Analysis of the Neuron Dynamics in Thalamic Reticular Nucleus by a Reduced Model

Strategically located between the thalamus and the cortex, the inhibitory thalamic reticular nucleus (TRN) is a hub to regulate selective attention during wakefulness and control the thalamic and cortical oscillations during sleep. A salient feature of TRN neurons contributing to these functions is...

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Autores principales:	Chaoming Wang, Shangyang Li, Si Wu
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	thalamic reticular nucleus neuron model bursting tonic spiking bifurcation analysis phase plane analysis Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Acceso en línea:	https://doaj.org/article/d63960a60d7341c49c3dad8c327954ff
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spelling	oai:doaj.org-article:d63960a60d7341c49c3dad8c327954ff2021-11-16T05:16:12ZAnalysis of the Neuron Dynamics in Thalamic Reticular Nucleus by a Reduced Model1662-518810.3389/fncom.2021.764153https://doaj.org/article/d63960a60d7341c49c3dad8c327954ff2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fncom.2021.764153/fullhttps://doaj.org/toc/1662-5188Strategically located between the thalamus and the cortex, the inhibitory thalamic reticular nucleus (TRN) is a hub to regulate selective attention during wakefulness and control the thalamic and cortical oscillations during sleep. A salient feature of TRN neurons contributing to these functions is their characteristic firing patterns, ranging in a continuum from tonic spiking to bursting spiking. However, the dynamical mechanism under these firing behaviors is not well understood. In this study, by applying a reduction method to a full conductance-based neuron model, we construct a reduced three-variable model to investigate the dynamics of TRN neurons. We show that the reduced model can effectively reproduce the spiking patterns of TRN neurons as observed in vivo and in vitro experiments, and meanwhile allow us to perform bifurcation analysis of the spiking dynamics. Specifically, we demonstrate that the rebound bursting of a TRN neuron is a type of “fold/homo-clinic” bifurcation, and the tonic spiking is the fold cycle bifurcation. Further one-parameter bifurcation analysis reveals that the transition between these discharge patterns can be controlled by the external current. We expect that this reduced neuron model will help us to further study the complicated dynamics and functions of the TRN network.Chaoming WangChaoming WangChaoming WangShangyang LiSi WuSi WuFrontiers Media S.A.articlethalamic reticular nucleusneuron modelburstingtonic spikingbifurcation analysisphase plane analysisNeurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENFrontiers in Computational Neuroscience, Vol 15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	thalamic reticular nucleus neuron model bursting tonic spiking bifurcation analysis phase plane analysis Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
spellingShingle	thalamic reticular nucleus neuron model bursting tonic spiking bifurcation analysis phase plane analysis Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Chaoming Wang Chaoming Wang Chaoming Wang Shangyang Li Si Wu Si Wu Analysis of the Neuron Dynamics in Thalamic Reticular Nucleus by a Reduced Model
description	Strategically located between the thalamus and the cortex, the inhibitory thalamic reticular nucleus (TRN) is a hub to regulate selective attention during wakefulness and control the thalamic and cortical oscillations during sleep. A salient feature of TRN neurons contributing to these functions is their characteristic firing patterns, ranging in a continuum from tonic spiking to bursting spiking. However, the dynamical mechanism under these firing behaviors is not well understood. In this study, by applying a reduction method to a full conductance-based neuron model, we construct a reduced three-variable model to investigate the dynamics of TRN neurons. We show that the reduced model can effectively reproduce the spiking patterns of TRN neurons as observed in vivo and in vitro experiments, and meanwhile allow us to perform bifurcation analysis of the spiking dynamics. Specifically, we demonstrate that the rebound bursting of a TRN neuron is a type of “fold/homo-clinic” bifurcation, and the tonic spiking is the fold cycle bifurcation. Further one-parameter bifurcation analysis reveals that the transition between these discharge patterns can be controlled by the external current. We expect that this reduced neuron model will help us to further study the complicated dynamics and functions of the TRN network.
format	article
author	Chaoming Wang Chaoming Wang Chaoming Wang Shangyang Li Si Wu Si Wu
author_facet	Chaoming Wang Chaoming Wang Chaoming Wang Shangyang Li Si Wu Si Wu
author_sort	Chaoming Wang
title	Analysis of the Neuron Dynamics in Thalamic Reticular Nucleus by a Reduced Model
title_short	Analysis of the Neuron Dynamics in Thalamic Reticular Nucleus by a Reduced Model
title_full	Analysis of the Neuron Dynamics in Thalamic Reticular Nucleus by a Reduced Model
title_fullStr	Analysis of the Neuron Dynamics in Thalamic Reticular Nucleus by a Reduced Model
title_full_unstemmed	Analysis of the Neuron Dynamics in Thalamic Reticular Nucleus by a Reduced Model
title_sort	analysis of the neuron dynamics in thalamic reticular nucleus by a reduced model
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/d63960a60d7341c49c3dad8c327954ff
work_keys_str_mv	AT chaomingwang analysisoftheneurondynamicsinthalamicreticularnucleusbyareducedmodel AT chaomingwang analysisoftheneurondynamicsinthalamicreticularnucleusbyareducedmodel AT chaomingwang analysisoftheneurondynamicsinthalamicreticularnucleusbyareducedmodel AT shangyangli analysisoftheneurondynamicsinthalamicreticularnucleusbyareducedmodel AT siwu analysisoftheneurondynamicsinthalamicreticularnucleusbyareducedmodel AT siwu analysisoftheneurondynamicsinthalamicreticularnucleusbyareducedmodel
_version_	1718426694837075968

Analysis of the Neuron Dynamics in Thalamic Reticular Nucleus by a Reduced Model

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