摘要
为研究情绪重评时的大脑皮层源活动,针对情绪重评实验范式下采集的15例健康人同步EEG-fMRI数据,首先提出一种新颖的基于偶极子特征优化的融合源定位方法:根据fMRI加权最小范数估计源定位结果,采用20 ms EEG滑动时间窗,提取每个时窗内的偶极子空间融合特征,将其作为动态融合先验进行加权最小范数估计溯源;随后将该结果与fMRI加权最小范数估计源定位结果进行情绪重评机制上的对比;最后采用样本熵进行脑电源复杂度分析。实验结果表明,该方法可以在高时间和空间分辨率下,有效地追踪情绪重评任务下大脑皮层上的脑电源动态并识别出相关脑区。情绪重评过程中,随着后枕顶叶晚期正电位的出现,显著活跃脑区从左顶叶下部、右侧额中回下部、左侧脑岛转移到右侧颞上回和左外侧枕叶,最后在晚期正电位慢波阶段激活了右侧梭状回、右侧额中回下部和右侧扣带回峡部(P<0.05)。通过脑电源样本熵的计算,提取出被试在接受不同情绪刺激后1500 ms内的显著脑区(P<0.05):情绪响应的活跃脑区为左外侧枕叶(负性:0.688±0.124,中性:0.590±0.126);情绪重评的活跃脑区为右侧额中回下部(负性重评:0.814±0.114,负性:0.736±0.123);情绪重评的抑制脑区为右侧颞上回(负性:0.642±0.152,负性重评:0.546±0.090)。这些结果为情绪重评相关的皮层脑电源定位研究提供了脑区参考。
To investigate the source activity of cerebral cortex during emotion reappraisal,a novel fused source localization method based on the dipole feature optimization was proposed for the simultaneous EEG-fMRI data of 15 healthy subjects acquired by the experimental paradigm of emotion reappraisal. First,fMRI-weighted minimum norm estimate was performed. Then 20 ms EEG sliding time window was used to extract dipole spatial fused feature in each time window. A weighted minimum norm estimation was subsequently performed based on the dynamic fused prior. The mechanism comparison of emotion reappraisal was conducted between the results of two source localization methods. Finally,the sample entropy was used to analyze the complexity of EEG source.The experimental results showed that the proposed method could effectively track the dynamics of EEG source on the cerebral cortex and recognized related brain regions during emotion reappraisal task with high temporal and spatial resolutions. In the process of emotion reappraisal,with the emergence of late positive potential in the posterior occipital parietal lobe,the active brain regions transferred from the left inferior parietal lobe,right rostral middle frontal gyrus,left insula to the right superior temporal gyrus and left lateral occipital lobe,and finally activated the right fusiform gyrus,right rostral middle frontal gyrus and right isthmus cingulate gyrus in the late positive potential slow-wave stage (P < 0. 05). By calculating the sample entropy of EEG source,the significant brain regions were extracted after the subjects received different emotional stimuli within 1500 ms (P<0. 05). The active brain region for emotion response was left lateral occipital lobe (negative: 0. 688±0. 124,neutral: 0. 590±0. 126). The active brain region for emotion reappraisal was right rostral middle frontal gyms (negative reappraisal: 0. 814 ± 0. 114,negative: 0. 736 ± 0. 123). The inhibited brain region for emotion reappraisal was right superior temporal gyrus (negative: 0. 642±0.
作者
张蔚
姜忠义
李文杰
邹凌
Zhang Wei;Jiang Zhongyi;Li Wenjie;Zou Ling(School of Microelectronics and Control Engineering,Changzhou University,Changzhou 213164,Jiangsu,China;Changzhou Key Laboratory of Biomedical Information Technology,Changzhou 213164,Jiangsu,China;Aliyun School of Big Data,Changzhou University,Changzhou 213164,Jiangsu,China)
出处
《中国生物医学工程学报》
CAS
CSCD
北大核心
2021年第3期280-290,共11页
Chinese Journal of Biomedical Engineering
基金
江苏省科技厅社会发展项目(BE2018638)
常州市社会发展项目(CE20195025)。
关键词
同步EEG-fMRI
情绪重评
源定位
偶极子特征优化
样本熵
simultaneous EEG-fMRI
emotion reappraisal
source localization
dipole feature optimization
sample entropy
