Travelling waves and EEG patterns during epileptic seizure: analysis with an integrate-and-fire neural network

Journal of Theoretical Biology
Mauro Ursino, Giuseppe-Emiliano La Cara

Abstract

Epilepsy is characterized by paradoxical patterns of neural activity. They may cause different types of electroencephalogram (EEG), which dynamically change in shape and frequency content during the temporal evolution of seizure. It is generally assumed that these epileptic patterns may originate in a network of strongly interconnected neurons, when excitation dominates over inhibition. The aim of this work is to use a neural network composed of 50 x 50 integrate-and-fire neurons to analyse which parameter alterations, at the level of synapse topology, may induce network instability and epileptic-like discharges, and to study the corresponding spatio-temporal characteristics of electrical activity in the network. We assume that a small group of central neurons is stimulated by a depolarizing current (epileptic focus) and that neurons are connected via a Mexican-hat topology of synapses. A signal representative of cortical EEG (ECoG) is simulated by summing the membrane potential changes of all neurons. A sensitivity analysis on the parameters describing the synapse topology shows that an increase in the strength and in spatial extension of excitatory vs. inhibitory synapses may cause the occurrence of travelling waves, which pr...Continue Reading

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Citations

Oct 19, 2010·Journal of Computational Neuroscience·Alexander HanuschkinMarkus Diesmann
Aug 22, 2012·Journal of Computational Neuroscience·Gleb BasalygaThomas Wennekers
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