Abstract
Motor imagery is one of the classical paradigms which have been used in brain-computer interface and motor function recovery. Finger movement-based motor execution is a complex biomechanical architecture and a crucial task for establishing most complicated and natural activities in daily life. Some patients may suffer from alternating hemiplegia after brain stroke and lose their ability of motor execution. Fortunately, the ability of motor imagery might be preserved independently and worked as a backdoor for motor function recovery. The efficacy of motor imagery for achieving significant recovery for the motor cortex after brain stroke is still an open question. In this study, we designed a new paradigm to investigate the neural mechanism of thirty finger movements in two scenarios: motor execution and motor imagery. Eleven healthy participants performed or imagined thirty hand gestures twice based on left and right finger movements. The electroencephalogram (EEG) signal for each subject during sixty trials left and right finger motor execution and imagery were recorded during our proposed experimental paradigm. The Granger causality (G-causality) analysis method was employed to analyze the brain connectivity and its strength between contralateral premotor, motor, and sensorimotor areas. Highest numbers for G-causality trials of 37 ± 7.3, 35.5 ± 8.8, 36.3 ± 10.3, and 39.2 ± 9.0 and lowest Granger causality coefficients of 9.1 ± 3.2, 10.9 ± 3.7, 13.2 ± 0.6, and 13.4 ± 0.6 were achieved from the premotor to motor area during execution/imagination tasks of right and left finger movements, respectively. These results provided a new insight into motor execution and motor imagery based on hand gestures, which might be useful to build a new biomarker of finger motor recovery for partially or even completely plegic patients. Furthermore, a significant difference of the G-causality trial number was observed during left finger execution/imagery and right finger imagery, but it was not observed during the right finger execution phase. Significant difference of the G-causality coefficient was observed during left finger execution and imagery, but it was not observed during right finger execution and imagery phases. These results suggested that different MI-based brain motor function recovery strategies should be taken for right-hand and left-hand patients after brain stroke.
Highlights
EEG-based brain-computer interfaces (BCIs) have been used for building an advanced communication or control pathway between brain and computer using noninvasive measurements [1, 2]
Several classical BCI paradigms were developed for helping handicapped people to interact with the environment by controlling a smart home, robotic arm, Journal of Healthcare Engineering and a wheelchair using brain activity based on event-related potential (ERP) such as the P300 wave [3, 4] or based on steady-state visually evoked potential (SSVEP) [5] and motor imagery [6, 7]
E mental process during motor execution or motor imagery has been widely used for building BCI systems in several domains [8,9,10]. is mental process has showed the potential applications in the rehabilitation field for patients who suffered from brain strokes [11, 12]. ese patients who lost some motor functions after brain stroke might be able to reactivate some brain areas such as sensorimotor area [13] by using BCI based on motor imagery as one of the most effective surrogate motor training methods [14]
Summary
Chao Chen ,1,2 Jiaxin Zhang, Abdelkader Nasreddine Belkacem ,3 Shanting Zhang, Rui Xu, Bin Hao, Qiang Gao, Duk Shin ,5 Changming Wang ,6,7 and Dong Ming 2. Highest numbers for G-causality trials of 37 ± 7.3, 35.5 ± 8.8, 36.3 ± 10.3, and 39.2 ± 9.0 and lowest Granger causality coefficients of 9.1 ± 3.2, 10.9 ± 3.7, 13.2 ± 0.6, and 13.4 ± 0.6 were achieved from the premotor to motor area during execution/imagination tasks of right and left finger movements, respectively. Ese results provided a new insight into motor execution and motor imagery based on hand gestures, which might be useful to build a new biomarker of finger motor recovery for partially or even completely plegic patients. Significant difference of the G-causality coefficient was observed during left finger execution and imagery, but it was not observed during right finger execution and imagery phases. Ese results suggested that different MI-based brain motor function recovery strategies should be taken for right-hand and left-hand patients after brain stroke Significant difference of the G-causality coefficient was observed during left finger execution and imagery, but it was not observed during right finger execution and imagery phases. ese results suggested that different MI-based brain motor function recovery strategies should be taken for right-hand and left-hand patients after brain stroke
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