Information encoding in the inferior temporal visual cortex: contributions of the firing rates and the correlations between the firing of neurons

Abstract

The encoding of information by populations of neurons in the macaque inferior temporal cortex was analyzed using quantitative information-theoretic approaches. It was shown that almost all the information about which of 20 stimuli had been shown in a visual fixation task was present in the number of spikes emitted by each neuron, with stimulus-dependent cross-correlation effects adding for most sets of simultaneously recorded neurons almost no additional information. It was also found that the redundancy between the simultaneously recorded neurons was low, approximately 4% to 10%. Consistent with this, a decoding procedure applied to a population of neurons showed that the information increases approximately linearly with the number of cells in the population.

Invariant Representations of Objects in Natural Scenes in the Temporal Cortex Visual Areas

“…The implication of these results is that any stimulus-dependent synchrony that is present is not quantitatively important, as measured by information theoretical analyses under natural scene conditions; this has been found for the inferior temporal cortex, a brain region where features are put together to form representations of objects , and where attention has strong effects, at least in scenes with blank backgrounds (Rolls et al 2003a). The fi nding as assessed by information theoretical methods of the importance of fi ring rates and not stimulus-dependent synchrony is consistent with previous information theoretic approaches Rolls et al 2003bRolls et al , 2004. It would of course also be of interest to test the same hypothesis in earlier visual areas, such as V4, with quantitative, information theoretical, techniques.…”

“…In the research described by Panzeri et al (1999b), Rolls et al (2003b), and Franco et al (2004), we developed methods for measuring the information in the relative time of fi ring of simultaneously recorded neurons, which might be signifi cant if the neurons became synchronized to some but not other stimuli in a set, as postulated by Singer (1999). We found that for the set of cells currently available, almost all the information was available in the fi ring rates of the cells, and very little (not more than approximately 5% of the total information) was available about these static images in the relative time of fi ring of different simultaneously recorded neurons Panzeri et al 1999b;Rolls et al 2003bRolls et al , 2004. Thus, the evidence is that for representations of faces and objects Fig.…”

“…The analyses just described were obtained with neurons that were not simultaneously recorded, but we have more recently shown that with simultaneously recorded neurons similar results are obtained, that is, the information about which stimulus was shown increases approximately linearly with the number of neurons, showing that the neurons convey information that is nearly independent (Panzeri et al 1999b;Rolls et al 2004). [Consistently, Gawne and Richmond (1993) showed that even adjacent pairs of neurons recorded simultaneously from the same electrode carried information that was approximately 80% independent.]…”

“…Thus, at least where objects are represented in the visual, olfactory, and taste systems (e.g., individual faces, odors, and tastes), information can be read out without taking into account any aspects of the possible temporal synchronization between neurons, or temporal encoding within a spike train Franco et al 2004;Panzeri et al 1999b;Rolls et al 1997aRolls et al , 2003bRolls et al , 2004Tovee et al 1993). …”

Cortical coding

“…The analysis of the encoding of information by multiple single cells, for which we have developed methods Rolls et al, 2004;Rolls et al, 2003a;Rolls et al, 1997a), also has implications for understanding how local or distributed the encoding is by cortical neurons. The important point for the present purposes is that if the encoding was local (or grandmother cell-like), the number of stimuli encoded by a population of neurons would be expected to rise approximately linearly with the number of neurons in the population.…”