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Diversity of functional connectivity patterns is reduced in propofol‐induced unconsciousness

Introduction Recent evidence suggests that the conscious brain is characterized by a diverse repertoire of functional connectivity patterns while the anesthetized brain shows stereotyped activity. However, classical time‐averaged methods of connectivity dismiss dynamic and temporal characteristics o...

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Published in:Human brain mapping 2017-10, Vol.38 (10), p.4980-4995
Main Authors: Lee, Heonsoo, Noh, Gyu‐Jeong, Joo, Pangyu, Choi, Byung‐Moon, Silverstein, Brian Henry, Kim, Minkyung, Wang, Jisung, Jung, Woo‐Sung, Kim, Seunghwan
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container_issue 10
container_start_page 4980
container_title Human brain mapping
container_volume 38
creator Lee, Heonsoo
Noh, Gyu‐Jeong
Joo, Pangyu
Choi, Byung‐Moon
Silverstein, Brian Henry
Kim, Minkyung
Wang, Jisung
Jung, Woo‐Sung
Kim, Seunghwan
description Introduction Recent evidence suggests that the conscious brain is characterized by a diverse repertoire of functional connectivity patterns while the anesthetized brain shows stereotyped activity. However, classical time‐averaged methods of connectivity dismiss dynamic and temporal characteristics of functional configurations. Here we demonstrate a new approach which characterizes time‐varying patterns of functional connectivity at the subsecond time scale. Methods We introduce phase‐lag entropy (PLE), a measure of the diversity of temporal patterns in the phase relationships between two signals. The proposed measure was applied to multichannel electroencephalogram (EEG), which were recorded from two distinct experimental settings: (1) propofol was administrated at a constant infusion rate for 60 min (n = 96); (2) administration of propofol by a target effect‐site concentration‐controlled infusion with simultaneous assessment of the level of consciousness (n = 10). Results From the first dataset, two substantial changes of the phase relationship during anesthesia was found: (1) the dynamics of the phase relationship between frontal channels became progressively less diverse and more stereotyped during unconsciousness, quantified as a reduction in PLE; and (2) the reduction in PLE was consistent across subjects. Furthermore, PLE provided better performance in the classification of states of consciousness than did phase‐lag index, a classical time‐averaged connectivity method. From the second dataset, PLE showed the highest agreement with the level of consciousness, compared to existing anesthetic depth indicators. Conclusions This study suggests that a scarcity of functional configurations is closely associated with anesthetically induced unconsciousness, and shows promise as a basis for a new consciousness monitoring system during general anesthesia. Hum Brain Mapp 38:4980–4995, 2017. © 2017 Wiley Periodicals, Inc.
doi_str_mv 10.1002/hbm.23708
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However, classical time‐averaged methods of connectivity dismiss dynamic and temporal characteristics of functional configurations. Here we demonstrate a new approach which characterizes time‐varying patterns of functional connectivity at the subsecond time scale. Methods We introduce phase‐lag entropy (PLE), a measure of the diversity of temporal patterns in the phase relationships between two signals. The proposed measure was applied to multichannel electroencephalogram (EEG), which were recorded from two distinct experimental settings: (1) propofol was administrated at a constant infusion rate for 60 min (n = 96); (2) administration of propofol by a target effect‐site concentration‐controlled infusion with simultaneous assessment of the level of consciousness (n = 10). Results From the first dataset, two substantial changes of the phase relationship during anesthesia was found: (1) the dynamics of the phase relationship between frontal channels became progressively less diverse and more stereotyped during unconsciousness, quantified as a reduction in PLE; and (2) the reduction in PLE was consistent across subjects. Furthermore, PLE provided better performance in the classification of states of consciousness than did phase‐lag index, a classical time‐averaged connectivity method. From the second dataset, PLE showed the highest agreement with the level of consciousness, compared to existing anesthetic depth indicators. Conclusions This study suggests that a scarcity of functional configurations is closely associated with anesthetically induced unconsciousness, and shows promise as a basis for a new consciousness monitoring system during general anesthesia. 