Chapter 15

Information-Theoretic Analysis of the Role of Correlations in Neural Spike Trains

Fernando Montani and Simon R. Schultz

Abstract

We have applied an information theoretic approach to gain insights of the role of spike correlations in the neuronal code. First, we illustrate and compare the different methods used in the literature to remove sample size dependent bias from information estimations. Then, we use a modified version of the information components breakdown to quantify the contribution of individual members of the population, the interaction between them, and the overall information encoded by the ensemble of neurons making an especial emphasis of the separation between contributions due to the noise and signal spike correlations. This formalism is applied to a set of multi-neuronal spike data with different stimuli configurations.

Total Pages: 375-407 (33)

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