Spatiotemporal discrimination in attractor networks with short-term synaptic plasticity.

ABSTRACT: We demonstrate that a randomly connected attractor network with dynamic synapses can discriminate between similar sequences containing multiple stimuli suggesting such networks provide a general basis for neural computations in the brain. The network contains units representing assemblies of pools of neurons, with preferentially strong recurrent excitatory connections rendering each unit bi-stable. Weak interactions between units leads to a multiplicity of attractor states, within which information can persist beyond stimulus offset. When a new stimulus arrives, the prior state of the network impacts the encoding of the incoming information, with short-term synaptic depression ensuring an itinerancy between sets of active units. We assess the ability of such a network to encode the identit

SUBMITTER: Ballintyn B 

PROVIDER: S-EPMC6571095 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature