Randomly connected networks generate emergent selectivity and predict decoding properties of large populations of neurons.

ABSTRACT: Modern recording methods enable sampling of thousands of neurons during the performance of behavioral tasks, raising the question of how recorded activity relates to theoretical models. In the context of decision making, functional connectivity between choice-selective cortical neurons was recently reported. The straightforward interpretation of these data suggests the existence of selective pools of inhibitory and excitatory neurons. Computationally investigating an alternative mechanism for these experimental observations, we find that a randomly connected network of excitatory and inhibitory neurons generates single-cell selectivity, patterns of pairwise correlations, and the same ability of excitatory and inhibitory populations to predict choice, as in experimental observations. Furthe

SUBMITTER: Sederberg A 

PROVIDER: S-EPMC7237045 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature