Dense neuron clustering explains connectivity statistics in cortical microcircuits.

ABSTRACT: Local cortical circuits appear highly non-random, but the underlying connectivity rule remains elusive. Here, we analyze experimental data observed in layer 5 of rat neocortex and suggest a model for connectivity from which emerge essential observed non-random features of both wiring and weighting. These features include lognormal distributions of synaptic connection strength, anatomical clustering, and strong correlations between clustering and connection strength. Our model predicts that cortical microcircuits contain large groups of densely connected neurons which we call clusters. We show that such a cluster contains about one fifth of all excitatory neurons of a circuit which are very densely connected with stronger than average synapses. We demonstrate that such clustering plays an i

SUBMITTER: Klinshov VV 

PROVIDER: S-EPMC3986068 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature