Synchronised firing patterns in a random network of adaptive exponential integrate-and-fire neuron model

We have studied neuronal synchronisation in a random network of adaptive exponential integrate-and-fire neurons. We study how spiking or bursting synchronous behaviour appears as a function of the coupling strength and the probability of connections, by constructing parameter spaces that identify th...

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Published inNeural networks Vol. 90; pp. 1 - 7
Main Authors Borges, F.S., Protachevicz, P.R., Lameu, E.L., Bonetti, R.C., Iarosz, K.C., Caldas, I.L., Baptista, M.S., Batista, A.M.
Format Journal Article
LanguageEnglish
Published United States Elsevier Ltd 01.06.2017
Subjects
Action Potentials - physiology
Humans
Integrate-and-fire
Models, Neurological
Network
Neural Networks (Computer)
Neurons - physiology
Probability
Synchronisation
Synchronisation
Integrate-and-fire
Network
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Summary:We have studied neuronal synchronisation in a random network of adaptive exponential integrate-and-fire neurons. We study how spiking or bursting synchronous behaviour appears as a function of the coupling strength and the probability of connections, by constructing parameter spaces that identify these synchronous behaviours from measurements of the inter-spike interval and the calculation of the order parameter. Moreover, we verify the robustness of synchronisation by applying an external perturbation to each neuron. The simulations show that bursting synchronisation is more robust than spike synchronisation.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0893-6080
1879-2782
DOI:10.1016/j.neunet.2017.03.005