Is cortical connectivity optimized for storing information?

Published

Journal Article

Cortical networks are thought to be shaped by experience-dependent synaptic plasticity. Theoretical studies have shown that synaptic plasticity allows a network to store a memory of patterns of activity such that they become attractors of the dynamics of the network. Here we study the properties of the excitatory synaptic connectivity in a network that maximizes the number of stored patterns of activity in a robust fashion. We show that the resulting synaptic connectivity matrix has the following properties: it is sparse, with a large fraction of zero synaptic weights ('potential' synapses); bidirectionally coupled pairs of neurons are over-represented in comparison to a random network; and bidirectionally connected pairs have stronger synapses on average than unidirectionally connected pairs. All these features reproduce quantitatively available data on connectivity in cortex. This suggests synaptic connectivity in cortex is optimized to store a large number of attractor states in a robust fashion.

Full Text

Duke Authors

Cited Authors

  • Brunel, N

Published Date

  • May 2016

Published In

Volume / Issue

  • 19 / 5

Start / End Page

  • 749 - 755

PubMed ID

  • 27065365

Pubmed Central ID

  • 27065365

Electronic International Standard Serial Number (EISSN)

  • 1546-1726

International Standard Serial Number (ISSN)

  • 1097-6256

Digital Object Identifier (DOI)

  • 10.1038/nn.4286

Language

  • eng