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Distinguishing mechanisms of gamma frequency oscillations in human current source signals using a computational model of a laminar neocortical network
Gamma frequency rhythms have been implicated in numerous studies for their role in healthy and abnormal brain function. The frequency band has been described to encompass as broad a range as 30–150 Hz. Crucial to understanding the role of gamma in brain function is an identification of the underlyin...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2013
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3866567/ https://www.ncbi.nlm.nih.gov/pubmed/24385958 http://dx.doi.org/10.3389/fnhum.2013.00869 |
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author | Lee, Shane Jones, Stephanie R. |
author_facet | Lee, Shane Jones, Stephanie R. |
author_sort | Lee, Shane |
collection | PubMed |
description | Gamma frequency rhythms have been implicated in numerous studies for their role in healthy and abnormal brain function. The frequency band has been described to encompass as broad a range as 30–150 Hz. Crucial to understanding the role of gamma in brain function is an identification of the underlying neural mechanisms, which is particularly difficult in the absence of invasive recordings in macroscopic human signals such as those from magnetoencephalography (MEG) and electroencephalography (EEG). Here, we studied features of current dipole (CD) signals from two distinct mechanisms of gamma generation, using a computational model of a laminar cortical circuit designed specifically to simulate CDs in a biophysically principled manner (Jones et al., 2007, 2009). We simulated spiking pyramidal interneuronal gamma (PING) whose period is regulated by the decay time constant of GABA(A)-mediated synaptic inhibition and also subthreshold gamma driven by gamma-periodic exogenous excitatory synaptic drive. Our model predicts distinguishable CD features created by spiking PING compared to subthreshold driven gamma that can help to disambiguate mechanisms of gamma oscillations in human signals. We found that gamma rhythms in neocortical layer 5 can obscure a simultaneous, independent gamma in layer 2/3. Further, we arrived at a novel interpretation of the origin of high gamma frequency rhythms (100–150 Hz), showing that they emerged from a specific temporal feature of CDs associated with single cycles of PING activity and did not reflect a separate rhythmic process. Last we show that the emergence of observable subthreshold gamma required highly coherent exogenous drive. Our results are the first to demonstrate features of gamma oscillations in human current source signals that distinguish cellular and circuit level mechanisms of these rhythms and may help to guide understanding of their functional role. |
format | Online Article Text |
id | pubmed-3866567 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-38665672014-01-02 Distinguishing mechanisms of gamma frequency oscillations in human current source signals using a computational model of a laminar neocortical network Lee, Shane Jones, Stephanie R. Front Hum Neurosci Neuroscience Gamma frequency rhythms have been implicated in numerous studies for their role in healthy and abnormal brain function. The frequency band has been described to encompass as broad a range as 30–150 Hz. Crucial to understanding the role of gamma in brain function is an identification of the underlying neural mechanisms, which is particularly difficult in the absence of invasive recordings in macroscopic human signals such as those from magnetoencephalography (MEG) and electroencephalography (EEG). Here, we studied features of current dipole (CD) signals from two distinct mechanisms of gamma generation, using a computational model of a laminar cortical circuit designed specifically to simulate CDs in a biophysically principled manner (Jones et al., 2007, 2009). We simulated spiking pyramidal interneuronal gamma (PING) whose period is regulated by the decay time constant of GABA(A)-mediated synaptic inhibition and also subthreshold gamma driven by gamma-periodic exogenous excitatory synaptic drive. Our model predicts distinguishable CD features created by spiking PING compared to subthreshold driven gamma that can help to disambiguate mechanisms of gamma oscillations in human signals. We found that gamma rhythms in neocortical layer 5 can obscure a simultaneous, independent gamma in layer 2/3. Further, we arrived at a novel interpretation of the origin of high gamma frequency rhythms (100–150 Hz), showing that they emerged from a specific temporal feature of CDs associated with single cycles of PING activity and did not reflect a separate rhythmic process. Last we show that the emergence of observable subthreshold gamma required highly coherent exogenous drive. Our results are the first to demonstrate features of gamma oscillations in human current source signals that distinguish cellular and circuit level mechanisms of these rhythms and may help to guide understanding of their functional role. Frontiers Media S.A. 2013-12-18 /pmc/articles/PMC3866567/ /pubmed/24385958 http://dx.doi.org/10.3389/fnhum.2013.00869 Text en Copyright © 2013 Lee and Jones. http://creativecommons.org/licenses/by/3.0/ 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) or licensor 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 Lee, Shane Jones, Stephanie R. Distinguishing mechanisms of gamma frequency oscillations in human current source signals using a computational model of a laminar neocortical network |
title | Distinguishing mechanisms of gamma frequency oscillations in human current source signals using a computational model of a laminar neocortical network |
title_full | Distinguishing mechanisms of gamma frequency oscillations in human current source signals using a computational model of a laminar neocortical network |
title_fullStr | Distinguishing mechanisms of gamma frequency oscillations in human current source signals using a computational model of a laminar neocortical network |
title_full_unstemmed | Distinguishing mechanisms of gamma frequency oscillations in human current source signals using a computational model of a laminar neocortical network |
title_short | Distinguishing mechanisms of gamma frequency oscillations in human current source signals using a computational model of a laminar neocortical network |
title_sort | distinguishing mechanisms of gamma frequency oscillations in human current source signals using a computational model of a laminar neocortical network |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3866567/ https://www.ncbi.nlm.nih.gov/pubmed/24385958 http://dx.doi.org/10.3389/fnhum.2013.00869 |
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