Emotion Processing in Virtual Reality: EEG Functional Connectivity Using Weighted Phase Lag Index

Understanding the neural mechanisms of emotion is critical for advancing knowledge and treatment approaches for emotional disorders such as depression. To investigate the characteristics of different emotional states, we recruited 42 healthy participants and induced various emotions using virtual reality (VR) devices, while simultaneously recording their electroencephalogram (EEG) data. The weighted phase lag index (wPLI) method was employed to construct brain networks corresponding to different emotional states. EEG electrodes were grouped into seven functional subnetworks to integrate structural and functional information. Our findings reveal that the Default Mode Network (DMN) is most strongly associated with emotion. In both the theta and alpha bands, positive emotions exhibited higher phase synchronization within the DMN. Additionally, in the theta band, positive emotions showed greater phase synchronization in the Visual Network. These results suggest that the Visual Network and DMN play a critical role in emotion processing.Clinical RelevanceThe weighted phase lag index (wPLI) analysis revealed enhanced connectivity between the Visual Network and the Default Mode Network (DMN) during positive emotional states. Both the Visual Network and the DMN are closely associated with emotion processing.