Neurophysiological prognostic factors of motor function and spasticity after stroke - Cherkasov, S. (Journal of Education, Health and Sport, 2021)
Purpose: Understanding the neural mechanisms of recovery of motor control and development of spasticity after stroke is paramount importance for neurorehabilitation. Methods: For this purpose, we have analyzed several TMS and EEG variables and their association with motor recovery and development of spasticity. Forty-two subjects with stroke have taken part in the investigation. The neurophysiological examination included assessments by transcranial magnetic stimulation (TMS), intra- and inter-hemispheric EEG coherence in different frequency bands (e.g. Theta (4.0–7.99 Hz)) as determined by quantitative electroencephalography (qEEG). Motor function has been measured by Fugl-Meyer (FM), spasticity has been measured by modified Ashworth scale. Multiple univariate and multivariate linear regression analyses have been performed to identify the predictors for motor function and spasticity. Results: Univariate analyses have shown a significant interaction of amplitude and motor threshold (MT) of injured and MT, central motor conduction time of uninjured hemisphere with motor function according to Fugle-Meyer (FM). Also significant interaction has been shown between MT of injured hemisphere and spasticity. Multivariate analyses have shown a significant interaction of MT and beta coherence in injured, uninjured hemisphere and interhemispheric in prediction of motor function by FM. Also significant interaction of MT of injured hemisphere, delta and theta coherence between C3-C4 and spasticity has been shown. These interaction suggests that higher beta activity in the lesioned hemisphere strengthens the association between MT and FM scores. Higher beta activity in the uninjured hemisphere strengthens the association between MT and FM scores. Higher interhemispheric beta activity between C3-C4 strengthens the association between MT and FM scores. Higher delta and theta interhemispheric activity between C3-C4 strengthens the association between MT and Ashworth scores. Conclusions: Our results suggest that MT of both hemispheres is the strongest predictors of motor recovery after stroke. Moreover, cortical activity in the injured and uninjured hemisphere measured by qEEG provides additional information, specifying the association between MT and FM scores. MT of injured hemisphere in the association with low-frequency cortical activity are the strongest predictors of spasticity after stroke. Thus, the combination of EEG and TMS in predicting the recovery of motor control after stroke provides additional opportunities in the study of nonlinear relationships of influencing the interhemispheric networks, uninjured hemisphere and the release of subcortical activity