Correlated connectivity and the distribution of firing rates in the neocortex. Koulakov, A., A., Hromádka, T., & Zador, A., M. The Journal of neuroscience : the official journal of the Society for Neuroscience, 29(12):3685-3694, 3, 2009.
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Paper Website abstract bibtex 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 nonzero 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 stronger synapses than other neurons. We propose a simple Hebb-like learning rule that gives rise to such correlations and yields 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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