54 research outputs found
Correlated connectivity and the distribution of firing rates in the neocortex
Two recent experimental observations pose a challenge to many cortical
models. First, the activity in the auditory cortex is sparse, and firing rates
can be described by a lognormal distribution. Second, the distribution of
non-zero synaptic strengths between nearby cortical neurons can also be
described by a lognormal distribution. Here we use a simple model of cortical
activity to reconcile these observations. The model makes the experimentally
testable prediction that synaptic efficacies onto a given cortical neuron are
statistically correlated, i.e. it predicts that some neurons receive many more
strong connections than other neurons. We propose a simple Hebb-like learning
rule which gives rise to both lognormal firing rates and synaptic efficacies.
Our results represent a first step toward reconciling sparse activity and
sparse connectivity in cortical networks
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