Lower-Limb Motor Assessment With Corticomuscular Coherence of Multiple Muscles During Ankle Dorsiflexion After Stroke

Abstract

Motor impairment after stroke is generally caused by damage to the neural networks that control movement. Corticomuscular coherence (CMC) is a valid method to analyze the functional connectivity of the corticospinal pathway between the cerebral cortex and muscles. However, current studies on CMC in stroke patients only focused on the upper limbs. The functional connectivity between the brain and lower limbs in stroke patients has not been well studied. Therefore, twelve stroke patients and fifteen healthy controls were recruited and their electroencephalogram (EEG) and electromyogram (EMG) of Tibialis Anterior (TA), Lateral Gastrocnemius (LG) and Medial Gastrocnemius (MG) during unilateral static ankle dorsiflexion were recorded. We found the mean beta and gamma CMC values of Cz electrode of stroke patients were significantly lower than those of healthy controls (p < 0.05). The brain topography showed significant coherence in the center of the cerebral cortex in healthy controls, while there was no significant coherence in stroke patients. For clinical assessment, there was a significant positive correlation between CMC and lower limb Fugl-Meyer Assessment (FMA) for Cz-TA in beta band (r = 0.6296, p = 0.0282), Cz-LG in beta band (r = 0.6816, p = 0.0147), and Cz-MG in gamma band (r = 0.6194, p = 0.0317). A multiple linear regression model was established between CMC and lower limb FMA (R 2 = 0.6600,

cTBS over primary motor cortex increased contralateral corticomuscular coupling and interhemispheric functional connection

“…Fang et al found the CMC value was significantly lower in stroke patients than that in healthy controls in beta and lower gamma bands during reaching movements [58]. Our previous research also had similar results, and we also found there was a significant positive correlation between CMC and lower limb Fugl-Meyer Assessment [40]. In patients with hemiplegia, the increase of CMC was accompanied by the recovery of motor function, so cTBS may provide strategies for the rehabilitation of hemiplegia patients.…”

“…Use MATLAB 2021a (MathWorks, Inc., Natick, MA, United States) to preprocess sEMG signals. Firstly, 20-250 Hz fourth-order Butterworth bandpass filter was used to filter the original sEMG signals [39,40]. The mean baseline was then subtracted from the sEMG data.…”

“…12 Hz, point 5-7), beta (14-30 Hz, point[8][9][10][11][12][13][14][15][16] and gamma(32)(33)(34)(35)(36)(37)(38)(39)(40) bands[40]. The coherence value was between 0 and 1, where 1 represented that the two signals were completely coherent, and 0 represented that the two signals were completely incoherent.…”

Automatic sleep–wake classification and Parkinson's disease recognition using multifeature fusion with support vector machine

“…The EMG signal was filtered within the range of 20-200 Hz, 34 and the mean absolute amplitude of the filtered EMG was also calculated as a feature of the 10-s segment. The CMC values were determined to measure the linear synchronization between ECoG and EMG signals across the seven frequency bands, 35 with values ranging between 0 and 1, which provided insights into the degree of coherence between the two signals. 36 A normalization procedure was employed to normalize the indices on a scale of 0-1 to reduce errors.…”

Analysis of corticomuscular-cortical functional network based on time-delayed maximal information spectral coefficient

“…Various methods, such as corticomuscular coherence (CMC) [7], have been used in studying interactions among neurophysiological signals. The CMC method can reflect frequency interactions among signals but may not reflect the direction of internal information flow [8].…”