Spontaneous transient brain states in EEG source space in disorders of consciousness

被引:24
作者
Bai, Yang [1 ,2 ,3 ]
He, Jianghong [4 ]
Xia, Xiaoyu [5 ]
Wang, Yong [6 ]
Yang, Yi [4 ]
Di, Haibo [1 ]
Li, Xiaoli [6 ]
Ziemann, Ulf [2 ,3 ]
机构
[1] Hangzhou Normal Univ, Int Vegetat State & Consciousness Sci Inst, Hangzhou, Peoples R China
[2] Univ Tubingen, Dept Neurol & Stroke, Hoppe Seyler Str 3, D-72076 Tubingen, Germany
[3] Univ Tubingen, Hertie Inst Clin Brain Res, Tubingen, Germany
[4] Capital Med Univ, Beijing Tiantan Hosp, Dept Neurosurg, Beijing, Peoples R China
[5] Chinese Peoples Liberat Army Gen Hosp, Dept Neurosurg, Beijing, Peoples R China
[6] Beijing Normal Univ, McGovern Inst Brain Res, IDG, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
Transient state; Hidden Markov model; Electroencephalography; Disorder of consciousness; RESTING-STATE; DEFAULT MODE; CONNECTIVITY; NETWORK; MEG; LEVEL; ORGANIZATION; DYNAMICS;
D O I
10.1016/j.neuroimage.2021.118407
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Spontaneous transient states were recently identified by functional magnetic resonance imaging and magnetoencephalography in healthy subjects. They organize and coordinate neural activity in brain networks. How spontaneous transient states are altered in abnormal brain conditions is unknown. Here, we conducted a transient state analysis on resting-state electroencephalography (EEG) source space and developed a state transfer analysis to patients with disorders of consciousness (DOC). They uncovered different neural coordination patterns, including spatial power patterns, temporal dynamics, spectral shifts, and connectivity construction varies at potentially very fast (millisecond) time scales, in groups with different consciousness levels: healthy subjects, patients in minimally conscious state (MCS), and patients with vegetative state/unresponsive wakefulness syndrome (VS/UWS). Machine learning based on transient state features reveal high classification accuracy between MCS and VS/UWS. This study developed methodology of transient states analysis on EEG source space and abnormal brain conditions. Findings correlate spontaneous transient states with human consciousness and suggest potential roles of transient states in brain disease assessment.
引用
收藏
页数:13
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