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...

Emerging neural theories of consciousness suggest a correlation between a specific type of neural dynamical complexity and the level of consciousness: When awake and aware, causal interactions between brain regions are both integrated (all regions are to a certain extent connected) and differentiated (there is inhomogeneity and variety in the interactions). In support of this, recent work by Casali et al (2013) has shown that Lempel-Ziv complexity correlates strongly with conscious level, when computed on the EEG response to transcranial magnetic stimulation. Here we investigated complexity of spontaneous high-density EEG data during propofol-induced general anaesthesia. We consider three distinct measures: (i) Lempel-Ziv complexity, which is derived from how compressible the data are; (ii) amplitude coalition entropy, which measures the variability in the constitution of the set of active channels; and (iii) the novel synchrony coalition entropy (SCE), which measures the variability in the constitution of the set of synchronous channels. After some simulations on Kuramoto oscillator models which demonstrate that these measures capture distinct ‘flavours’ of complexity, we show that there is a robustly measurable decrease in the complexity of spontaneous EEG during general anaesthesia.

Studying transitions in and out of the altered state of consciousness caused by intravenous (IV) N,N-Dimethyltryptamine (DMT - a fast-acting tryptamine psychedelic) offers a safe and powerful means of advancing knowledge on the neurobiology of conscious states. Here we sought to investigate the effects of IV DMT on the power spectrum and signal diversity of human brain activity (6 female, 7 male) recorded via multivariate EEG, and plot relationships between subjective experience, brain activity and drug plasma concentrations across time. Compared with placebo, DMT markedly reduced oscillatory power in the alpha and beta bands and robustly increased spontaneous signal diversity. Time-referenced and neurophenomenological analyses revealed close relationships between changes in various aspects of subjective experience and changes in brain activity. Importantly, the emergence of oscillatory activity within the delta and theta frequency bands was found to correlate with the peak of the experience - particularly its eyes-closed visual component. These findings highlight marked changes in oscillatory activity and signal diversity with DMT that parallel broad and specific components of the subjective experience, thus advancing our understanding of the neurobiological underpinnings of immersive states of consciousness.

Key to understanding the neuronal basis of consciousness is the characterization of the neural signatures of changes in level of consciousness during sleep. Here we analysed three measures of dynamical complexity on spontaneous depth electrode recordings from 10 epilepsy patients during wakeful rest (WR) and different stages of sleep: (i) Lempel–Ziv complexity, which is derived from how compressible the data are; (ii) amplitude coalition entropy, which measures the variability over time of the set of channels active above a threshold; (iii) synchrony coalition entropy, which measures the variability over time of the set of synchronous channels. When computed across sets of channels that are broadly distributed across multiple brain regions, all three measures decreased substantially in all participants during early-night non-rapid eye movement (NREM) sleep. This decrease was partially reversed during late-night NREM sleep, while the measures scored similar to WR during rapid eye movement (REM) sleep. This global pattern was in almost all cases mirrored at the local level by groups of channels located in a single region. In testing for differences between regions, we found elevated signal complexity in the frontal lobe. These differences could not be attributed solely to changes in spectral power between conditions. Our results provide further evidence that the level of consciousness correlates with neural dynamical complexity.

Noninvasive behavioral tracking of animals is crucial for many scientific investigations. Recent transfer learning approaches for behavioral tracking have considerably advanced the state of the art. Typically these methods treat each video frame and each object to be tracked independently. In this work, we improve on these methods (particularly in the regime of few training labels) by leveraging the rich spatiotemporal structures pervasive in behavioral video --- specifically, the spatial statistics imposed by physical constraints (e.g., paw to elbow distance), and the temporal statistics imposed by smoothness from frame to frame. We propose a probabilistic graphical model built on top of deep neural networks, Deep Graph Pose (DGP), to leverage these useful spatial and temporal constraints, and develop an efficient structured variational approach to perform inference in this model. The resulting semi-supervised model exploits both labeled and unlabeled frames to achieve significantly more accurate and robust tracking while requiring users to label fewer training frames. In turn, these tracking improvements enhance performance on downstream applications, including robust unsupervised segmentation of behavioral "syllables," and estimation of interpretable "disentangled" low-dimensional representations of the full behavioral video.

