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The ability of prefrontal cortex to quickly encode novel associations is crucial for adaptive behavior and central to working memory. Fast Hebbian changes in synaptic strength permit forming new associations, but neuronal signatures of this have been elusive. We devised a trialwise index of pattern similarity to look for rapid changes in population codes. Based on a computational model of working memory, we hypothesized that synaptic strength-and consequently, the tuning of neurons-could change if features of a subsequent stimulus need to be "reassociated," i.e., if bindings between features need to be broken to encode the new item. As a result, identical stimuli might elicit different neural responses. As predicted, neural response similarity dropped following rebinding, but only in prefrontal cortex. The history-dependent changes were expressed on top of traditional, fixed selectivity and were not explainable by carryover of previous firing into the current trial or by neural adaptation.

More information Original publication

DOI

10.1073/pnas.2200400119

Type

Journal article

Publication Date

2022-10-04T00:00:00+00:00

Volume

119

Keywords

computational model of working memory, history-dependent neural selectivity, prefrontal cortex, synaptic plasticity, working memory, Memory, Short-Term, Models, Neurological, Neurons, Prefrontal Cortex, Synapses