Complex patterns in networks of hyperexcitable neurons

Document Type

Article

Publication Date

6-20-2016

Abstract

Complex patterns in neuronal networks emerge from the cooperative activity of the participating neurons, synaptic connectivity and network topology. Several neuron types exhibit complex intrinsic dynamics due to the presence of nonlinearities and multiple time scales. In this paper we extend previous work on hyperexcitability of neuronal networks, a hallmark of epileptic brain seizure generation, which results from the net imbalance between excitation and inhibition and the ability of certain neuron types to exhibit abrupt transitions between low and high firing frequency regimes as the levels of recurrent AMPA excitation change. We examine the effect of different topologies and connection delays on the hyperexcitability phenomenon in networks having recurrent synaptic AMPA (fast) excitation (in the absence of synaptic inhibition) and demonstrate the emergence of additional time scales.

Identifier

84969497724 (Scopus)

Publication Title

Theoretical Computer Science

External Full Text Location

https://doi.org/10.1016/j.tcs.2015.05.051

ISSN

03043975

First Page

71

Last Page

82

Volume

633

Grant

1313861

Fund Ref

National Science Foundation

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