Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, Guangdong Provincial Engineering and Technology Center of Advanced and Portable Medical Devices, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China.
Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
J Neurosci Res. 2021 Apr;99(4):1108-1119. doi: 10.1002/jnr.24769. Epub 2020 Dec 23.
The functional connectivity (FC) between multiple brain regions during tasks is currently gradually being explored with functional near-infrared spectroscopy (fNIRS). However, the FC present during grip force tracking tasks performed under visual feedback remains unclear. In the present study, we used fNIRS to measure brain activity during resting states and grip force tracking tasks at 25%, 50%, and 75% of maximum voluntary contraction (MVC) in 11 healthy subjects, and the activity was measured from four target brain regions: the left prefrontal cortex (lPFC), right prefrontal cortex (rPFC), left sensorimotor cortex (lSMC), and right sensorimotor cortex (rSMC). We determined the FC between these regions utilizing three different methods: Pearson's correlation method, partial correlation method, and a pairwise maximum entropy model (MEM). The results showed that the FC of lSMC-rSMC and lPFC-rPFC (interhemispheric homologous pairs) were significantly stronger than those of other brain region pairs. Moreover, FC of lPFC-rPFC was strengthened during the 75% MVC task compared to the other task states and the resting states. The FC of lSMC-lPFC and rSMC-rPFC (intrahemispheric region pairs) strengthened with a higher task load. The results provided new insights into the FC between brain regions during visuo-guided grip force tracking tasks.
目前,功能近红外光谱(fNIRS)技术正逐渐被用于探索任务状态下多个脑区之间的功能连接(FC)。然而,在视觉反馈下进行握力跟踪任务时的 FC 仍不清楚。在本研究中,我们使用 fNIRS 技术在 11 名健康受试者的静息状态和 25%、50%和 75%最大自主收缩(MVC)的握力跟踪任务中测量了脑活动,并从四个目标脑区测量了活动:左侧前额叶皮层(lPFC)、右侧前额叶皮层(rPFC)、左侧感觉运动皮层(lSMC)和右侧感觉运动皮层(rSMC)。我们利用三种不同的方法确定了这些区域之间的 FC:皮尔逊相关法、偏相关法和成对最大熵模型(MEM)。结果表明,lSMC-rSMC 和 lPFC-rPFC(半球间同源对)之间的 FC 明显强于其他脑区对。此外,与其他任务状态和静息状态相比,75% MVC 任务时 lPFC-rPFC 的 FC 增强。lSMC-lPFC 和 rSMC-rPFC(半球内区域对)的 FC 随着任务负荷的增加而增强。研究结果为视觉引导的握力跟踪任务中脑区之间的 FC 提供了新的见解。