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.
Keywords: Information Theory, Neural Code, Sampling bias correction, Spike correlations, Sensory encoding.
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