Concepts and Recent Advances in Generalized Information Measures and Statistics

1. Since the introduction of the information measure widely known as Shannon entropy, quantifiers based on information theory and concepts such as entropic forms and statistical complexities have ...
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Information-Theoretic Analysis of the Role of Correlations in Neural Spike Trains

Pp. 375-407 (33)

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.

Keywords:

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

Affiliation:

Instituto de Fisica La Plata, CONICET and Universidad Nacional de La Plata 115 y 49 C.C: 67 1900 La Plata Argentina