Motor network reorganization in stroke patients with dyskinesias during a shoulder-touching task: A fNIRS study

Abstract

Hemiplegia after stroke has become a major cause of the world’s high disabilities, and it is vital to enhance our understanding of post-stroke neuroplasticity to develop efficient rehabilitation programs. This study aimed to explore the brain activation and network reorganization of the motor cortex (MC) with functional near-infrared spectroscopy (fNIRS). The MC hemodynamic signals were gained from 22 stroke patients and 14 healthy subjects during a shoulder-touching task with the right hand. The MC activation pattern and network attributes analyzed with the graph theory were compared between the two groups. The results revealed that healthy controls presented dominant activation in the left MC while stroke patients exhibited dominant activation in the bilateral hemispheres MC. The MC networks for the two groups had small-world properties. Compared with healthy controls, patients had higher transitivity and lower global efficiency (GE), mean connectivity, and long connections (LCs) in the left MC. In addition, both MC activation and network attributes were correlated with patient’s upper limb motor function. The results showed the stronger compensation of the unaffected motor area, the better recovery of the upper limb motor function for patients. Moreover, the MC network possessed high clustering and relatively sparse inter-regional connections during recovery for patients. Our results promote the understanding of MC reorganization during recovery and indicate that MC activation and network could provide clinical assessment significance in stroke patients. Given the advantages of fNIRS, it shows great application potential in the assessment and rehabilitation of motor function after stroke.