Information-Theoretic Analysis of the Role of Correlations in Neural Spike Trains
Pp. 375-407 (33)
Fernando Montani and Simon R. Schultz
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.
Information Theory, Neural Code, Sampling bias correction, Spike correlations,
Instituto de Fisica La Plata, CONICET and Universidad Nacional de La Plata 115 y 49 C.C: 67 1900 La Plata Argentina