ArticleCognitive neurodynamics2022
Assessing residual motor function in patients with disorders of consciousness by brain network properties of task-state EEG.
Article in Cognitive neurodynamics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 11 citations in OpenAlex.
- Beside Resting-State EEG in the Diagnosis and Prognosis of Patients with Disorders of Consciousness.Diagnostics (Basel, Switzerland) · 2026Article
- [Brain-computer interface technology and its applications for patients with disorders of consciousness].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025Review
- Functional networks in prolonged disorders of consciousness.Frontiers in neuroscience · 2023Review
- Evaluation of consciousness rehabilitation via neuroimaging methods.Frontiers in human neuroscience · 2023Review
- Frontal and parietal lobes play crucial roles in understanding the disorder of consciousness: A perspective from electroencephalogram studies.Frontiers in neuroscience · 2022Review
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11 authors at 4 institutions in 1 country.
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Abstract
Recent achievements in evaluating the residual consciousness of patients with disorders of consciousness (DOCs) have demonstrated that spontaneous or evoked electroencephalography (EEG) could be used to improve consciousness state diagnostic classification. Recent studies showed that the EEG signal of the task-state could better characterize the conscious state and cognitive ability of the brain, but it has rarely been used in consciousness assessment. A cue-guide motor task experiment was designed, and task-state EEG were collected from 18 patients with unresponsive wakefulness syndrome (UWS), 29 patients in a minimally conscious state (MCS), and 19 healthy controls. To obtain the markers of residual motor function in patients with DOC, the event-related potential (ERP), scalp topography, and time-frequency maps were analyzed. Then the coherence (COH) and debiased weighted phase lag index (dwPLI) networks in the delta, theta, alpha, beta, and gamma bands were constructed, and the correlations of network properties and JFK Coma Recovery Scale-Revised (CRS-R) motor function scores were calculated. The results showed that there was an obvious readiness potential (RP) at the Cz position during the motor preparation process in the MCS group, but no RP was observed in the UWS group. Moreover, the node degree properties of the COH network in the theta and alpha bands and the global efficiency properties of the dwPLI network in the theta band were significantly greater in the MCS group compared to the UWS group. The above network properties and CRS-R motor function scores showed a strong linear correlation. These findings demonstrated that the brain network properties of task-state EEG could be markers of residual motor function of DOC patients. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-021-09741-7.
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