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High-energy brain dynamics during anesthesia-induced unconsciousness
Characterizing anesthesia-induced alterations to brain network dynamics provides a powerful framework to understand the neural mechanisms of unconsciousness. To this end, increased attention has been directed at how anesthetic drugs alter the functional connectivity between brain regions as defined...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MIT Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6063715/ https://www.ncbi.nlm.nih.gov/pubmed/30090873 http://dx.doi.org/10.1162/NETN_a_00023 |
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author | Riehl, James R. Palanca, Ben J. Ching, ShiNung |
author_facet | Riehl, James R. Palanca, Ben J. Ching, ShiNung |
author_sort | Riehl, James R. |
collection | PubMed |
description | Characterizing anesthesia-induced alterations to brain network dynamics provides a powerful framework to understand the neural mechanisms of unconsciousness. To this end, increased attention has been directed at how anesthetic drugs alter the functional connectivity between brain regions as defined through neuroimaging. However, the effects of anesthesia on temporal dynamics at functional network scales is less well understood. Here, we examine such dynamics in view of the free-energy principle, which postulates that brain dynamics tend to promote lower energy (more organized) states. We specifically engaged the hypothesis that such low-energy states play an important role in maintaining conscious awareness. To investigate this hypothesis, we analyzed resting-state BOLD fMRI data from human volunteers during wakefulness and under sevoflurane general anesthesia. Our approach, which extends an idea previously used in the characterization of neuron-scale populations, involves thresholding the BOLD time series and using a normalized Hamiltonian energy function derived from the Ising model. Our major finding is that the brain spends significantly more time in lower energy states during eyes-closed wakefulness than during general anesthesia. This effect is especially pronounced in networks thought to be critical for maintaining awareness, suggesting a crucial cognitive role for both the structure and the dynamical landscape of these networks. |
format | Online Article Text |
id | pubmed-6063715 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MIT Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-60637152018-08-06 High-energy brain dynamics during anesthesia-induced unconsciousness Riehl, James R. Palanca, Ben J. Ching, ShiNung Netw Neurosci Research Characterizing anesthesia-induced alterations to brain network dynamics provides a powerful framework to understand the neural mechanisms of unconsciousness. To this end, increased attention has been directed at how anesthetic drugs alter the functional connectivity between brain regions as defined through neuroimaging. However, the effects of anesthesia on temporal dynamics at functional network scales is less well understood. Here, we examine such dynamics in view of the free-energy principle, which postulates that brain dynamics tend to promote lower energy (more organized) states. We specifically engaged the hypothesis that such low-energy states play an important role in maintaining conscious awareness. To investigate this hypothesis, we analyzed resting-state BOLD fMRI data from human volunteers during wakefulness and under sevoflurane general anesthesia. Our approach, which extends an idea previously used in the characterization of neuron-scale populations, involves thresholding the BOLD time series and using a normalized Hamiltonian energy function derived from the Ising model. Our major finding is that the brain spends significantly more time in lower energy states during eyes-closed wakefulness than during general anesthesia. This effect is especially pronounced in networks thought to be critical for maintaining awareness, suggesting a crucial cognitive role for both the structure and the dynamical landscape of these networks. MIT Press 2017-12-01 /pmc/articles/PMC6063715/ /pubmed/30090873 http://dx.doi.org/10.1162/NETN_a_00023 Text en © 2017 Massachusetts Institute of Technology http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Riehl, James R. Palanca, Ben J. Ching, ShiNung High-energy brain dynamics during anesthesia-induced unconsciousness |
title | High-energy brain dynamics during anesthesia-induced unconsciousness |
title_full | High-energy brain dynamics during anesthesia-induced unconsciousness |
title_fullStr | High-energy brain dynamics during anesthesia-induced unconsciousness |
title_full_unstemmed | High-energy brain dynamics during anesthesia-induced unconsciousness |
title_short | High-energy brain dynamics during anesthesia-induced unconsciousness |
title_sort | high-energy brain dynamics during anesthesia-induced unconsciousness |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6063715/ https://www.ncbi.nlm.nih.gov/pubmed/30090873 http://dx.doi.org/10.1162/NETN_a_00023 |
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