Information analyses of both single neurons and, through decoding procedures, of populations of neurons, have been applied to recordings from the lab of Edmund Rolls (including monkey visual cortex [6,7] and orbito-frontal cortex ), and seminal collaborations have been initiated with other labs, including that of Mathew Diamond [3,8].
Subsequent work has focused on the short time limit , that allows the accurate quantification of the effects of decoding [9,17] and of correlations among simultaneously recorded cells ; interactions among different neurons have also been analyzed in terms of firing coincidences (VdP with Laura Martignon). We have then analyzed how the information about a set of discrete stimuli depends on the size of the neuronal population, both in the short time limit for correlated units  and over finite times with uncorrelated units , leading to a validation of the simple Gawne & Richmond model (reviewed in : the figure to the left shows how the ceiling alone captures most of the redundancy when a population of IT units has to discriminate between 4, 9 or 20 face stimuli). Stimulated by a collaboration with Eilon Vaadia, we have explored the coding of more structured stimuli, with both a discrete and a continuous dimension, at the level of theoretical modelling [13,15] and in real neurons recorded from the motor cortex of monkeys performing bimanual movements . Recently we have extended decoding procedures to deal with the contribution of correlations [18,19].
The most recent developments are in connection with the hippocampal recordings in the lab of May-Britt and Edvard Moser, which required information measures obtained without explicit reference to the salient correlate, the position of the rat in the environment. We developed measures based on the distribution of population vectors, obtained from the spike counts over short time bins by simultaneously recorded units . Such measures can be used to assess information content about spatial position, spatial context, etc.
Work in progress applies simplified network models and replica techniques [12, 15] to estimate measures of information content in newly stored spatial representations (EC, AT).