The entropic brain - revisited

Carhart-Harris, Robin

doi:10.1016/j.neuropharm.2018.03.010

Cited by 366 publications

(416 citation statements)

References 111 publications

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“…The network dimension and matrix dimension results fit nicely with the previously described Entropic Brain Hypothesis (Carhart-Harris, 2018), which predicts that as the brain moves further from the zone of criticality, level of consciousness falls. If the fractal character is indicative of critical behaviour, then these results may show an association between decreased signs of criticality and disorders of consciousness.…”

Section: Discussionsupporting

confidence: 80%

“…The Entropic Brain Hypothesis (EBH) posits that consciousness emerges when the brain is near a critical point between order and randomness, known as criticality, and that to move too far in either direction will result in a change in the quality of consciousness, and ultimately, loss of consciousness entirely Carhart-Harris, 2018). Various studies have used different metrics to approximate the complexity of brain activity, and the results have been quite consistent, even across modalities.…”

Section: Introductionmentioning

confidence: 99%

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Fractal Dimension of Cortical Functional Connectivity Networks Predicts Severity in Disorders of Consciousness

Varley

Craig

Adapa

et al. 2019

Preprint

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Recent evidence suggests that the quantity and quality of conscious experience may be a function of the complexity of activity in the brain, and that consciousness emerges in a critical zone on the axes of order/randomness and integration/differentiation. We propose fractal shapes as a measure of proximity to this critical point, as fractal dimension encodes information about complexity beyond simple entropy or randomness, and fractal structures are known to emerge in systems nearing a critical point. To validate this, we tested the several measures of fractal dimension on the brain activity from healthy volunteers and patients with disorders of consciousness of varying severity. We used a Compact Box Burning algorithm to compute the fractal dimension of cortical functional connectivity networks as well as computing the fractal dimension of the associated adjacency matrices using a 2D box-counting algorithm. To test whether brain activity is fractal in time as well as space, we used the Higuchi temporal fractal dimension on BOLD time-series. We found significant decreases in the fractal dimension between healthy volunteers (n=15), patients in a minimally conscious state (n=10), and patients in a vegetative state (n=8), regardless of the mechanism of injury. We also found significant decreases in adjacency matrix fractal dimension and Higuchi temporal fractal dimension, which correlated with decreasing level of consciousness. These results suggest that cortical functional connectivity networks display fractal character and that this is predictive of level of consciousness in a clinically relevant population, with more fractal (i.e. more complex) networks being associated with higher levels of consciousness. This supports the hypothesis that level of consciousness and system complexity are positively associated, and is consistent with previous EEG, MEG, and fMRI studies.

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Section: Discussionsupporting

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Fractal Dimension of Cortical Functional Connectivity Networks Predicts Severity in Disorders of Consciousness

Varley

Craig

Adapa

et al. 2019

Preprint

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“…It is possible that complete ego-dissolution and the parallel unitive experience that accompanies it may be the common factor that can bridge between these different states and is also responsible for the longer-term psychological benefits associated with them. Another recent thought, is that a return of the brain to ‘criticality’ (Atasoy et al, 2017), albeit temporarily, may offer a reminder of one’s closeness with nature (Carhart-Harris, 2018) and so what is left afterwards is as much an epistemic ‘reminder’ as anything else.…”

Section: Discussionmentioning

confidence: 99%

DMT Models the Near-Death Experience

et al. 2018

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Near-death experiences (NDEs) are complex subjective experiences, which have been previously associated with the psychedelic experience and more specifically with the experience induced by the potent serotonergic, N,N-Dimethyltryptamine (DMT). Potential similarities between both subjective states have been noted previously, including the subjective feeling of transcending one’s body and entering an alternative realm, perceiving and communicating with sentient ‘entities’ and themes related to death and dying. In this within-subjects placebo-controled study we aimed to test the similarities between the DMT state and NDEs, by administering DMT and placebo to 13 healthy participants, who then completed a validated and widely used measure of NDEs. Results revealed significant increases in phenomenological features associated with the NDE, following DMT administration compared to placebo. Also, we found significant relationships between the NDE scores and DMT-induced ego-dissolution and mystical-type experiences, as well as a significant association between NDE scores and baseline trait ‘absorption’ and delusional ideation measured at baseline. Furthermore, we found a significant overlap in nearly all of the NDE phenomenological features when comparing DMT-induced NDEs with a matched group of ‘actual’ NDE experiencers. These results reveal a striking similarity between these states that warrants further investigation.

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“…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 possibility of having information theoretic based measures of consciousness, accessible from noninvasive EEG recordings, could be further leveraged to investigate a range of sleep disorders, in addition to typical, diurnal variations of the sleep-wake cycle .…”

Section: Changes In Eeg Multiscale Entropy and Power-law Frequency mentioning

confidence: 98%

“…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). 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. 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.…”

Section: Changes In Eeg Multiscale Entropy and Power-law Frequency mentioning

confidence: 99%

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

Miskovic

MacDonald

Rhodes

et al. 2018

Human Brain Mapping

161

137

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We explored changes in multiscale brain signal complexity and power‐law scaling exponents of electroencephalogram (EEG) frequency spectra across several distinct global states of consciousness induced in the natural physiological context of the human sleep cycle. We specifically aimed to link EEG complexity to a statistically unified representation of the neural power spectrum. Further, by utilizing surrogate‐based tests of nonlinearity we also examined whether any of the sleep stage‐dependent changes in entropy were separable from the linear stochastic effects contained in the power spectrum. Our results indicate that changes of brain signal entropy throughout the sleep cycle are strongly time‐scale dependent. Slow wave sleep was characterized by reduced entropy at short time scales and increased entropy at long time scales. Temporal signal complexity (at short time scales) and the slope of EEG power spectra appear, to a large extent, to capture a common phenomenon of neuronal noise, putatively reflecting cortical balance between excitation and inhibition. Nonlinear dynamical properties of brain signals accounted for a smaller portion of entropy changes, especially in stage 2 sleep.

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The entropic brain - revisited

Cited by 366 publications

References 111 publications

Fractal Dimension of Cortical Functional Connectivity Networks Predicts Severity in Disorders of Consciousness

Fractal Dimension of Cortical Functional Connectivity Networks Predicts Severity in Disorders of Consciousness

DMT Models the Near-Death Experience

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

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