Adaptation Reduces Variability of the Neuronal Population Code

Physics – Biological Physics

Scientific paper

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4 pages, 2 figures

Scientific paper

10.1103/PhysRevE.83.050905

Sequences of events in noise-driven excitable systems with slow variables often show serial correlations among their intervals of events. Here, we employ a master equation for general non-renewal processes to calculate the interval and count statistics of superimposed processes governed by a slow adaptation variable. For an ensemble of spike-frequency adapting neurons this results in the regularization of the population activity and an enhanced post-synaptic signal decoding. We confirm our theoretical results in a population of cortical neurons.

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