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Structural Covariance of the Prefrontal-Amygdala Pathways Associated with Heart Rate Variability

The neurovisceral integration model has shown a key role of the amygdala in neural circuits underlying heart rate variability (HRV) modulation, and suggested that reciprocal connections from amygdala to brain regions centered on the central autonomic network (CAN) are associated with HRV. To provide...

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Autores principales: Wei, Luqing, Chen, Hong, Wu, Guo-Rong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5838315/
https://www.ncbi.nlm.nih.gov/pubmed/29545744
http://dx.doi.org/10.3389/fnhum.2018.00002
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author Wei, Luqing
Chen, Hong
Wu, Guo-Rong
author_facet Wei, Luqing
Chen, Hong
Wu, Guo-Rong
author_sort Wei, Luqing
collection PubMed
description The neurovisceral integration model has shown a key role of the amygdala in neural circuits underlying heart rate variability (HRV) modulation, and suggested that reciprocal connections from amygdala to brain regions centered on the central autonomic network (CAN) are associated with HRV. To provide neuroanatomical evidence for these theoretical perspectives, the current study used covariance analysis of MRI-based gray matter volume (GMV) to map structural covariance network of the amygdala, and then determined whether the interregional structural correlations related to individual differences in HRV. The results showed that covariance patterns of the amygdala encompassed large portions of cortical (e.g., prefrontal, cingulate, and insula) and subcortical (e.g., striatum, hippocampus, and midbrain) regions, lending evidence from structural covariance analysis to the notion that the amygdala was a pivotal node in neural pathways for HRV modulation. Importantly, participants with higher resting HRV showed increased covariance of amygdala to dorsal medial prefrontal cortex and anterior cingulate cortex (dmPFC/dACC) extending into adjacent medial motor regions [i.e., pre-supplementary motor area (pre-SMA)/SMA], demonstrating structural covariance of the prefrontal-amygdala pathways implicated in HRV, and also implying that resting HRV may reflect the function of neural circuits underlying cognitive regulation of emotion as well as facilitation of adaptive behaviors to emotion. Our results, thus, provide anatomical substrates for the neurovisceral integration model that resting HRV may index an integrative neural network which effectively organizes emotional, cognitive, physiological and behavioral responses in the service of goal-directed behavior and adaptability.
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spelling pubmed-58383152018-03-15 Structural Covariance of the Prefrontal-Amygdala Pathways Associated with Heart Rate Variability Wei, Luqing Chen, Hong Wu, Guo-Rong Front Hum Neurosci Neuroscience The neurovisceral integration model has shown a key role of the amygdala in neural circuits underlying heart rate variability (HRV) modulation, and suggested that reciprocal connections from amygdala to brain regions centered on the central autonomic network (CAN) are associated with HRV. To provide neuroanatomical evidence for these theoretical perspectives, the current study used covariance analysis of MRI-based gray matter volume (GMV) to map structural covariance network of the amygdala, and then determined whether the interregional structural correlations related to individual differences in HRV. The results showed that covariance patterns of the amygdala encompassed large portions of cortical (e.g., prefrontal, cingulate, and insula) and subcortical (e.g., striatum, hippocampus, and midbrain) regions, lending evidence from structural covariance analysis to the notion that the amygdala was a pivotal node in neural pathways for HRV modulation. Importantly, participants with higher resting HRV showed increased covariance of amygdala to dorsal medial prefrontal cortex and anterior cingulate cortex (dmPFC/dACC) extending into adjacent medial motor regions [i.e., pre-supplementary motor area (pre-SMA)/SMA], demonstrating structural covariance of the prefrontal-amygdala pathways implicated in HRV, and also implying that resting HRV may reflect the function of neural circuits underlying cognitive regulation of emotion as well as facilitation of adaptive behaviors to emotion. Our results, thus, provide anatomical substrates for the neurovisceral integration model that resting HRV may index an integrative neural network which effectively organizes emotional, cognitive, physiological and behavioral responses in the service of goal-directed behavior and adaptability. Frontiers Media S.A. 2018-01-23 /pmc/articles/PMC5838315/ /pubmed/29545744 http://dx.doi.org/10.3389/fnhum.2018.00002 Text en Copyright © 2018 Wei, Chen and Wu. 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) 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
Wei, Luqing
Chen, Hong
Wu, Guo-Rong
Structural Covariance of the Prefrontal-Amygdala Pathways Associated with Heart Rate Variability
title Structural Covariance of the Prefrontal-Amygdala Pathways Associated with Heart Rate Variability
title_full Structural Covariance of the Prefrontal-Amygdala Pathways Associated with Heart Rate Variability
title_fullStr Structural Covariance of the Prefrontal-Amygdala Pathways Associated with Heart Rate Variability
title_full_unstemmed Structural Covariance of the Prefrontal-Amygdala Pathways Associated with Heart Rate Variability
title_short Structural Covariance of the Prefrontal-Amygdala Pathways Associated with Heart Rate Variability
title_sort structural covariance of the prefrontal-amygdala pathways associated with heart rate variability
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5838315/
https://www.ncbi.nlm.nih.gov/pubmed/29545744
http://dx.doi.org/10.3389/fnhum.2018.00002
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