Neural complexity is increased after low doses of LSD, but not moderate to high doses of oral THC or methamphetamine.

Neural complexity correlates with one's level of consciousness. During coma, anesthesia, and sleep, complexity is reduced. During altered states, including after lysergic acid diethylamide (LSD), complexity is increased. In the present analysis, we examined whether low doses of LSD (13 and 26 µg) were sufficient to increase neural complexity in the absence of altered states of consciousness. In addition, neural complexity was assessed after doses of two other drugs that significantly altered consciousness and mood: delta-9-tetrahydrocannabinol (THC; 7.5 and 15 mg) and methamphetamine (MA; 10 and 20 mg). In three separate studies (N = 73; 21, LSD; 23, THC; 29, MA), healthy volunteers received placebo or drug in a within-subjects design over three laboratory visits. During anticipated peak drug effects, resting state electroencephalography (EEG) recorded Limpel-Ziv complexity and spectral power. LSD, but not THC or MA, dose-dependently increased neural complexity. LSD also reduced delta and theta power. THC reduced, and MA increased, alpha power, primarily in frontal regions. Neural complexity was not associated with any subjective drug effect; however, LSD-induced reductions in delta and theta were associated with elation, and THC-induced reductions in alpha were associated with altered states. These data inform relationships between neural complexity, spectral power, and subjective states, demonstrating that increased neural complexity is not necessary or sufficient for altered states of consciousness. Future studies should address whether greater complexity after low doses of LSD is related to cognitive, behavioral, or therapeutic outcomes, and further examine the role of alpha desynchronization in mediating altered states of consciousness.

Consciousness in the cradle: on the emergence of infant experience.

Although each of us was once a baby, infant consciousness remains mysterious and there is no received view about when, and in what form, consciousness first emerges. Some theorists defend a 'late-onset' view, suggesting that consciousness requires cognitive capacities which are unlikely to be in place before the child's first birthday at the very earliest. Other theorists defend an 'early-onset' account, suggesting that consciousness is likely to be in place at birth (or shortly after) and may even arise during the third trimester. Progress in this field has been difficult, not just because of the challenges associated with procuring the relevant behavioral and neural data, but also because of uncertainty about how best to study consciousness in the absence of the capacity for verbal report or intentional behavior. This review examines both the empirical and methodological progress in this field, arguing that recent research points in favor of early-onset accounts of the emergence of consciousness.

Paradoxical pharmacological dissociations result from drugs that enhance delta oscillations but preserve consciousness.

Low-frequency (<4 Hz) neural activity, particularly in the delta band, is generally indicative of loss of consciousness and cortical down states, particularly when it is diffuse and high amplitude. Remarkably, however, drug challenge studies of several diverse classes of pharmacological agents-including drugs which treat epilepsy, activate GABAB receptors, block acetylcholine receptors, or produce psychedelic effects-demonstrate neural activity resembling cortical down states even as the participants remain conscious. Of those substances that are safe to use in healthy volunteers, some may be highly valuable research tools for investigating which neural activity patterns are sufficient for consciousness or its absence.

Not with a "zap" but with a "beep": Measuring the origins of perinatal experience.

When does the mind begin? Infant psychology is mysterious in part because we cannot remember our first months of life, nor can we directly communicate with infants. Even more speculative is the possibility of mental life prior to birth. The question of when consciousness, or subjective experience, begins in human development thus remains incompletely answered, though boundaries can be set using current knowledge from developmental neurobiology and recent investigations of the perinatal brain. Here, we offer our perspective on how the development of a sensory perturbational complexity index (sPCI) based on auditory ("beep-and-zip"), visual ("flash-and-zip"), or even olfactory ("sniff-and-zip") cortical perturbations in place of electromagnetic perturbations ("zap-and-zip") might be used to address this question. First, we discuss recent studies of perinatal cognition and consciousness using techniques such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and, in particular, magnetoencephalography (MEG). While newborn infants are the archetypal subjects for studying early human development, researchers may also benefit from fetal studies, as the womb is, in many respects, a more controlled environment than the cradle. The earliest possible timepoint when subjective experience might begin is likely the establishment of thalamocortical connectivity at 26 weeks gestation, as the thalamocortical system is necessary for consciousness according to most theoretical frameworks. To infer at what age and in which behavioral states consciousness might emerge following the initiation of thalamocortical pathways, we advocate for the development of the sPCI and similar techniques, based on EEG, MEG, and fMRI, to estimate the perinatal brain's state of consciousness.

