Ongoing Dynamics of Peak Alpha Frequency Characterize Hypnotic Induction in Highly Hypnotic-Susceptible Individuals

Author:

Landry Mathieu1,da Silva Castanheira Jason2,Rousseaux Floriane3,Rainville Pierre45ORCID,Ogez David36,Jerbi Karim789

Affiliation:

1. Département de Psychologie, Université du Québec à Trois-Rivières, Trois-Rivières, QC G9A 5H7, Canada

2. Department of Experimental Psychology, University College London, London WC1E 6BT, UK

3. Centre de Recherche Hôpital Maisonneuve-Rosemont, Montreal, QC H1T 2M4, Canada

4. Départment de Stomatologie, Faculté de Médecine Dentaire, Université de Montréal, Montréal, QC H3T 1J4, Canada

5. Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal (CRIUGM), Université de Montréal, Montréal, QC H3W 1W6, Canada

6. Département d’Anesthésiologie et de Médecine de la Douleur, Université de Montréal, Montreal, QC H3C 3J7, Canada

7. Département de Psychologie, Université de Montréal, Montreal, QC H3C 3J7, Canada

8. MILA-Quebec Artificial Intelligence Institute, Montreal, QC H2S 3H1, Canada

9. UNIQUE Center (Quebec Neuro-AI Research Center), Montreal, QC H3T 1P1, Canada

Abstract

Hypnotic phenomena exhibit significant inter-individual variability, with some individuals consistently demonstrating efficient responses to hypnotic suggestions, while others show limited susceptibility. Recent neurophysiological studies have added to a growing body of research that shows variability in hypnotic susceptibility is linked to distinct neural characteristics. Building on this foundation, our previous work identified that individuals with high and low hypnotic susceptibility can be differentiated based on the arrhythmic activity observed in resting-state electrophysiology (rs-EEG) outside of hypnosis. However, because previous work has largely focused on mean spectral characteristics, our understanding of the variability over time of these features, and how they relate to hypnotic susceptibility, is still limited. Here we address this gap using a time-resolved assessment of rhythmic alpha peaks and arrhythmic components of the EEG spectrum both prior to and following hypnotic induction. Using multivariate pattern classification, we investigated whether these neural features differ between individuals with high and low susceptibility to hypnosis. Specifically, we used multivariate pattern classification to investigate whether these non-stationary neural features could distinguish between individuals with high and low susceptibility to hypnosis before and after a hypnotic induction. Our analytical approach focused on time-resolved spectral decomposition to capture the intricate dynamics of neural oscillations and their non-oscillatory counterpart, as well as Lempel–Ziv complexity. Our results show that variations in the alpha center frequency are indicative of hypnotic susceptibility, but this discrimination is only evident during hypnosis. Highly hypnotic-susceptible individuals exhibit higher variability in alpha peak center frequency. These findings underscore how dynamic changes in neural states related to alpha peak frequency represent a central neurophysiological feature of hypnosis and hypnotic susceptibility.

Funder

Bial

Fonds de Recherche du Québec—Nature et Technologies

Natural Sciences and Engineering Research Council

Fonds de recherche du Québec

Canada Research Chairs

Publisher

MDPI AG

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