Exploring aperiodic, complexity and entropic brain changes during non-ordinary states of consciousness

Summary

A self-induced, substance-free trance state called Auto-Induced Cognitive Trance (AICT) engages frontal regions, the posterior cingulate cortex, and the left parietal cortex, brain areas linked to rich subjective experiences. Analysis of EEG recordings from 27 trained participants showed that the aperiodic component of the power spectrum, entropy, and complexity measures distinguished AICT from rest, with the aperiodic component being the strongest discriminator. Baseline neural activity in frontal and parietal regions predicted how much brain activity changed when entering the trance. These results suggest that self-induced trance states alter neural functioning in ways that may explain their intense and unique subjective qualities.

Study at a glance

Abstract

Non-ordinary states of consciousness (NOC) provide an opportunity to experience highly intense, unique, and perceptually rich subjective states. The neural mechanisms supporting these experiences remain poorly understood. This study examined brain activity associated with a self-induced, substance-free NOC known as Auto-Induced Cognitive Trance (AICT). Twenty-seven trained participants underwent high-density electroencephalography (EEG) recordings during rest and AICT. We analyzed the aperiodic component of the power spectrum (1/f), Lempel-Ziv complexity, and sample entropy from five-minute signal segments. A machine learning approach was used to classify rest and AICT, identify discriminative features, and localize their sources. We also compared EEG metrics across conditions and assessed whether baseline activity predicted the magnitude of change during AICT. Classification analyses revealed condition-specific differences in spectral exponents, complexity, and entropy. The aperiodic component showed the strongest discriminative power, followed by entropy and complexity. Source localization highlighted frontal regions, the posterior cingulate cortex, and the left parietal cortex as key contributors to the AICT state. Baseline neural activity in frontal and parietal regions predicted individual variability in the transition from rest to AICT. These findings indicate that AICT engages brain regions implicated in rich subjective experiences and provide mechanistic insights into how self-induced trance states influence neural functioning.