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Brain Network Topology Study on Precise Grip Force Controlunder Visual Feedback |
Lv Yadong1, Li Ke1*, Hou Ying2, Zhang Dongmei2, Wei Na3,4* |
1(Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan 250061, China) 2(Department of Rehabilitation, Suzhou Hospital, Nanjing Medical University, Suzhou 215008, Jiangsu, China) 3(Department of Geriatrics, Qilu Hospital, Shandong University, Jinan 250012, China) 4(Shandong University Suzhou Research Institute, Suzhou 215000, Jiangsu, China) |
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Abstract The precise force control of grip is the key to achieve a variety of sophisticated hand functions. When human performs precise force control of grip, whether the speed and the up-down states of force change or not is dominated by different brain functional networks, and the underlying sensorimotor control mechanism remains unclear. The purpose of this study was to investigate the topology changes of the EEG function network related with the speed and up-down states of grip force changes under the vision-precision grip force tracking task. In this study, 11 healthy subjects were recruited. First, the maximum voluntary contraction (MVC) of their grip was measured, and then the subjects were requested to use the thumb and index finger of their right hand to perform vision-precision grip force tracking task at the speed of 1% MVC/s (speed 1), 2% MVC/s (speed 2), and 3% MVC/s (speed 3). The network topology parameters of average clustering coefficient C and the characteristic path length L were used to analyze the EEG functional network based on the phase lag index. The results showed that C values in the θ frequency band during up-ramp state were (0.157±0.032), (0.164±0.044), (0.194±0.039) and during down-ramp state were (0.154±0.026), (0.173±0.041), (0.211±0.058). The C increased significantly in the θ (P<0.05) and similarly in the β (P<0.001) frequency bands. Different from the change of C values, L values in the θ frequency band during up-ramp state were (4.644±0.400), (4.150±0.325), (3.909±0.497) and during down-ramp state were (4.606±0.346), (4.040±0.471), (3.716±0.498). The L decreased significantly in the θ (P<0.001) and similarly in the α, β and γ frequency bands. The local activation of central and posterior parietal were improved with the increasing speed. Except for the L value in the β band [P=0.049] under the condition of tracking speed 2, there was no significant difference between the up and down states. These results indicated that the global and local information transmission efficiency was enhanced with the increasing speed, which meant the brain network connectivity pattern was altered during the adaptation to speed differences. This study provided a basis for exploring the sensorimotor control mechanism of precision grip under the different speeds and up-down states, and provided a new evaluation method for the rehabilitation state of hand function after nervous system diseases.
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Received: 15 October 2019
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