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作者机构:Graduate Program in Science-Physics State University of Ponta Grossa Ponta Grossa84030-900 Institute of Physics University of Saõ Paulo Saõ Paulo05508-900 Brazil Department of Physics State University of Ponta Grossa Ponta Grossa84030-900 Center ForMathematics Computation and Cognition Federal University of ABC Sao Bernardo do Campo09606-045 Department of Mathematics Federal University of Technology Paraná Ponta Grossa84016-210 Department of Mathematics and Statistics State University of Ponta Grossa Ponta Grossa84030-900 Faculdade de Telêmaco Borba FATEB Telemaco Borba84266-010 Brazil Department of Mathematical Sciences University of Essex Wivenhoe ParkCO43SQ United Kingdom Department of Applied Mathematics Northwestern Polytechnical University Xi'an710072 Department of Physics Federal University of Paraná Curitiba82590-300 Brazil
出 版 物:《arXiv》 (arXiv)
年 卷 期:2020年
核心收录:
主 题:Neurons
摘 要:Noise appears in the brain due to various sources, such as ionic channel fluctuations and synaptic events. They affect the activities of the brain and influence neuron action potentials. Stochastic differential equations have been used to model firing patterns of neurons subject to noise. In this work, we consider perturbing noise in the adaptive exponential integrate-and-fire (AEIF) neuron. The AEIF is a two-dimensional model that describes different neuronal firing patterns by varying its parameters. Noise is added in the equation related to the membrane potential. We show that a noise current can induce continuous and noncontinuous transitions in neuronal interspike intervals. Moreover, we show that the noncontinuous transition occurs mainly for parameters close to the border between tonic spiking and burst activities of the neuron without noise. Copyright © 2020, The Authors. All rights reserved.