Increased spontaneous MEG signal diversity for psychoactive doses of ketamine, LSD and psilocybin

Abstract

What is the level of consciousness of the psychedelic state? Empirically, measures of neural signal diversity such as entropy and Lempel-Ziv (LZ) complexity score higher for wakeful rest than for states with lower conscious level like propofol-induced anesthesia. Here we compute these measures for spontaneous magnetoencephalographic (MEG) signals from humans during altered states of consciousness induced by three psychedelic substances: psilocybin, ketamine and LSD. For all three, we find reliably higher spontaneous signal diversity, even when controlling for spectral changes. This increase is most pronounced for the single-channel LZ complexity measure, and hence for temporal, as opposed to spatial, signal diversity. We also uncover selective correlations between changes in signal diversity and phenomenological reports of the intensity of psychedelic experience. This is the first time that these measures have been applied to the psychedelic state and, crucially, that they have yielded values exceeding those of normal waking consciousness. These findings suggest that the sustained occurrence of psychedelic phenomenology constitutes an elevated level of consciousness -as measured by neural signal diversity.Understanding the brain basis of consciousness remains one of the outstanding challenges in modern science. While rigorous definitions are still mainly lacking, consciousness can be defined rather broadly as that which "vanishes every night when we fall into dreamless sleep" and returns the next morning when we wake up 1 . Equally, when we are conscious, our conscious experiences are populated by a variety of perceptions, thoughts, and feelings that collectively form an integrated conscious scene. These observations lead to an intuitive distinction between conscious level (how conscious one is) and conscious content (what one is conscious of, when one is conscious). The large majority of recent neuroscientific research into consciousness has treated these dimensions separately 2-5 . Investigations of conscious level typically contrast global changes in brain activity among different states including wakeful awareness, various sleep stages, and different forms of anaesthesia. Many of these studies attempt to isolate neural changes that accompany alterations of conscious level independently of changes in general physiological arousal. Studies of conscious content have focused primarily on uncovering differences in brain activity between closely matched conscious and unconscious perception, while conscious level is maintained constant 6 .Recently, following early suggestions that increased conscious level may be related to an increased range of conscious contents 3,7 , there has been growing interest in characterising how conscious level and conscious content may relate 2,5 . One empirical approach to this question is to apply emerging measures of conscious level to experimental manipulations that primarily affect conscious content. Here, we capitalise on the profound effects on conscious phenomenology elicited by...

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

“…The rationale for use of the surrogates is the following: linear processes are completely accounted for by the second order statistics (power spectrum) of a time series. Surrogate sets were generated separately for every participant, electrode channel and sleep stage (using a maximum number of 100 iterations) and then, these surrogates were used to construct ratio scores of original relative to surrogate data, similar to what has been reported in other studies (Schartner, Carhart-Harris, et al, 2017;Schartner, Pigorini, et al, 2017). The surrogate signals are generated by keeping the power spectrum constant, while randomly shuffling phase (which destroys higher-order correlations) and in the final step, performing an inverse Fourier transform back into the time domain (Theiler et al, 1992).…”

“…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.…”

“…The algorithm that we used to construct the surrogates was the iterated amplitude adjusted Fourier transform (IAAFT) which minimizes the spurious detection of nonlinearity (Schreiber & Schmitz, 1996). Surrogate sets were generated separately for every participant, electrode channel and sleep stage (using a maximum number of 100 iterations) and then, these surrogates were used to construct ratio scores of original relative to surrogate data, similar to what has been reported in other studies (Schartner, Carhart-Harris, et al, 2017;Schartner, Pigorini, et al, 2017). In brief, the normalized ratios were calculated as MDE original / MDE surrogate for each sleep stage.…”

“…The high amounts of variance in EEG entropy explained by variation in PSD 0.5-35 Hz slopes-between 60 and 70% at fine time scales and approximately 40% at coarse scales-indicates that a substantial portion of the state-dependent changes in scalp EEG complexity is driven by linear stochastic effects (see also Pereda, Gamundi, Rial, &González, 1998 andShen, Olbrich, Achermann, &Meier, 2003 for additional evidence of weak nonlinearity in human sleep EEG). However, higherorder dynamical properties of brain activity also accounted for some of the stage-dependent complexity changes (see also Schartner, Carhart-Harris, et al, 2017;Schartner, Pigorini, et al, 2017). This conclusion can be drawn from two separate lines of evidence.…”

How Do We Explain ‛Autistic Traits’ in European Upper Palaeolithic Art?

“…Psychedelic drugs do change sensory experience, and create changes in emotions and an expansion of an individual's sense of thought and identity (Sessa, 2008;Schartner et al, 2017). Some of the largest studies were carried out in the late 1950s and 1960s for example.…”