RT Journal Article
SR Electronic
T1 A Biologically Plausible Mechanism to Learn Clusters of Neural Activity
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 389155
DO 10.1101/389155
A1 Adrianna R. Loback
A1 Michael J. Berry II
YR 2018
UL http://biorxiv.org/content/early/2018/08/10/389155.abstract
AB 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 cluster tuning, 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.