Dataset for "On the state - non state theory of hypnosis: network and topological EEG findings."
Description
This dataset contains EEG recordings and derived functional connectivity and topological metrics from a study investigating the neural correlates of neutral hypnosis in high and low hypnotizable individuals. The research hypothesis explores whether neutral hypnosis represents a distinct physiological state or a modulation of ordinary consciousness. EEG data were collected from 16 high and 16 low hypnotizable participants across six experimental conditions: open eyes rest, closed eyes rest, hypnotic induction (two phases), neutral hypnosis, and post-hypnosis rest. Network and Topological Data Analysis (TDA) were applied to extract measures such as functional connectivity, total homological persistence, and persistent entropy. The results show that highs exhibit greater functional and topological homogeneity compared to lows, independent of condition. Additionally, highs displayed larger transitions in functional connectivity between conditions. These findings suggest that neutral hypnosis is a modulation of wakefulness rather than a distinct physiological state. The dataset includes raw and processed EEG signals, functional connectivity matrices, and topological descriptors, along with metadata for reproducibility. This dataset is valuable for researchers studying consciousness, hypnotizability, and the application of TDA in neuroscience. Updated code can be found at: https://github.com/nplresearch/hypnotic-state/