Research Repository

Bistable firing pattern in a neural network model

Protachevicz, Paulo Ricardo and da Silva Borges, Fernando and Lameu, Ewandson Luiz and Ji, Peng and Iarosz, Kelly Cristiane and Kihara, Alexandre Hiroaki and Caldas, Ibere Luiz and Szezech, Jose Danilo and Baptista, Murilo S and Macau, Elbert EN and Antonopoulos, Chris and Batista, Antonio Marcos and Kurths, Jurgen (2019) 'Bistable firing pattern in a neural network model.' Frontiers in Computational Neuroscience, 13 (19). ISSN 1662-5188

[img]
Preview
Text
fncom-13-00019.pdf - Published Version
Available under License Creative Commons Attribution.

Download (4MB) | Preview

Abstract

Excessively high, neural synchronisation has been associated with epileptic seizures, one of the most common brain diseases worldwide. A better understanding of neural synchronisation mechanisms can thus help control or even treat epilepsy. In this paper, we study neural synchronisation in a random network where nodes are neurons with excitatory and inhibitory synapses, and neural activity for each node is provided by the adaptive exponential integrate-and-fire model. In this framework, we verify that the decrease in the influence of inhibition can generate synchronisation originating from a pattern of desynchronised spikes. The transition from desynchronous spikes to synchronous bursts of activity, induced by varying the synaptic coupling, emerges in a hysteresis loop due to bistability where abnormal (excessively high synchronous) regimes exist. We verify that, for parameters in the bistability regime, a square current pulse can trigger excessively high (abnormal) synchronisation, a process that can reproduce features of epileptic seizures. Then, we show that it is possible to suppress such abnormal synchronisation by applying a small-amplitude external current on less than 10\% of the neurons in the network. Our results demonstrate that external electrical stimulation not only can trigger synchronous behaviour, but more importantly, it can be used as a means to reduce abnormal synchronisation and thus, control or treat effectively epileptic seizures

Item Type: Article
Uncontrolled Keywords: Bistable regime, Networks, Adaptive exponential integrate-and-fire neural model, Neural dynamics, Synchronisation, Epilepsy
Subjects: R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Divisions: Faculty of Science and Health > Mathematical Sciences, Department of
Depositing User: Elements
Date Deposited: 05 Apr 2019 08:56
Last Modified: 05 Apr 2019 08:56
URI: http://repository.essex.ac.uk/id/eprint/24220

Actions (login required)

View Item View Item