| dc.description.abstract | Virtual reality based rehabilitation has drawn a lot of attention recently but the efficacy of it is still under debate. In this study, we set up to test if there is any difference of rehabilitation efficacy between convention and VR based intervention. Specifically, we examine whether the efficacy of the two intervention changes with time by using EEG and dynamic causal modelling for induced response (DCM_IR).
This is a prospective study. 30 subjects (8 females, 22males) were recruited and divide randomly into either VR (study) or conventional (control) training group, resulting in 16 and 14 in the study and control group, respectively. All subjects underwent a total 24 hours training program with the frequency of 1 hour a day, five days a week. 30 channel EEG were measured three times at pre-(before rehabilitation) , post- ( after rehabilitation ) intervention and one month after as the follow-up when patients performed either the shoulder or elbow flexion-extension using their affected hand. Clinical measures included FMA, TEMPA, WOLF were also conducted followed EEG measurement. The EEG data were pre-processed and then entered DCM_IR for network identification. Six plausible models, comprising bilateral primary motor cortex (M1), premotor cortex(PM) and (supplementary motor area) SMA, were tested and Bayesian model selection (BMS) was used to selected the model.
There has a significant effect on the efficacy of both groups, and this treatement effect can last at least one month, indicating the effectiveness of VR based intervention. The Bayesian Model Selection (BMS) identified the model with ipsilesional M1 dominating the network structure for both groups after rehab, suggesting that the strategy used by the brain for functional restoration is identical: to be as normal as before, irrelevant to the means of intervention. However, the best model switched into a model with more contralesional M1 engaged in the network structure for both groups at follow-up, indicating the compensation mechanism occurred after stopping rehab training. Qualitatively, there has no difference on the best model between two groups. In terms of the alternations of motor network after rehabilitation, the contralesional hamisphere engaged more for moving the paretic hand in the control group while, in the study, the activation patterns were more bilateral. Nevertheless, the overall coupling strength decrease in both groups at follow-up. Our result puts forward our understanding of the recovery process after stroke.
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