The Influence of Mexican Hat Recurrent Connectivity on Noise Correlations and Stimulus Encoding.

ABSTRACT: Noise correlations are a common feature of neural responses and have been observed in many cortical areas across different species. These correlations can influence information processing by enhancing or diminishing the quality of the neural code, but the origin of these correlations is still a matter of controversy. In this computational study we explore the hypothesis that noise correlations are the result of local recurrent excitatory and inhibitory connections. We simulated two-dimensional networks of adaptive spiking neurons with local connection patterns following Gaussian kernels. Noise correlations decay with distance between neurons but are only observed if the range of excitatory connections is smaller than the range of inhibitory connections ("Mexican hat" connectivity) and if t

SUBMITTER: Meyer R 

PROVIDER: S-EPMC5423970 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature