视觉反馈作用下精确抓握力量控制的脑网络拓扑研究

doi:10.3969/j.issn.0258-8021.2021.02.05

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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.

Key words： precision grip force control phase lag index network topology electroencephalography

Received: 15 October 2019

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R318

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	Articles by authors
	Lv Yadong
	Li Ke
	Hou Ying
	Zhang Dongmei
	Wei Na

Cite this article:

Lv Yadong,Li Ke,Hou Ying, et al. Brain Network Topology Study on Precise Grip Force Controlunder Visual Feedback[J]. Chinese Journal of Biomedical Engineering, 2021, 40(2): 163-169.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2021.02.05 OR http://cjbme.csbme.org/EN/Y2021/V40/I2/163

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