Shannon entropy of brain functional complex networks under the influence of the psychedelic Ayahuasca

Abstract

The entropic brain hypothesis holds that the key facts concerning psychedelics are partially explained in terms of increased entropy of the brain’s functional connectivity. Ayahuasca is a psychedelic beverage of Amazonian indigenous origin with legal status in Brazil in religious and scientific settings. In this context, we use tools and concepts from the theory of complex networks to analyze resting state fMRI data of the brains of human subjects under two distinct conditions: (i) under ordinary waking state and (ii) in an altered state of consciousness induced by ingestion of Ayahuasca. We report an increase in the Shannon entropy of the degree distribution of the networks subsequent to Ayahuasca ingestion. We also find increased local and decreased global network integration. Our results are broadly consistent with the entropic brain hypothesis. Finally, we discuss our findings in the context of descriptions of “mind-expansion” frequently seen in self-reports of users of psychedelic drugs.

Neural correlates of the DMT experience as assessed via multivariate EEG

“…Based on the present study's results, revealing a strong and comprehensive relationship between spontaneous signal diversity (a measure intimately related to entropy 37 ) and the temporal evolution of different aspects of DMT's subjective effects, we maintain that entropy-related measures are indeed informative indices of the quality of a given state of consciousness 10,11 . An increasing number of studies have reported increased signal complexity, diversity or entropy under psychedelics using a variety of imaging metrics and psychedelic drugs 12,38,39 . The increases in signal diversity observed here were associated with the perceived intensity of the experience as well as levels of DMT in plasma.…”

“…Broadband decreases in (absolute) oscillatory power have been seen with psilocybin 7 , LSD 8 , and (the DMT-containing ceremonial brew) ayahuasca 9 . Brain imaging measures of the complexity, diversity, or entropy of brain activity have been used to index the quality of a range of different conscious states [10][11][12] and MEG studies have shown this to be increased after the administration of a range of psychedelics 13 . Recent advances in analytical methods have allowed for the decomposition of spectral power into its oscillatory and fractal (1/f) components 14 and these components are thought to have distinct functional relevancies 15 .…”

Changes in EEG multiscale entropy and power‐law frequency scaling during the human sleep cycle

“…The overall trend reported by studies encompassing human and non-human animal models, is that signal diversity decreases from wakefulness to the NREM-1 and NREM-2 stages, reaching its nadir in slow-wave sleep (SWS), before recovering to near waking levels during REM epochs (Abásolo, Simons, Morgado da Silva, Tononi, & Vyazovskiy, 2015;Acharya, Faust, Kannathal, Chua, & Laxminarayan, 2005;Bruce, Bruce, & Vennelaganti, 2009;Burioka et al, 2005;Lee, Fattinger, Mouthon, Noirhomme, & Huber, 2013;Mateos, Guevara Erra, Wennberg, & Perez Velazquez, 2018;Nicolaou & Georgiou, 2011;Shi, Shang, Ma, Sun, & Yeh, 2017). Convergent findings point to reductions of neurophysiological signal complexity during the loss of consciousness induced by anesthesia (e.g., Ferenets, Vanluchene, Lipping, Heyse, & Struys, 2007;Schartner et al, 2015;Zhang, Roy, & Jensen, 2001) while hallucinogenic drugs produce a diversification of neuronal time series patterns consistent with their profound perceptual, cognitive, and emotional effects (e.g., Schartner, Carhart-Harris, Barrett, & Seth, 2017;Tagliazucchi, Carhart-Harris, Leech, Nutt, & Chialvo, 2014;Viol, Palhano-Fontes, Onias, de Araujo, & Viswanathan, 2017). These findings have paved the way for a novel view of conscious states referred to as the entropic brain theory (Carhart-Harris, 2018;Carhart-Harris et al, 2014), according to which qualitative shifts in mental states can be directly linked to the degree of irregularity evident in macroscopic recordings of neuronal activity.…”

Decreased Directed Functional Connectivity in the Psychedelic State

“…Lebedev et al (2016) calculate voxel-level sample entropy from resting-state fMRI data, comparing LSD with placebo, and finding increased entropy in sensory and higher networks across multiple time scales. Viol et al (2017) estimate functional brain networks from resting-state fMRI data recorded under ayahuasca, finding an increase in the entropy of the network degree distribution (a measure of network complexity) in the drug state. Atasoy et al (2017) perform a "connectome-harmonic decomposition" of brain activity based on fMRI recordings under placebo and LSD (connectome harmonics are identified as spatial patterns reflecting synchronisation of activity at different spatial scales).…”