Detecting cognitive motor dissociation by functional near-infrared spectroscopy

BackgroundBehavioral assessment based on external manifestations of consciousness fails for patients with cognitive motor dissociation (CMD). Functional near-infrared spectroscopy (fNIRS) is an emerging neuroimaging technique that can detect internal brain functional activities. However, the extent...

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Main Authors: Yan Wang, Wentao Zeng, Leyao Zou, Qijun Wang, Bingkai Ren, Qi Xiong, Yang Bai, Zhen Feng
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-04-01
Series:Frontiers in Neurology
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Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2025.1532804/full
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author Yan Wang
Yan Wang
Yan Wang
Wentao Zeng
Wentao Zeng
Wentao Zeng
Leyao Zou
Leyao Zou
Leyao Zou
Qijun Wang
Bingkai Ren
Bingkai Ren
Bingkai Ren
Qi Xiong
Yang Bai
Yang Bai
Yang Bai
Zhen Feng
Zhen Feng
Zhen Feng
author_facet Yan Wang
Yan Wang
Yan Wang
Wentao Zeng
Wentao Zeng
Wentao Zeng
Leyao Zou
Leyao Zou
Leyao Zou
Qijun Wang
Bingkai Ren
Bingkai Ren
Bingkai Ren
Qi Xiong
Yang Bai
Yang Bai
Yang Bai
Zhen Feng
Zhen Feng
Zhen Feng
author_sort Yan Wang
collection DOAJ
description BackgroundBehavioral assessment based on external manifestations of consciousness fails for patients with cognitive motor dissociation (CMD). Functional near-infrared spectroscopy (fNIRS) is an emerging neuroimaging technique that can detect internal brain functional activities. However, the extent to which fNIRS can help identify CMD patients among those with disorders of consciousness (DOC) remains unclear.ObjectiveTo identify CMD patients among DOC patients using fNIRS with a command-driven hand-open-close motor imagery task.MethodsfNIRS was used to measure the hemodynamic responses of 70 prolonged DOC patients, including 30 with vegetative state/unresponsive wakefulness syndrome (VS/UWS), 20 with minimally conscious state minus (MCS–), and 20 with minimally conscious state plus (MCS+), during a command-driven hand-open-close motor imagery task. Seven features of hemodynamic responses were extracted during the task and the rest conditions. The support vector machine combined with genetic algorithm was employed to classify and predict the brain's response to spoken commands and to identify CMD patients among prolonged DOC individuals.ResultsWe identified seven CMD patients using fNIRS, of whom four were in VS/UWS and three were in MCS–. Six months after fNIRS examination, the seven identified CMD patients were more likely to have a favorable outcome (3/4 vs. 1/31, P = 0.014, Fisher's exact test) compared with non-CMD patients.ConclusionsCMD patients can be identified through fNIRS combined with a command-driven motor imagery task, which will aid in the accurate diagnosis of DOC patients.
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spelling doaj-art-cb218494dcc945eb912592df8a939e922025-08-20T02:53:43ZengFrontiers Media S.A.Frontiers in Neurology1664-22952025-04-011610.3389/fneur.2025.15328041532804Detecting cognitive motor dissociation by functional near-infrared spectroscopyYan Wang0Yan Wang1Yan Wang2Wentao Zeng3Wentao Zeng4Wentao Zeng5Leyao Zou6Leyao Zou7Leyao Zou8Qijun Wang9Bingkai Ren10Bingkai Ren11Bingkai Ren12Qi Xiong13Yang Bai14Yang Bai15Yang Bai16Zhen Feng17Zhen Feng18Zhen Feng19Affiliated Rehabilitation Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, ChinaRehabilitation Medicine Clinical Research Center of Jiangxi Province, Nanchang, Jiangxi, ChinaKey Laboratory of Jiangxi Provincial Health Commission for DOC Rehabilitation, Nanchang, Jiangxi, ChinaAffiliated Rehabilitation Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, ChinaRehabilitation Medicine Clinical Research Center of Jiangxi Province, Nanchang, Jiangxi, ChinaKey Laboratory of Jiangxi Provincial Health Commission for DOC Rehabilitation, Nanchang, Jiangxi, ChinaAffiliated Rehabilitation Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, ChinaRehabilitation Medicine Clinical Research Center of Jiangxi Province, Nanchang, Jiangxi, ChinaKey