Is cortical connectivity optimized for storing information?
Abstract
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.
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https://hdl.handle.net/10161/23352Published Version (Please cite this version)
10.1038/nn.4286Publication Info
Brunel, Nicolas (2016). Is cortical connectivity optimized for storing information?. Nature neuroscience, 19(5). pp. 749-755. 10.1038/nn.4286. Retrieved from https://hdl.handle.net/10161/23352.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Nicolas Brunel
Duke School of Medicine Distinguished Professor in Neuroscience
We use theoretical models of brain systems to investigate how they process and learn
information from their inputs. Our current work focuses on the mechanisms of learning
and memory, from the synapse to the network level, in collaboration with various experimental
groups. Using methods fromstatistical physics, we have shown recently that the synapticconnectivity
of a network that maximizes storage capacity reproducestwo key experimentally observed
features: low connection proba

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