What are the global neuronal signatures of altered states of consciousness (ASC)?Recently, increases in neural signal diversity, compared to those found in wakeful rest, have been reported during psychedelic states. Neural signal diversity has previously been identified as a robust signature of the state of consciousness, showing lower scores during sleep or anaesthesia compared to wakeful rest. The increased neural signal diversity during psychedelic states raises the additional possibility that it may also reflect the increased diversity of subjective experiences associated with these states. However, psychedelic states involve widespread neuropsychopharmacological changes, only some of which may be associated with altered phenomenology. Therefore, we used stroboscopic stimulation to induce nonpharmacological altered states of consciousness while measuring the diversity of EEG signals. Stroboscopic stimulation caused substantial increases in the intensity and range of subjective experiences, with reports of both simple and complex visual hallucinations. These experiences were accompanied by increases in EEG signal diversity scores (measured using Lempel-Ziv complexity) exceeding those associated with wakeful rest, in line with studies of the psychedelic state. Our findings support the proposal that EEG signal diversity reflects the diversity of subjective experience that is associated with different states of consciousness.

Obsessive-compulsive disorder (OCD) is a circuit disorder involving corticostriatal projections, which play a role in motor control. The Sapap3-knockout (KO) mouse is a mouse model to study OCD and recapitulates OCD-like compulsion through excessive grooming behavior, with skin lesions appearing at advanced age. Deficits in corticostriatal control provide a link to the pathophysiology of OCD. However, there remain significant gaps in the characterization of the Sapap3-KO mouse, with respect to age, specificity of synaptic dysfunction, and locomotor phenotype. We therefore investigated the corticostriatal synaptic phenotype of Sapap3-KO mice using patch-clamp slice electrophysiology, in adult mice and with projection-specificity. We also analyzed grooming across age and locomotor phenotype with a novel, unsupervised machine learning technique (MoSeq). Increased grooming in Sapap3-KO mice without skin lesions was age-independent. Synaptic deficits persisted in adulthood and involved the projections from the motor cortices and cingulate cortex to the dorsolateral and dorsomedial striatum. Decreased synaptic strength was evident at the input from the primary motor cortex by reduction in AMPA receptor function. Hypolocomotion, i.e. slowness of movement, was consistently observed in Sapap3-KO mice. Our findings emphasize the utility of young adult Sapap3-KO mice to investigate corticostriatal synaptic dysfunction in motor control.

Understanding whole-brain-scale electrophysiological recordings will rely on the collective work of multiple labs. Because two labs recording from the same brain area often reach different conclusions, it is critical to quantify and control for features that decrease reproducibility. To address these issues, we formed a multi-lab collaboration using a shared, open-source behavioral task and experimental apparatus. We repeatedly inserted Neuropixels multi-electrode probes targeting the same brain locations (including posterior parietal cortex, hippocampus, and thalamus) in mice performing the behavioral task. We gathered data across 9 labs and developed a common histological and data processing pipeline to analyze the resulting large datasets. After applying stringent behavioral, histological, and electrophysiological quality-control criteria, we found that neuronal yield, firing rates, spike amplitudes, and task-modulated neuronal activity were reproducible across laboratories. To quantify variance in neural activity explained by task variables (e.g., stimulus onset time), behavioral variables (timing of licks/paw movements), and other variables (e.g., spatial location in the brain or the lab ID), we developed a multi-task neural network encoding model that extends common, simpler regression approaches by allowing nonlinear interactions between variables. We found that within-lab random effects captured by this model were comparable to between-lab random effects. Taken together, these results demonstrate that across-lab standardization of electrophysiological procedures can lead to reproducible results across labs. Moreover, our protocols to achieve reproducibility, along with our analyses to evaluate it are openly accessible to the scientific community, along with our extensive electrophysiological dataset with corresponding behavior and open-source analysis code.