Laboratory of Jiangxi Provincial Health Commission for DOC Rehabilitation, Nanchang, Jiangxi, ChinaCenter for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, ChinaAffiliated Rehabilitation Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, ChinaRehabilitation Medicine Clinical Research Center of Jiangxi Province, Nanchang, Jiangxi, ChinaKey Laboratory of Jiangxi Provincial Health Commission for DOC Rehabilitation, Nanchang, Jiangxi, ChinaThe First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, ChinaAffiliated Rehabilitation Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, ChinaRehabilitation Medicine Clinical Research Center of Jiangxi Province, Nanchang, Jiangxi, ChinaKey Laboratory of Jiangxi Provincial Health Commission for DOC Rehabilitation, Nanchang, Jiangxi, ChinaAffiliated Rehabilitation Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, ChinaRehabilitation Medicine Clinical Research Center of Jiangxi Province, Nanchang, Jiangxi, ChinaKey Laboratory of Jiangxi Provincial Health Commission for DOC Rehabilitation, Nanchang, Jiangxi, ChinaBackgroundBehavioral assessment based on external manifestations of consciousness fails for patients with cognitive motor dissociation (CMD). Functional near-infrared spectroscopy (fNIRS) is an emerging neuroimaging technique that can detect internal brain functional activities. However, the extent to which fNIRS can help identify CMD patients among those with disorders of consciousness (DOC) remains unclear.ObjectiveTo identify CMD patients among DOC patients using fNIRS with a command-driven hand-open-close motor imagery task.MethodsfNIRS was used to measure the hemodynamic responses of 70 prolonged DOC patients, including 30 with vegetative state/unresponsive wakefulness syndrome (VS/UWS), 20 with minimally conscious state minus (MCS–), and 20 with minimally conscious state plus (MCS+), during a command-driven hand-open-close motor imagery task. Seven features of hemodynamic responses were extracted during the task and the rest conditions. The support vector machine combined with genetic algorithm was employed to classify and predict the brain's response to spoken commands and to identify CMD patients among prolonged DOC individuals.ResultsWe identified seven CMD patients using fNIRS, of whom four were in VS/UWS and three were in MCS–. Six months after fNIRS examination, the seven identified CMD patients were more likely to have a favorable outcome (3/4 vs. 1/31, P = 0.014, Fisher's exact test) compared with non-CMD patients.ConclusionsCMD patients can be identified through fNIRS combined with a command-driven motor imagery task, which will aid in the accurate diagnosis of DOC patients.https://www.frontiersin.org/articles/10.3389/fneur.2025.1532804/fulldisorders of consciousnesscognitive motor dissociationfunctional near-infrared spectroscopymotor imagerysupport vector machine
spellingShingle Yan Wang
Yan Wang
Yan Wang
Wentao Zeng
Wentao Zeng
Wentao Zeng
Leyao Zou
Leyao Zou
Leyao Zou
Qijun Wang
Bingkai Ren
Bingkai Ren
Bingkai Ren
Qi Xiong
Yang Bai
Yang Bai
Yang Bai
Zhen Feng
Zhen Feng
Zhen Feng
Detecting cognitive motor dissociation by functional near-infrared spectroscopy
Frontiers in Neurology
disorders of consciousness
cognitive motor dissociation
functional near-infrared spectroscopy
motor imagery
support vector machine
title Detecting cognitive motor dissociation by functional near-infrared spectroscopy
title_full Detecting cognitive motor dissociation by functional near-infrared spectroscopy
title_fullStr Detecting cognitive motor dissociation by functional near-infrared spectroscopy
title_full_unstemmed Detecting cognitive motor dissociation by functional near-infrared spectroscopy
title_short Detecting cognitive motor dissociation by functional near-infrared spectroscopy
title_sort detecting cognitive motor dissociation by functional near infrared spectroscopy
topic disorders of consciousness
cognitive motor dissociation
functional near-infrared spectroscopy
motor imagery
support vector machine
url https://www.frontiersin.org/articles/10.3389/fneur.2025.1532804/full
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