| dc.description.abstract | In this study, we aimed to investigate the cerebral re-organization of motor networks in response to rehabilitation after stroke using Dynamic Causal Modelling for induced responses (DCM_IR) as measured with electroencephalography (EEG). Specifically, the difference in changes due to Virtual-Reality game based rehabilitation (VR) and conventional rehabilitation (CR), including the architecture of the motor network and the coupling parameters govern it resulting from DCM, was examined and compared.
21 stroke patients were recruited in this study and divided randomly into two groups: 11 for VR group (average age:54.73±10.93) and 10 for CR group (average age:64.4 ±8.72). All subjects underwent a totall 24 hours training program with the frequency of 1 hour a day, four days a week. The daily treatment for the VR group consisted of playing 1 hour of home-made VR game which was specially designed to match the conventional CR protocol while the CR group underwent 1 hour route CR treatment. 30 channel EEG were acquired with 2000 Hz sampling rate before (pre-treatment) and after (post-treatment) completed the rehabilitation training. During the EEG acquisition, all subjects were asked to perform about 80 trials of simple upper-limb movement, like shoulder or elbow flexion-extension (subjective to the subject' ability and decided by the therapist), using their affected hand. The EEG data were filtered with 60Hz stop-pass filter to remove power line noise and epoched form -800 to +800 ms where the time zero indicated the inhibition of movement as commanded by the therapist. The epoched data were further filtered with 4~48 Hz band-pass filter and the 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 that can explain the data best at both the single subject and group level. Statistic test on the estimates of the best model were performed using analysis of variance (ANOVA), paired t-test, two sample t-test. Clinical measures included FM-UE, TEMPA, WMFT were also conducted by the therapist pre- and post-treatment.
The statistic test on FM, TEMPA, WOLF shows there has a significant difference between pre- and post-treatment but no significant difference between VR and CR groups, indicating that VR based rehabilitation has the similar treatment effect as the convention CR does. The BMS identifies the model with contralesional M1 dominating the network structure for both groups and for pre- and post-rehab, suggesting that the strategy used by the brain for functional restoration is identical: to be as normal as before, irrelavent to the means of intervention. We compared the changes in coupling parameters and found that CR group is better than VR group with four connections and VR group is better than CR group with two connections only.
In conclution, we investigated the architecture of the motor network during task by DCM and the difference of connection between architecture of the brain. We found a more complete result by focus on connection changed from cortical area compared with previous studies and we observed that cerebral motor networks indeed affected by occupational therapy and VR based rehabilitation. We believe the outcome of this study could be an evidence that VR based rehabilitation is better for stroke patient and benefit the study of motor recovery during rehabilitation n after stroke in the future. | en_US |