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However, classical time‐averaged methods of connectivity dismiss dynamic and temporal characteristics of functional configurations. Here we demonstrate a new approach which characterizes time‐varying patterns of functional connectivity at the subsecond time scale. Methods We introduce phase‐lag entropy (PLE), a measure of the diversity of temporal patterns in the phase relationships between two signals. The proposed measure was applied to multichannel electroencephalogram (EEG), which were recorded from two distinct experimental settings: (1) propofol was administrated at a constant infusion rate for 60 min (n = 96); (2) administration of propofol by a target effect‐site concentration‐controlled infusion with simultaneous assessment of the level of consciousness (n = 10). Results From the first dataset, two substantial changes of the phase relationship during anesthesia was found: (1) the dynamics of the phase relationship between frontal channels became progressively less diverse and more stereotyped during unconsciousness, quantified as a reduction in PLE; and (2) the reduction in PLE was consistent across subjects. Furthermore, PLE provided better performance in the classification of states of consciousness than did phase‐lag index, a classical time‐averaged connectivity method. From the second dataset, PLE showed the highest agreement with the level of consciousness, compared to existing anesthetic depth indicators. Conclusions This study suggests that a scarcity of functional configurations is closely associated with anesthetically induced unconsciousness, and shows promise as a basis for a new consciousness monitoring system during general anesthesia. 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Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Human brain mapping</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lee, Heonsoo</au><au>Noh, Gyu‐Jeong</au><au>Joo, Pangyu</au><au>Choi, Byung‐Moon</au><au>Silverstein, Brian Henry</au><au>Kim, Minkyung</au><au>Wang, Jisung</au><au>Jung, Woo‐Sung</au><au>Kim, Seunghwan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Diversity of functional connectivity patterns is reduced in propofol‐induced unconsciousness</atitle><jtitle>Human brain mapping</jtitle><addtitle>Hum Brain Mapp</addtitle><date>2017-10</date><risdate>2017</risdate><volume>38</volume><issue>10</issue><spage>4980</spage><epage>4995</epage><pages>4980-4995</pages><issn>1065-9471</issn><eissn>1097-0193</eissn><abstract>Introduction Recent evidence suggests that the conscious brain is characterized by a diverse repertoire of functional connectivity patterns while the anesthetized brain shows stereotyped activity. However, classical time‐averaged methods of connectivity dismiss dynamic and temporal characteristics of functional configurations. Here we demonstrate a new approach which characterizes time‐varying patterns of functional connectivity at the subsecond time scale. Methods We introduce phase‐lag entropy (PLE), a measure of the diversity of temporal patterns in the phase relationships between two signals. The proposed measure was applied to multichannel electroencephalogram (EEG), which were recorded from two distinct experimental settings: (1) propofol was administrated at a constant infusion rate for 60 min (n = 96); (2) administration of propofol by a target effect‐site concentration‐controlled infusion with simultaneous assessment of the level of consciousness (n = 10). Results From the first dataset, two substantial changes of the phase relationship during anesthesia was found: (1) the dynamics of the phase relationship between frontal channels became progressively less diverse and more stereotyped during unconsciousness, quantified as a reduction in PLE; and (2) the reduction in PLE was consistent across subjects. Furthermore, PLE provided better performance in the classification of states of consciousness than did phase‐lag index, a classical time‐averaged connectivity method. From the second dataset, PLE showed the highest agreement with the level of consciousness, compared to existing anesthetic depth indicators. Conclusions This study suggests that a scarcity of functional configurations is closely associated with anesthetically induced unconsciousness, and shows promise as a basis for a new consciousness monitoring system during general anesthesia. 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subjects Anesthesia
Anesthesia, General
Anesthetics, Intravenous - pharmacology
Brain
Brain - drug effects
Brain - physiology
Classification
complexity
Consciousness
Consciousness - drug effects
Consciousness - physiology
Depth indicators
Dose-Response Relationship, Drug
EEG
electroencephalogram
Electroencephalography
Entropy
functional connectivity
Functional Neuroimaging
Humans
Hypnotics and Sedatives - pharmacology
Neural networks
Neural Pathways - drug effects
Neural Pathways - physiology
Phase relationships
Phase transitions
phase‐lag index
Propofol
Propofol - pharmacology
Reduction
Signal Processing, Computer-Assisted
Unconsciousness
Unconsciousness - chemically induced
Unconsciousness - physiopathology
title Diversity of functional connectivity patterns is reduced in propofol‐induced unconsciousness
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