Data Sheet 1_Topological resilience of EEG-based functional networks during virtual reality-induced emotional states.docx

IntroductionVirtual reality (VR) provides an immersive environment for inducing emotional experiences, offering a naturalistic framework for investigating brain network dynamics. However, traditional emotional neuroscience has largely focused on regional activations, leaving the topological robustness and adaptive capacity of integrated brain networks underexplored. This study addresses this gap by applying a graph-theoretical framework to quantify how different emotional states modulate the resilience of functional architectures against systematic disruptions.
MethodsIn this study, we examined the resilience of EEG-based functional brain networks during negative, neutral, and positive emotional states induced by VR stimuli. Functional connectivity was computed using coherence across six frequency bands (delta to high gamma), and graph-theoretical measures were applied to characterize network topology. To assess resilience, we simulated network disruptions using two complementary approaches: targeted attacks (removing high-centrality nodes) and random failures (removing nodes randomly). Changes in global efficiency and the largest connected component were tracked as nodes were progressively removed.
ResultsOur findings revealed emotion-specific resilience profiles. In the alpha band, both negative and positive emotions demonstrated enhanced resilience to targeted attacks compared to neutral states, maintaining higher efficiency and greater network integrity, with positive emotions showing particularly strong preservation of large-scale connectivity. In the high gamma band, networks during negative emotional states exhibited greater robustness than those during positive emotions, indicating enhanced capacity to withstand targeted disruptions.
DiscussionThese findings suggest that emotional experiences are associated with differences in functional brain architecture that affect network robustness and adaptability, providing insights into neural mechanisms of emotion regulation and potential applications for emotion-aware VR systems.