Decorrelation by recurrent inhibition in heterogeneous neural circuits

Biology – Quantitative Biology – Neurons and Cognition

Scientific paper

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26 pages, 6 figures

Scientific paper

The activity of cortical neurons is correlated, and this correlation affects how the brain processes information. What are the neural circuit mechanisms underlying correlations? Shared synaptic input is necessary to synchronize neurons, but it may not be sufficient if neural circuits are heterogeneous. We study the neural circuit mechanisms of correlations by analyzing a network model characterized by strong and heterogeneous interactions. We consider strong excitatory and inhibitory connections: the excitatory input drives the fluctuations of neural activity, which are counterbalanced by the inhibitory feedback. While the strong excitatory input tends to correlate neurons, the inhibitory feedback strongly reduces the correlations. Crucially, the heterogeneity of synaptic connections is necessary for the inhibition of correlations. Under these conditions, we found that correlations are positive and of magnitude K^{-1/2}, where K is the number of connections to a neuron. The result agrees with anatomical and physiological measurements in the cortex: a cortical neuron receives about K \simeq 10^4 connections, and the measured correlations are about 10^{-2}.

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