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- W3158820567 abstract "Understanding the connectivity observed in the brain and how it emerges from local plasticity rules is a grand challenge in modern neuroscience. In the primary visual cortex (V1) of mice, synapses between excitatory pyramidal neurons and inhibitory parvalbumin-expressing (PV) interneurons tend to be stronger for neurons that respond to similar stimulus features, although these neurons are not topographically arranged according to their stimulus preference. The presence of such excitatory-inhibitory (E/I) neuronal assemblies indicates a stimulus-specific form of feedback inhibition. Here, we show that activity-dependent synaptic plasticity on input and output synapses of PV interneurons generates a circuit structure that is consistent with mouse V1. Computational modeling reveals that both forms of plasticity must act in synergy to form the observed E/I assemblies. Once established, these assemblies produce a stimulus-specific competition between pyramidal neurons. Our model suggests that activity-dependent plasticity can refine inhibitory circuits to actively shape cortical computations." @default.
- W3158820567 created "2021-05-10" @default.
- W3158820567 creator A5015039578 @default.
- W3158820567 creator A5034199903 @default.
- W3158820567 creator A5040105095 @default.
- W3158820567 date "2021-04-26" @default.
- W3158820567 modified "2023-10-02" @default.
- W3158820567 title "Learning excitatory-inhibitory neuronal assemblies in recurrent networks" @default.
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- W3158820567 doi "https://doi.org/10.7554/elife.59715" @default.
- W3158820567 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8075581" @default.
- W3158820567 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33900199" @default.
- W3158820567 hasPublicationYear "2021" @default.
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