Psychedelics as a treatment for disorders of consciousness
Gregory SCOTT and Robin L. CARHART-HARRIS
Neuroscience of Consciousness, 2019, 5, (1), niz003
Based on its ability to increase brain complexity, a seemingly reliable index of conscious level, we propose testing the capacity of the classic psychedelic, psilocybin, to increase conscious awareness in patients with disorders of consciousness. We also confront the considerable ethical and practical challenges this proposal must address, if this hypothesis is to be directly assessed.
Key words : disorders of consciousness; psychedelics; psilocybin; complexity
Disorders of consciousness (DoC) are the most devastating form of impairment that may follow acquired brain injury. In contrast to comatose patients, those in the vegetative state (VS) and minimally conscious state (MCS) exhibit signs of wakefulness (eye opening). VS patients show no overt signs of awareness,
whereas MCS patients show minimal but clearly discernible behavioural evidence of awareness. A range of therapies have been proposed for patients with DoC, including pharmacological (e.g. zolpidem, amantadine) (Gosseries et al. 2014), invasive- [e.g. deep brain stimulation (DBS) (Vanhoecke and Hariz 2017), vagal nerve stimulation (VNS) (Corazzol et al. 2017)] and non-invasive electrical stimulation [e.g. transcranial direct current stimulation (Thibaut et al. 2014)], and transcranial magnetic stimulation (TMS) (Pistoia et al. 2013). However, no treatments have consistently shown beneficial effects on conscious awareness or functional recovery (Royal College of Physicians 2013; Giacino et al. 2014; Vanhoecke and Hariz 2017).
Classic psychedelics are currently undergoing significant investigation for the treatment of a range of psychiatric disorders (Carhart-Harris and Goodwin 2017). Here, we propose that the classic psychedelic, psilocybin, be explored as a treatment to increase conscious awareness in patients with DoC. A scientific
rationale is proposed based on findings from research into the neurobiology of DoC and the effects of psychedelics. Developments in these hitherto separate fields of inquiry now suggest a potential therapeutic avenue, based on the twin discoveries that measures of brain complexity reliably index conscious level, and that brain complexity can be increased by psychedelics (Fig. 1).
Brain Complexity and Consciousness
Complexity is a multifaceted concept that pervades many branches of the physical and life sciences. In the neurosciences, many theoretical accounts of consciousness have related the complexity of dynamics in a neural system to the manifestation of conscious experiences (Tononi et al. 1994; Edelman 2009; Ruffini 2017; Carhart-Harris 2018). One influential formulation has been that of neural complexity, proposed by Tononi and Edelman in 1994 (Tononi et al. 1994). This concept accounts for two fundamental features of consciousness, namely differentiation, the property that any particular experience is composed of many different components and is distinguishable from any other experience, and also integration, the property that any given conscious experience involves the integration of components into a unified whole. Importantly, neural complexity could, in principle, be calculated empirically, as the average mutual information—a measure of information sharing—between each subset and the rest of a system. Tononi and Edelman posited that during conscious awareness, ‘heterogeneous patterns of short-term correlations within the corticothalamic system will result in [high neural complexity]’ (Tononi et al. 1994).
Several theories of consciousness have since been advanced that emphasize a link between different formulations of complexity within brain activity and conscious level. Alongside these theoretical developments has been the introduction of a wide range of measures of dynamical complexity. These various measures reflect the diversity of definitions of complexity in use [for review, see Arsiwalla and Verschure (2018), Seth et al. (2006); see also Bassett and Gazzaniga (2011), Cocchi et al. (2017) for broader reviews in complex systems theory] and differ in the extent to which they directly capture the properties of differentiation versus integration, as well as temporal versus spatial complexity, and in their computational feasibility for large datasets.
Despite heterogenous definitions of complexity, a prediction shared by many theories of consciousness is that complexity should be high in the normal awake state and low whenever consciousness is lost, be it through anaesthesia, non-rapid eye movement (REM) sleep, or acquired brain injury. In the past two decades, a raft of empirical support for these predictions has emerged. Massimini and colleagues have provided striking evidence in favour of the principle via use of the so-called perturbational- complexity index (PCI). PCI quantifies the complexity of electroencephalogram (EEG) responses to pulses of TMS (Fig. 1A) (Casali et al. 2013). This perturbational approach has been likened to hitting a bell and measuring the complexity of the reverberations that follow. The PCI has been shown to robustly index conscious level across a range of states, including wakefulness (where the PCI is highest), sedation, non-REM sleep and anaesthesia. In patients with DoC, the PCI is lowest in VS patients, followed by patients in the MCS, then those emerged from MCS (denoted EMCS). In contrast, patients with locked-in syndrome, who have intact conscious awareness but cannot respond motorically, show PCI levels as high as healthy awake subjects (Casali et al. 2013).
At the heart of the PCI approach is quantification of the complexity of TMS-evoked EEG responses using an implementation of the Lempel-Ziv algorithm, a measure of compressibility which counts the number of unique patterns in a sequence, hence its everyday use in compressing large computer files (‘zipping’).
Importantly, the Lempel-Ziv complexity (LZC)measure can also be applied to EEG recordings of spontaneous brain activity, i.e. without TMS perturbation. Whilst there are substantial differences between the spontaneous and perturbational approach, particularly that PCI evaluates only the complexity of deterministic responses of the cortex to TMS (Casali et al. 2013), the LZC of spontaneous EEG also effectively differentiates between conscious and unconscious states [including anaesthesia (Bai et al. 2015; Schartner et al. 2015) and sleep (Schartner et al. 2017b)]. In DoC, LZC-based values of spontaneous EEG reliably discriminate VS from MCS patients (Wu et al. 2011; Sitt et al. 2014) and values increase monotonically with patients’ conscious level (Sitt et al. 2014).
Our interpretation of these spontaneous EEG results is that LZC principally captures the variability or diversity of brain activity (i.e. differentiation rather than integration), and so behaves similarly to other measures of information entropy (i.e. capturing signal diversity over time). These related entropy-based metrics also appear to track conscious level [see Schartner et al. (2015), Carhart-Harris (2018) for further discussion]. Please see Schartner et al. (2015) and Mediano et al. (2019) for further discussion of these topics, and note that, for the sake of disambiguation, from here on, when we refer to ‘complexity’ we are referring to the ‘differentiation’ component in the original conception of ‘brain complexity’, i.e. the component that is measurable via LZC or a related entropy-basedmetric.
Psychedelics Increase Brain Complexity
Until recently, it was generally assumed that, in terms of states of consciousness, brain complexity would be maximal during normal wakefulness, since all other tested states of reduced consciousness (e.g. non-REM sleep, anaesthesia, DoC) feature correspondingly lower complexity values. It was therefore remarkable to discover that brain complexity values recorded during the psychedelic state exceed those found in normal waking consciousness (Fig. 1B). Specifically, in human subjects, increases in brain complexity (LZC) in excess of those seen in normal wakefulness were observed with psilocybin, lysergic acid diethylamide (LSD) and ketamine (at ‘psychedelic-like’ doses) (Schartner et al. 2017a). This finding has been replicated using a variety of complexity measures and measurement tools, including EEG, magnetoencephalography and functional MRI [see Carhart-Harris (2018) for review]. Furthermore, the magnitude of complexity increases correlated with the subjective intensity of the psychedelic experience (Schartner et al. 2017).