A Rate-Reduced Neuron Model for Complex Spiking Behavior

We present a simple rate-reduced neuron model that captures a wide range of complex, biologically plausible, and physiologically relevant spiking behavior. This includes spike-frequency adaptation, postinhibitory rebound, phasic spiking and accommodation, first-spike latency, and inhibition-induced...

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Autores principales: Dijkstra, Koen, Kuznetsov, Yuri A., van Putten, Michel J. A. M., van Gils, Stephan A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2017
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5725415/
https://www.ncbi.nlm.nih.gov/pubmed/29230566
http://dx.doi.org/10.1186/s13408-017-0055-3
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author Dijkstra, Koen
Kuznetsov, Yuri A.
van Putten, Michel J. A. M.
van Gils, Stephan A.
author_facet Dijkstra, Koen
Kuznetsov, Yuri A.
van Putten, Michel J. A. M.
van Gils, Stephan A.
author_sort Dijkstra, Koen
collection PubMed
description We present a simple rate-reduced neuron model that captures a wide range of complex, biologically plausible, and physiologically relevant spiking behavior. This includes spike-frequency adaptation, postinhibitory rebound, phasic spiking and accommodation, first-spike latency, and inhibition-induced spiking. Furthermore, the model can mimic different neuronal filter properties. It can be used to extend existing neural field models, adding more biological realism and yielding a richer dynamical structure. The model is based on a slight variation of the Rulkov map.
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spelling pubmed-57254152017-12-14 A Rate-Reduced Neuron Model for Complex Spiking Behavior Dijkstra, Koen Kuznetsov, Yuri A. van Putten, Michel J. A. M. van Gils, Stephan A. J Math Neurosci Research We present a simple rate-reduced neuron model that captures a wide range of complex, biologically plausible, and physiologically relevant spiking behavior. This includes spike-frequency adaptation, postinhibitory rebound, phasic spiking and accommodation, first-spike latency, and inhibition-induced spiking. Furthermore, the model can mimic different neuronal filter properties. It can be used to extend existing neural field models, adding more biological realism and yielding a richer dynamical structure. The model is based on a slight variation of the Rulkov map. Springer Berlin Heidelberg 2017-12-11 /pmc/articles/PMC5725415/ /pubmed/29230566 http://dx.doi.org/10.1186/s13408-017-0055-3 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Dijkstra, Koen
Kuznetsov, Yuri A.
van Putten, Michel J. A. M.
van Gils, Stephan A.
A Rate-Reduced Neuron Model for Complex Spiking Behavior
title A Rate-Reduced Neuron Model for Complex Spiking Behavior
title_full A Rate-Reduced Neuron Model for Complex Spiking Behavior
title_fullStr A Rate-Reduced Neuron Model for Complex Spiking Behavior
title_full_unstemmed A Rate-Reduced Neuron Model for Complex Spiking Behavior
title_short A Rate-Reduced Neuron Model for Complex Spiking Behavior
title_sort rate-reduced neuron model for complex spiking behavior
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5725415/
https://www.ncbi.nlm.nih.gov/pubmed/29230566
http://dx.doi.org/10.1186/s13408-017-0055-3
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