Chen Zemeng, Ji Xiang, Li Ting, Gao Chenyang, Li Guorui, Liu Shuyu, Zhang Yingyuan
Institute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China.
Applied Physiology and Kinesiology, College of Health and Human Performance, University of Florida, Gainesville, FL, United States.
Front Psychiatry. 2023 Aug 23;14:1221381. doi: 10.3389/fpsyt.2023.1221381. eCollection 2023.
Conflict monitoring and processing is an important part of the human cognitive system, it plays a key role in many studies of cognitive disorders.
Based on a Chinese word-color match Stroop task, which included incongruent and neutral stimuli, the Electroencephalogram (EEG) and functional Near-infrared Spectroscopy (fNIRS) signals were recorded simultaneously. The Pearson correlation coefficient matrix was calculated to analyze brain connectivity based on EEG signals. Granger Causality (GC) method was employed to analyze the effective connectivity of bilateral frontal lobes. Wavelet Transform Coherence (WTC) was used to analyze the functional connectivity of the bilateral hemisphere and ipsilateral hemisphere.
Results indicated that brain connectivity analysis on EEG signals did not show any significant lateralization, while fNIRS analysis results showed the frontal lobes especially the left frontal lobe play the leading role in dealing with conflict tasks. The human brain shows leftward lateralization while processing the more complicated incongruent stimuli. This is demonstrated by the higher functional connectivity in the left frontal lobe and the information flow from the left frontal lobe to the right frontal lobe.
Our findings in brain connectivity during cognitive conflict processing demonstrated that the dual modality method combining EEG and fNIRS is a valuable tool to excavate more information through cognitive and physiological studies.
冲突监测与处理是人类认知系统的重要组成部分,在许多认知障碍研究中发挥着关键作用。
基于一个中文词-颜色匹配的Stroop任务,该任务包括不一致和中性刺激,同时记录脑电图(EEG)和功能性近红外光谱(fNIRS)信号。计算Pearson相关系数矩阵以基于EEG信号分析脑连接性。采用格兰杰因果关系(GC)方法分析双侧额叶的有效连接性。使用小波变换相干性(WTC)分析双侧半球和同侧半球的功能连接性。
结果表明,对EEG信号的脑连接性分析未显示出任何显著的偏侧化,而fNIRS分析结果表明额叶尤其是左额叶在处理冲突任务中起主导作用。人类大脑在处理更复杂的不一致刺激时表现出向左偏侧化。这通过左额叶中更高的功能连接性以及从左额叶到右额叶的信息流得到证明。
我们在认知冲突处理过程中的脑连接性研究结果表明,结合EEG和fNIRS的双模态方法是通过认知和生理研究挖掘更多信息的有价值工具。