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arXiv · 2004.00240

The effects of within-neuron degree correlations in networks of spiking neurons

Carlo R. Laing·Christian Blasche
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Abstract

We consider the effects of correlations between the in- and out-degrees of individual neurons on the dynamics of a network of neurons. By using theta neurons, we can derive a set of coupled differential equations for the expected dynamics of neurons with the same in-degree. A Gaussian copula is used to introduce correlations between a neuron's in- and out-degree and numerical bifurcation analysis is used determine the effects of these correlations on the network's dynamics. For excitatory coupling we find that inducing positive correlations has a similar effect to increasing the coupling strength between neurons, while for inhibitory coupling it has the opposite effect. We also determine the propensity of various two- and three-neuron motifs to occur as correlations are varied and give a plausible explanation for the observed changes in dynamics.

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Carlo R. Laing, Christian Blasche. 2020-04-01. The effects of within-neuron degree correlations in networks of spiking neurons. https://doi.org/10.1007/s00422-020-00822-0

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