CUED Publications database

A Biologically Plausible Mechanism to Learn Clusters of Neural Activity

Loback, AR and Berry, MJ (2018) A Biologically Plausible Mechanism to Learn Clusters of Neural Activity. bioRxiv. (Unpublished)

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<jats:p>When correlations within a neural population are strong enough, neural activity in early visual areas is organized into a discrete set of clusters. Here, we show that a simple, biologically plausible circuit can learn and then readout in real-time the identity of experimentally measured clusters of retinal ganglion cell population activity. After learning, individual readout neurons develop <jats:italic>cluster tuning</jats:italic>, meaning that they respond strongly to any neural activity pattern in one cluster and weakly to all other inputs. Different readout neurons specialize for different clusters, and all input clusters can be learned, as long as the number of readout units is mildly larger than the number of input clusters. We argue that this operation can be repeated as signals flow up the cortical hierarchy.</jats:p>

Item Type: Article
Divisions: Div F > Control
Depositing User: Cron Job
Date Deposited: 28 Aug 2018 01:28
Last Modified: 19 Nov 2020 10:43
DOI: 10.1101/389155