, Ohio State University)
Formal neural networks: exact results

The purpose of the course is to explain the nature of the methods that allow to obtain rigorous results for mean field models for disordered systems. We will explain what has already been proved for neural networks, and the obstacles to overcome for further progress. The most important method is the cavity method. The main obstacle to use it rogorously is that the error terms arising fron the use of this method are very difficult to control. We will also explain the use of other tools, and in particular of concentration of measure.

Yves FREGNAC (Gif) and David McCORMICK (Yale University School of Medicine)
Dynamics of Neural Networks

Program:
I. Neuronal excitability and fast adaptation in synaptic transmission (D. McCormick)
II. Dynamics of conductances and small networks (A. Destexhe and T. Bal)
III. Spatio-temporal dynamics of oscillations in the CNS (T. Bal and A. Destexhe)
IV. Plasticity of cortical representations (Y. Frégnac)

Eberhard FETZ
(University of Washington, Seattle, and Invited Professor at Collège de France)

Lecture 1: "Control of forelimb muscle activity by cortical and spinal premotor neurons in behaving primates"
Lecture 2: "Role of spinal interneurons in preparation and execution of voluntary movements"
Lecture 3: "Mechanisms and function of synchrony and gamma oscillations in the primate motor cortex"
Lecture 4: "Dynamic recurrent neural network models of sensorimotor behavior"

The two first lectures will be given at Collège de France (11, place Marcelin-Berthelot, Paris 5e), on March, Tuesdays 12 and 26, 4:30 pm., Room 5;
Lectures 3 and 4 will be given at Institut Henri Poincaré, amphithéâtre Hermite on April 3 and 10, 4:30 p.m.

Nota for the French students: