基于脑电溯源的顿悟状态脑功能网络研究

Signal from the cerebral cortex can be reconstructed based on electroencephalography (EEG) by source analysis. The brain network of insight is constructed based on the cortical sourced signal and the attribute parameters of the network are calculated to explore the neural mechanism underlying insight. 64-channel EEGs are recorded from 14 volunteers when they finish Chinese remote association tasks (CRAT), the synchronization likelihood analysis are performed on the source analyzed EEGs in beta(14~30 Hz)and high gamma rhythm(50~80 Hz), the appropriate threshold is selected to construct the brain network and calculate the node degree and clustering coefficient of the network. The results show that the node degree and clustering coefficient of insight brain network are larger than that of non-insight in both beta and gamma rhythm, the brain network in gamma band shows higher values of these parameters than that in beta rhythm. The result suggests that the neural mechanism underlying insight involves increased functional connectivity and information transmission efficiency in beta rhythm, especially in gamma rhythm. Compared with the scalp EEG signal, the cortical sourced signal more accurately reflects the characteristics of cortical interregional connection. This study provides a new perspective for revealing the cognitive neural mechanism.