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Tracking resting state connectivity dynamics in veterans with PTSD

Posttraumatic stress disorder (PTSD) is a trauma- and stressor-related disorder that may emerge following a traumatic event. Neuroimaging studies have shown evidence of functional abnormality in many brain regions and systems affected by PTSD. Exaggerated threat detection associated with abnormaliti...

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Autores principales: Yuan, Han, Phillips, Raquel, Wong, Chung Ki, Zotev, Vadim, Misaki, Masaya, Wurfel, Brent, Krueger, Frank, Feldner, Matthew, Bodurka, Jerzy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6051475/
https://www.ncbi.nlm.nih.gov/pubmed/30035020
http://dx.doi.org/10.1016/j.nicl.2018.04.014
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author Yuan, Han
Phillips, Raquel
Wong, Chung Ki
Zotev, Vadim
Misaki, Masaya
Wurfel, Brent
Krueger, Frank
Feldner, Matthew
Bodurka, Jerzy
author_facet Yuan, Han
Phillips, Raquel
Wong, Chung Ki
Zotev, Vadim
Misaki, Masaya
Wurfel, Brent
Krueger, Frank
Feldner, Matthew
Bodurka, Jerzy
author_sort Yuan, Han
collection PubMed
description Posttraumatic stress disorder (PTSD) is a trauma- and stressor-related disorder that may emerge following a traumatic event. Neuroimaging studies have shown evidence of functional abnormality in many brain regions and systems affected by PTSD. Exaggerated threat detection associated with abnormalities in the salience network, as well as abnormalities in executive functions involved in emotions regulations, self-referencing and context evaluation processing are broadly reported in PTSD. Here we aimed to investigate the behavior and dynamic properties of fMRI resting state networks in combat-related PTSD, using a novel, multimodal imaging approach. Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) was employed to measure neurobiological brain activity among 36 veterans with combat-related PTSD and 20 combat-exposed veterans without PTSD. Based on the recently established method of measuring temporal-independent EEG microstates, we developed a novel strategy to integrate EEG and fMRI by quantifying the fast temporal dynamics associated with the resting state networks. We found distinctive occurrence rates of microstates associated with the dorsal default mode network and salience networks in the PTSD group as compared with control. Furthermore, the occurrence rate of the microstate for the dorsal default mode network was positively correlated with PTSD severity, whereas the occurrence rate of the microstate for the anterior salience network was negatively correlated with hedonic tone reported by participants with PTSD. Our findings reveal a novel aspect of abnormal network dynamics in combat-related PTSD and contribute to a better understanding of the pathophysiology of the disorder. Simultaneous EEG and fMRI will be a valuable tool in continuing to study the neurobiology underlying PTSD.
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spelling pubmed-60514752018-07-20 Tracking resting state connectivity dynamics in veterans with PTSD Yuan, Han Phillips, Raquel Wong, Chung Ki Zotev, Vadim Misaki, Masaya Wurfel, Brent Krueger, Frank Feldner, Matthew Bodurka, Jerzy Neuroimage Clin Regular Article Posttraumatic stress disorder (PTSD) is a trauma- and stressor-related disorder that may emerge following a traumatic event. Neuroimaging studies have shown evidence of functional abnormality in many brain regions and systems affected by PTSD. Exaggerated threat detection associated with abnormalities in the salience network, as well as abnormalities in executive functions involved in emotions regulations, self-referencing and context evaluation processing are broadly reported in PTSD. Here we aimed to investigate the behavior and dynamic properties of fMRI resting state networks in combat-related PTSD, using a novel, multimodal imaging approach. Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) was employed to measure neurobiological brain activity among 36 veterans with combat-related PTSD and 20 combat-exposed veterans without PTSD. Based on the recently established method of measuring temporal-independent EEG microstates, we developed a novel strategy to integrate EEG and fMRI by quantifying the fast temporal dynamics associated with the resting state networks. We found distinctive occurrence rates of microstates associated with the dorsal default mode network and salience networks in the PTSD group as compared with control. Furthermore, the occurrence rate of the microstate for the dorsal default mode network was positively correlated with PTSD severity, whereas the occurrence rate of the microstate for the anterior salience network was negatively correlated with hedonic tone reported by participants with PTSD. Our findings reveal a novel aspect of abnormal network dynamics in combat-related PTSD and contribute to a better understanding of the pathophysiology of the disorder. Simultaneous EEG and fMRI will be a valuable tool in continuing to study the neurobiology underlying PTSD. Elsevier 2018-04-21 /pmc/articles/PMC6051475/ /pubmed/30035020 http://dx.doi.org/10.1016/j.nicl.2018.04.014 Text en © 2018 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
Yuan, Han
Phillips, Raquel
Wong, Chung Ki
Zotev, Vadim
Misaki, Masaya
Wurfel, Brent
Krueger, Frank
Feldner, Matthew
Bodurka, Jerzy
Tracking resting state connectivity dynamics in veterans with PTSD
title Tracking resting state connectivity dynamics in veterans with PTSD
title_full Tracking resting state connectivity dynamics in veterans with PTSD
title_fullStr Tracking resting state connectivity dynamics in veterans with PTSD
title_full_unstemmed Tracking resting state connectivity dynamics in veterans with PTSD
title_short Tracking resting state connectivity dynamics in veterans with PTSD
title_sort tracking resting state connectivity dynamics in veterans with ptsd
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6051475/
https://www.ncbi.nlm.nih.gov/pubmed/30035020
http://dx.doi.org/10.1016/j.nicl.2018.04.014
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