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heterogeneous-timescales

topic1 events
papersTODAY 04:00 UTC

Random Matrix Theory Describes Sparse Neuronal Networks with Heterogeneous Timescales

A theoretical study models sparse recurrent networks of excitatory and inhibitory units whose time constants vary across the population, using random matrix theory to analyze their dynamics. The authors report that training such networks with additive noise on working memory tasks slows and diversifies inhibitory timescales, a change linked to improved task performance.

neuroscience/recurrent-networks/random-matrix-theory/working-memory