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		<doi>10.3389/fncom.2019.00019</doi>
		<issn>1662-5188</issn>
		<citationkey>ProtacheviczBLJIKCSBMABK:2019:BiFiPa</citationkey>
		<title>Bistable firing pattern in a neural network model</title>
		<year>2019</year>
		<month>Feb.</month>
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		<author>Protachevicz, Paulo R.,</author>
		<author>Borges, Fernando S.,</author>
		<author>Lameu, Ewandson Luiz,</author>
		<author>Ji, Peng,</author>
		<author>Iarosz, Kelly c.,</author>
		<author>Kihara, Alexandre H.,</author>
		<author>Caldas, Ibere L.,</author>
		<author>Szezech Junior, José D.,</author>
		<author>Baptista, Murilo S.,</author>
		<author>Macau, Elbert Einstein Nehrer,</author>
		<author>Antonopoulos, Chris G.,</author>
		<author>Batista, Antonio M.,</author>
		<author>Kuths, Jurgen,</author>
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		<affiliation>Universidade Estadual de Ponta Grossa</affiliation>
		<affiliation>Universidade Federal do ABC (UFABC)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Fudan University</affiliation>
		<affiliation>Universidade de São Paulo (USP)</affiliation>
		<affiliation>Universidade Federal do ABC (UFABC)</affiliation>
		<affiliation>Universidade de São Paulo (USP)</affiliation>
		<affiliation>Universidade Estadual de Ponta Grossa</affiliation>
		<affiliation>University of Aberdeen</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>University of Essex</affiliation>
		<affiliation>Universidade Estadual de Ponta Grossa</affiliation>
		<affiliation>Potsdam Institute for Climate Impact Research</affiliation>
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		<electronicmailaddress>elbert.macau@inpe.br</electronicmailaddress>
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		<electronicmailaddress>kurths@pik-potsdam.de</electronicmailaddress>
		<journal>Frontiers in Computational Neuroscience</journal>
		<volume>13</volume>
		<transferableflag>1</transferableflag>
		<contenttype>External Contribution</contenttype>
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		<keywords>bistable regime, network, adaptive exponential integrate-and-fire neural model, neural dynamics, synchronization, epilepsy.</keywords>
		<abstract>Excessively high, neural synchronization has been associated with epileptic seizures, one of the most common brain diseases worldwide. A better understanding of neural synchronization mechanisms can thus help control or even treat epilepsy. In this paper, we study neural synchronization 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 synchronization originating from a pattern of desynchronized 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) synchronization, a process that can reproduce features of epileptic seizures. Then, we show that it is possible to suppress such abnormal synchronization by applying a small-amplitude external current on > 10% of the neurons in the network. Our results demonstrate that external electrical stimulation not only can trigger synchronous behavior, but more importantly, it can be used as a means to reduce abnormal synchronization and thus, control or treat effectively epileptic seizures.</abstract>
		<area>COMP</area>
		<language>en</language>
		<targetfile>fncom-13-00019.pdf</targetfile>
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