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Updated: Dec 27, 2025

Examining Local Network Processing using Multi-contact Laminar Electrode Recording
Published on: September 8, 2011
The effects of within-neuron degree correlations in networks of spiking neurons
Carlo R Laing1, Christian Bläsche2
1School of Natural and Computational Sciences, Massey University, NSMC, Private Bag 102-904, Auckland, New Zealand. c.r.laing@massey.ac.nz.
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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