Large Scale Resting-State Network Connectivities Predict Verbal Suggestibility
Yeganeh Farahzadi, Zoltan Kekecs, Eötvös Loránd University, Hungary
Posters 3 Poster
Pacific Ballroom H-O
Sat, 27 Aug, 19:30 - 21:30 Pacific Time (UTC -8)
Behavioral evidence suggests that hypnotizability is associated with the reconfiguration of the control processes. However, it is not clear whether those reconfigurations are specific to the control networks in the brain or general to all the networks including sensorimotor, salience, and default mode networks. In the current study, we use EEG functional connectivity across all the networks, regardless of being control-related or not, and train a classification model that predicts self-report of hypnotic experience. We show that network connectivity successfully classifies highly susceptible participants as evaluated by the accuracy on a held-out test set. Further feature importance analysis reveals that the most contributing connectivities are within the control networks — i.e. Dorsal Attention Network (DAN), Ventral Attention Network (VAN), and Frontal-Parietal (FPN) — rather than sensorimotor networks.