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Behavioral Context Determines Network State and Variability Dynamics in Monkey Motor Cortex
Variability of spiking activity is ubiquitous throughout the brain but little is known about its contextual dependance. Trial-to-trial spike count variability, estimated by the Fano Factor (FF), and within-trial spike time irregularity, quantified by the coefficient of variation (CV), reflect variab...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6052126/ https://www.ncbi.nlm.nih.gov/pubmed/30050415 http://dx.doi.org/10.3389/fncir.2018.00052 |
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author | Riehle, Alexa Brochier, Thomas Nawrot, Martin Grün, Sonja |
author_facet | Riehle, Alexa Brochier, Thomas Nawrot, Martin Grün, Sonja |
author_sort | Riehle, Alexa |
collection | PubMed |
description | Variability of spiking activity is ubiquitous throughout the brain but little is known about its contextual dependance. Trial-to-trial spike count variability, estimated by the Fano Factor (FF), and within-trial spike time irregularity, quantified by the coefficient of variation (CV), reflect variability on long and short time scales, respectively. We co-analyzed FF and the local coefficient of variation (CV2) in monkey motor cortex comparing two behavioral contexts, movement preparation (wait) and execution (movement). We find that the FF significantly decreases from wait to movement, while the CV2 increases. The more regular firing (expressed by a low CV2) during wait is related to an increased power of local field potential (LFP) beta oscillations and phase locking of spikes to these oscillations. In renewal processes, a widely used model for spiking activity under stationary input conditions, both measures are related as FF ≈ CV(2). This expectation was met during movement, but not during wait where FF ≫ CV2(2). Our interpretation is that during movement preparation, ongoing brain processes result in changing network states and thus in high trial-to-trial variability (expressed by a high FF). During movement execution, the network is recruited for performing the stereotyped motor task, resulting in reliable single neuron output. Our interpretation is in the light of recent computational models that generate non-stationary network conditions. |
format | Online Article Text |
id | pubmed-6052126 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-60521262018-07-26 Behavioral Context Determines Network State and Variability Dynamics in Monkey Motor Cortex Riehle, Alexa Brochier, Thomas Nawrot, Martin Grün, Sonja Front Neural Circuits Neuroscience Variability of spiking activity is ubiquitous throughout the brain but little is known about its contextual dependance. Trial-to-trial spike count variability, estimated by the Fano Factor (FF), and within-trial spike time irregularity, quantified by the coefficient of variation (CV), reflect variability on long and short time scales, respectively. We co-analyzed FF and the local coefficient of variation (CV2) in monkey motor cortex comparing two behavioral contexts, movement preparation (wait) and execution (movement). We find that the FF significantly decreases from wait to movement, while the CV2 increases. The more regular firing (expressed by a low CV2) during wait is related to an increased power of local field potential (LFP) beta oscillations and phase locking of spikes to these oscillations. In renewal processes, a widely used model for spiking activity under stationary input conditions, both measures are related as FF ≈ CV(2). This expectation was met during movement, but not during wait where FF ≫ CV2(2). Our interpretation is that during movement preparation, ongoing brain processes result in changing network states and thus in high trial-to-trial variability (expressed by a high FF). During movement execution, the network is recruited for performing the stereotyped motor task, resulting in reliable single neuron output. Our interpretation is in the light of recent computational models that generate non-stationary network conditions. Frontiers Media S.A. 2018-07-12 /pmc/articles/PMC6052126/ /pubmed/30050415 http://dx.doi.org/10.3389/fncir.2018.00052 Text en Copyright © 2018 Riehle, Brochier, Nawrot and Grün. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Riehle, Alexa Brochier, Thomas Nawrot, Martin Grün, Sonja Behavioral Context Determines Network State and Variability Dynamics in Monkey Motor Cortex |
title | Behavioral Context Determines Network State and Variability Dynamics in Monkey Motor Cortex |
title_full | Behavioral Context Determines Network State and Variability Dynamics in Monkey Motor Cortex |
title_fullStr | Behavioral Context Determines Network State and Variability Dynamics in Monkey Motor Cortex |
title_full_unstemmed | Behavioral Context Determines Network State and Variability Dynamics in Monkey Motor Cortex |
title_short | Behavioral Context Determines Network State and Variability Dynamics in Monkey Motor Cortex |
title_sort | behavioral context determines network state and variability dynamics in monkey motor cortex |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6052126/ https://www.ncbi.nlm.nih.gov/pubmed/30050415 http://dx.doi.org/10.3389/fncir.2018.00052 |
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