Abstract
INTRODUCTION: Virtual Reality mediated virtual embodiment training (VR-VET) is designed to reduce chronic pain, yet a neuroimaging marker predictive of outcomes or associated with clinical changes in pain has not been validated. This study considers four candidate EEG metrics that are associated with cognitive states of mental imagery, chronic pain intensity, and stress states. VR-VET with EEG enables measurement of these metrics and collection of kinematic data. Kinematic data serves as an indicator of functional movement. In a healthy population, this study assessed neuroimaging markers for cognitive processes involved in VET or pain perception. METHODS: EEG was collected in 16 healthy individuals during VR-VET. Candidate EEG metrics were computed. Position data for each hand was used to calculate smoothness of movement within each activity. EEG metrics and smoothness were compared between the breathwork activity and activities with active movement of arms. RESULTS: Relative global alpha was significantly different in all VET activities compared to breathwork (p < 0.001). Specifically, relative posterior alpha power (p < 0.001) and relative mu (p = 0.026) were significantly lower in all active conditions. Smoothness of the active arm varied across VET activities and was reduced compared to breathwork (p < 0.001). DISCUSSION: Neuroimaging markers are feasible to investigate VET mechanisms during movement. Relative global alpha is sensitive to VET states and may be related to motor imagery tasks or visual attention, making it a relevant EEG metric in the study of VET.