fNIRS-based Monitoring of Functional Brain Network during Image Guided Hand Movements

This study investigated the effects of image guidance on uni- and bi-manual movements using functional near-infrared spectroscopy (fNIRS), a pivotal wearable system for optical neuroimaging. We analyzed fNIRS signals from seven participants performing three motor tasks: left finger tapping, right finger tapping, and finger crossing under three conditions: motor execution, motor imagery, and guided motor imagery (GMI). Moreover, the motor and prefrontal cortices’ functional connectivity, and brain networks were compared. Obtained results demonstrated that bimanual movements elicit tighter functional connections than unimanual movements. Additionally, image guidance made motor imagery more similar to actual movements under various features. Furthermore, the achieved results are the highest classification accuracy of 0.896 from GMI among the three motor conditions using a hybrid strategy of 5-channel statistical and 9-channel functional brain network features. Also, the outcome of this study provides insights into the functional connectivity and brain networks involved in various motor tasks, with implications for rehabilitation training and brain-machine interface applications.