Enhanced Brain Functional Interaction Following BCI-Guided Supernumerary Robotic Finger Training Based on Sixth-Finger Motor Imagery.
Journal:
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
PMID:
40257872
Abstract
Supernumerary robotic finger (SRF) has shown unique advantages in the field of motor augmentation and rehabilitation, while the development of brain computer interface (BCI) technology has provided the possibility for direct control of SRF. However, the neuroplasticity effects of BCI-actuated SRF (BCI-SRF) training based on the "six finger" motor imagery paradigm are still unclear. This study recruited 20 healthy right-handed participants and randomly assigned them to either a BCI-SRF training group or a sham SRF training group. During the testing phase before and after 4 weeks of training, all participants were tested for SRF-finger opposition sequence behavior, resting state fMRI (rs-fMRI), and task-based fMRI (tb-fMRI). The results showed that compared with the Sham group, the BCI-SRF group improved the accuracy rate of the SRF-finger opposition sequence by 132%. The activation analysis of tb-fMRI before and after training revealed a significant increase in left middle frontal gyrus only in the BCI-SRF group. In addition, the BCI-SRF group showed an increase in FC between the right primary motor cortex and left cerebellum inferior lobe, as well as between the left middle frontal gyrus and the right precuneus lobe after training, while there was no significant change in the Sham group. In addition, only the BCI-SRF group showed a significant increase in clustering coefficients after training. Moreover, the increase in the clustering coefficients of the two groups is positively correlated with the improvement of the accuracy of the SRF-finger opposition sequences. These results indicate that the integration of BCI and SRF significantly regulates the functional interaction between motor learning and cognitive imagery brain regions, enhances the integration and processing ability of brain networks for local information, and improves human-machine interaction behavioral performance.