Interpretation of correlated neural variability from models of feed-forward and recurrent circuits.

ABSTRACT: Neural populations respond to the repeated presentations of a sensory stimulus with correlated variability. These correlations have been studied in detail, with respect to their mechanistic origin, as well as their influence on stimulus discrimination and on the performance of population codes. A number of theoretical studies have endeavored to link network architecture to the nature of the correlations in neural activity. Here, we contribute to this effort: in models of circuits of stochastic neurons, we elucidate the implications of various network architectures-recurrent connections, shared feed-forward projections, and shared gain fluctuations-on the stimulus dependence in correlations. Specifically, we derive mathematical relations that specify the dependence of population-averaged co

SUBMITTER: Pernice V 

PROVIDER: S-EPMC5833435 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature