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Phenomenology of auto-induced cognitive trance using text mining: a prospective and exploratory group study.

Audrey Vanhaudenhuyse, Marie-Carmen Castillo, Charlotte Martial, Jitka Annen, Aminata Bicego, Floriane Rousseaux, Leandro R D Sanz, Corine Sombrun, Antoine Bioy, Olivia Gosseries

Neuroscience of consciousness January 1, 2024 DOI: 10.1093/nc/niae036 via PubMed

Summary

AI-generated from the abstract

Auto-induced cognitive trance (AICT) produces richer and more distinct subjective experiences than ordinary rest, auditory stimulation, or imagination. In 27 trained participants, free recalls of experiences were longer during AICT than in other conditions. Text mining identified four distinct classes of discourse, with AICT forming its own class clearly separate from ordinary conscious states. Nine content categories emerged, including nature, animals, body modifications, and difficulty describing thoughts. AICT was specifically characterized by reports of nature, animals, body modifications, and difficulty describing thoughts. These findings indicate that AICT generates a unique and richer phenomenology compared to other conscious states.

Study at a glance

Characteristics Experimental study Randomized Peer reviewed
Sample size 27
Population Trained participants who can practise auto-induced cognitive trance
Intervention Auto-induced cognitive trance
Duration Five pseudo-randomized experimental sessions
Topics Philosophy of mind
Keywords Auto-induced cognitive trance Narrative content Subjective experience Text mining
Citations 7
Key finding Auto-induced cognitive trance yields longer and phenomenologically richer reports with distinct content categories, including nature, animals, body modifications, and difficulty describing thoughts, compared to ordinary conscious states.

Abstract

Auto-induced cognitive trance (AICT) is a modified state of consciousness derived from shamanic tradition that can be practised by individuals after specific training. The aim of this work was to characterize the phenomenological experiences of AICT, using text mining analysis. Free recalls of subjective experiences were audio-recorded in 27 participants after five pseudo-randomized experimental sessions: ordinary conscious resting state, with auditory stimulation and with an imaginary mental task, as well as during AICT with and without auditory stimulation. Recordings were transcribed, normalized total word counts were calculated for each condition, and analyses of content were performed using IRaMuTeQ software. Results showed that the length of the participants' reports was higher for AICT compared to the other conditions, and that the content could be categorized into four classes of discourse: AICT memory, AICT, ordinary conscious states, and AICT with and without stimulation. AICT was also characterized by specific content compared to rest, auditory stimulation, and imagination conditions. Content analysis of the narrative revealed nine categories encompassing the presence of nature, people, animals, positive and negative features, sensory perceptions, body modifications, metacognition, and difficulty of describing thoughts. Among these categories, AICT is specifically characterized by reports related to the presence of nature, animals, body modifications, as well as the difficulty of describing thoughts. These results suggest that a richer phenomenology was reported during AICT, compared to the other conditions, and that AICT constitutes a class of discourse on its own, with a clear dissociation from the other conditions.

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