Functional Brain Controllability Alterations in Stroke

• Published in: Frontiers in bioengineering and biotechnology Vol. 10; p. 925970
• Main Authors: Li, Xuhong, Fang, Feng, Li, Rihui, Zhang, Yingchun
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 27.06.2022
• Subjects: Bioengineering and Biotechnology; brain controllability; EEG; fNIRS (functional near infrared spectroscopy); motor control; stroke
• ISSN: 2296-4185; 2296-4185
• DOI: 10.3389/fbioe.2022.925970

Motor control deficits are very common in stroke survivors and often lead to disability. Current clinical measures for profiling motor control impairments are largely subjective and lack precise interpretation in a “control” perspective. This study aims to provide an accurate interpretation and assessment of the underlying “motor control” deficits caused by stroke, using a recently developed novel technique, i.e., the functional brain controllability analysis. The electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) were simultaneously recorded from 16 stroke patients and 11 healthy subjects during a hand-clenching task. A high spatiotemporal resolution fNIRS-informed EEG source imaging approach was then employed to estimate the cortical activity and construct the functional brain network. Subsequently, network control theory was applied to evaluate the modal controllability of some key motor regions, including primary motor cortex (M1), premotor cortex (PMC), and supplementary motor cortex (SMA), and also the executive control network (ECN). Results indicated that the modal controllability of ECN in stroke patients was significantly lower than healthy subjects ( p = 0.03). Besides, the modal controllability of SMA in stroke patients was also significant smaller than healthy subjects ( p = 0.02). Finally, the baseline modal controllability of M1 was found to be significantly correlated with the baseline FM-UL clinical scores ( r = 0.58, p = 0.01). In conclusion, our results provide a new perspective to better understand the motor control deficits caused by stroke. We expect such an analytical methodology can be extended to investigate the other neurological or psychiatric diseases caused by cognitive control or motor control impairment.