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Coordinated Human Brainstem and Spinal Cord Networks during the Expectation of Pain Have Elements Unique from Resting-State Effects

Functional magnetic resonance imaging (fMRI) research on the human brainstem (BS) and spinal cord (SC) has identified extensive BS/SC resting-state networks (RSNs) by showing spontaneous coordinated blood oxygenation-level dependent (BOLD) signal fluctuations in the absence of a stimulus. Studies ha...

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Autores principales: Ioachim, Gabriela, Powers, Jocelyn M., Warren, Howard J. M., Stroman, Patrick W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7565010/
https://www.ncbi.nlm.nih.gov/pubmed/32824896
http://dx.doi.org/10.3390/brainsci10090568
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author Ioachim, Gabriela
Powers, Jocelyn M.
Warren, Howard J. M.
Stroman, Patrick W.
author_facet Ioachim, Gabriela
Powers, Jocelyn M.
Warren, Howard J. M.
Stroman, Patrick W.
author_sort Ioachim, Gabriela
collection PubMed
description Functional magnetic resonance imaging (fMRI) research on the human brainstem (BS) and spinal cord (SC) has identified extensive BS/SC resting-state networks (RSNs) by showing spontaneous coordinated blood oxygenation-level dependent (BOLD) signal fluctuations in the absence of a stimulus. Studies have shown that these networks can be influenced by participants’ level of arousal or attention (e.g., watching a video), and linked network function to autonomic homeostatic regulation. Here we explore how the cognitive state of expecting pain can influence connectivity in these networks. Data from two studies (a predictable pain stimulus study, and a resting-state study) were compared to show the effects of expecting pain on BS/SC networks, and how networks differed from networks associated with the resting-state. In each study, BOLD fMRI data were obtained from the cervical SC and brainstem in healthy participants at 3 tesla using a T(2)-weighted single-shot fast spin-echo imaging method. Functional connectivity was investigated within the entire 3D volume by means of structural equation modeling (SEM) and analyses of covariance (ANCOVA). Results showed extensive connectivity within/across BS and SC regions during the expectation of pain, and ANCOVA analyses showed that connectivity in specific components of these networks varied with individual pain sensitivity. Comparing these results to RSN fluctuations revealed commonalities in coordination between BS and SC regions, and specific BS–BS connectivity fluctuations unique to the expectation of pain. Based on the regions involved, these results provide evidence of brainstem regulation specific to the expectation of pain.
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spelling pubmed-75650102020-10-26 Coordinated Human Brainstem and Spinal Cord Networks during the Expectation of Pain Have Elements Unique from Resting-State Effects Ioachim, Gabriela Powers, Jocelyn M. Warren, Howard J. M. Stroman, Patrick W. Brain Sci Article Functional magnetic resonance imaging (fMRI) research on the human brainstem (BS) and spinal cord (SC) has identified extensive BS/SC resting-state networks (RSNs) by showing spontaneous coordinated blood oxygenation-level dependent (BOLD) signal fluctuations in the absence of a stimulus. Studies have shown that these networks can be influenced by participants’ level of arousal or attention (e.g., watching a video), and linked network function to autonomic homeostatic regulation. Here we explore how the cognitive state of expecting pain can influence connectivity in these networks. Data from two studies (a predictable pain stimulus study, and a resting-state study) were compared to show the effects of expecting pain on BS/SC networks, and how networks differed from networks associated with the resting-state. In each study, BOLD fMRI data were obtained from the cervical SC and brainstem in healthy participants at 3 tesla using a T(2)-weighted single-shot fast spin-echo imaging method. Functional connectivity was investigated within the entire 3D volume by means of structural equation modeling (SEM) and analyses of covariance (ANCOVA). Results showed extensive connectivity within/across BS and SC regions during the expectation of pain, and ANCOVA analyses showed that connectivity in specific components of these networks varied with individual pain sensitivity. Comparing these results to RSN fluctuations revealed commonalities in coordination between BS and SC regions, and specific BS–BS connectivity fluctuations unique to the expectation of pain. Based on the regions involved, these results provide evidence of brainstem regulation specific to the expectation of pain. MDPI 2020-08-19 /pmc/articles/PMC7565010/ /pubmed/32824896 http://dx.doi.org/10.3390/brainsci10090568 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ioachim, Gabriela
Powers, Jocelyn M.
Warren, Howard J. M.
Stroman, Patrick W.
Coordinated Human Brainstem and Spinal Cord Networks during the Expectation of Pain Have Elements Unique from Resting-State Effects
title Coordinated Human Brainstem and Spinal Cord Networks during the Expectation of Pain Have Elements Unique from Resting-State Effects
title_full Coordinated Human Brainstem and Spinal Cord Networks during the Expectation of Pain Have Elements Unique from Resting-State Effects
title_fullStr Coordinated Human Brainstem and Spinal Cord Networks during the Expectation of Pain Have Elements Unique from Resting-State Effects
title_full_unstemmed Coordinated Human Brainstem and Spinal Cord Networks during the Expectation of Pain Have Elements Unique from Resting-State Effects
title_short Coordinated Human Brainstem and Spinal Cord Networks during the Expectation of Pain Have Elements Unique from Resting-State Effects
title_sort coordinated human brainstem and spinal cord networks during the expectation of pain have elements unique from resting-state effects
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7565010/
https://www.ncbi.nlm.nih.gov/pubmed/32824896
http://dx.doi.org/10.3390/brainsci10090568
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