The use of decoding to analyze the contribution to the information of the correlations between the firing of simultaneously recorded neurons

Abstract

A new decoding method is described that enables the information that is encoded by simultaneously recorded neurons to be measured. The algorithm measures the information that is contained not only in the number of spikes from each neuron, but also in the cross-correlations between the neuronal firing including stimulus-dependent synchronization effects. The approach enables the effects of interactions between the 'signal' and 'noise' correlations to be identified and measured, as well as those from stimulus-dependent cross-correlations. The approach provides an estimate of the statistical significance of the stimulus-dependent synchronization information, as well as enabling its magnitude to be compared with the magnitude of the spike-count related information, and also whether these two contributions are additive or redundant. The algorithm operates even with limited numbers of trials. The algorithm is validated by simulation. It was then used to analyze neuronal data from the primate inferior temporal visual cortex. The main conclusions from experiments with two to four simultaneously recorded neurons were that almost all of the information was available in the spike counts of the neurons; that this Rate information included on average very little redundancy arising from stimulus-independent correlation effects; and that stimulus-dependent cross-correlation effects (i.e. stimulus-dependent synchronization) contribute very little to the encoding of information in the inferior temporal visual cortex about which object or face has been presented.

Role of Spike Timing in the Forelimb Somatosensory Cortex of the Rat

“…The maximum number of neurons used was 28. The smooth and sublinear performance increase when adding neurons reveals information redundancy within the ensembles in this simple task (Franco et al, 2004) and supports the idea of distributed processing in the somatosensory cortex (Nicolelis et al, 1998;Ghazanfar et al, 2000). into the temporal precision of the somatosensory code.…”

“…However, previous studies in the whisker cortex suggested that these correlations play minor roles in the somatosensory code (Ghazanfar et al, 2000;Petersen et al, 2001) and that stimulusdependent changes in correlation convey almost no information about stimulus location , which allows a decoder that neglects correlation to extract virtually 100% of the encoded information . Nevertheless, the redundancy we found in ensembles of neurons, as revealed by the sublinear increase of information as the number of neurons increased (Franco et al, 2004), does reflect correlation between neurons as absence of "information independence" (Schneidman et al, 2003) and can be related to the "signal similarity" described in the whisker cortex Pola et al, 2003). Importantly, information theoretic redundancy should be carefully interpreted within the specific boundaries of the experiment, because it could reflect low entropy of the stimulus set chosen (Rolls et al, 1997) rather than actual redundancy in the somatosensory code.…”

“…Complete cross-validation is particularly efficient using the PSTH-based classification method (for details, see Foffani and Moxon, 2004). For each ensemble, classification performance was evaluated by using two measures: (1) the total percentage of trials correctly classified and (2) the bits of mutual information between predicted and actual stimuli, computed from the confusion matrix of the classification (Gochin et al, 1994;Rolls et al, 1997Rolls et al, , 1998Panzeri et al, 1999;Laubach et al, 2000;Gruner, 2002;Franco et al, 2004). Perfect classification would lead to 100% of trials correctly classified and 3.32 bits (i.e., log 2 10) of mutual information.…”

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

“…[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.] 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, 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). …”