Neural complexity is a common denominator of human consciousness across diverse regimes of cortical dynamics.

What is the common denominator of consciousness across divergent regimes of cortical dynamics? Does consciousness show itself in decibels or in bits? To address these questions, we introduce a testbed for evaluating electroencephalogram (EEG) biomarkers of consciousness using dissociations between neural oscillations and consciousness caused by rare genetic disorders. Children with Angelman syndrome (AS) exhibit sleep-like neural dynamics during wakefulness. Conversely, children with duplication 15q11.2-13.1 syndrome (Dup15q) exhibit wake-like neural dynamics during non-rapid eye movement (NREM) sleep. To identify highly generalizable biomarkers of consciousness, we trained regularized logistic regression classifiers on EEG data from wakefulness and NREM sleep in children with AS using both entropy measures of neural complexity and spectral (i.e., neural oscillatory) EEG features. For each set of features, we then validated these classifiers using EEG from neurotypical (NT) children and abnormal EEGs from children with Dup15q. Our results show that the classification performance of entropy-based EEG biomarkers of conscious state is not upper-bounded by that of spectral EEG features, which are outperformed by entropy features. Entropy-based biomarkers of consciousness may thus be highly adaptable and should be investigated further in situations where spectral EEG features have shown limited success, such as detecting covert consciousness or anesthesia awareness.

Consciousness is supported by near-critical slow cortical electrodynamics.

Mounting evidence suggests that during conscious states, the electrodynamics of the cortex are poised near a critical point or phase transition and that this near-critical behavior supports the vast flow of information through cortical networks during conscious states. Here, we empirically identify a mathematically specific critical point near which waking cortical oscillatory dynamics operate, which is known as the edge-of-chaos critical point, or the boundary between stability and chaos. We do so by applying the recently developed modified 0-1 chaos test to electrocorticography (ECoG) and magnetoencephalography (MEG) recordings from the cortices of humans and macaques across normal waking, generalized seizure, anesthesia, and psychedelic states. Our evidence suggests that cortical information processing is disrupted during unconscious states because of a transition of low-frequency cortical electric oscillations away from this critical point; conversely, we show that psychedelics may increase the information richness of cortical activity by tuning low-frequency cortical oscillations closer to this critical point. Finally, we analyze clinical electroencephalography (EEG) recordings from patients with disorders of consciousness (DOC) and show that assessing the proximity of slow cortical oscillatory electrodynamics to the edge-of-chaos critical point may be useful as an index of consciousness in the clinical setting.

Neural oscillations track recovery of consciousness in acute traumatic brain injury patients.

Electroencephalography (EEG), easily deployed at the bedside, is an attractive modality for deriving quantitative biomarkers of prognosis and differential diagnosis in severe brain injury and disorders of consciousness (DOC). Prior work by Schiff has identified four dynamic regimes of progressive recovery of consciousness defined by the presence or absence of thalamically-driven EEG oscillations. These four predefined categories (ABCD model) relate, on a theoretical level, to thalamocortical integrity and, on an empirical level, to behavioral outcome in patients with cardiac arrest coma etiologies. However, whether this theory-based stratification of patients might be useful as a diagnostic biomarker in DOC and measurably linked to thalamocortical dysfunction remains unknown. In this work, we relate the reemergence of thalamically-driven EEG oscillations to behavioral recovery from traumatic brain injury (TBI) in a cohort of N = 38 acute patients with moderate-to-severe TBI and an average of 1 week of EEG recorded per patient. We analyzed an average of 3.4 hr of EEG per patient, sampled to coincide with 30-min periods of maximal behavioral arousal. Our work tests and supports the ABCD model, showing that it outperforms a data-driven clustering approach and may perform equally well compared to a more parsimonious categorization. Additionally, in a subset of patients (N = 11), we correlated EEG findings with functional magnetic resonance imaging (fMRI) connectivity between nodes in the mesocircuit-which has been theoretically implicated by Schiff in DOC-and report a trend-level relationship that warrants further investigation in larger studies.

Electrophysiological Abnormalities in Angelman Syndrome Correlate With Symptom Severity.

BACKGROUND: Angelman syndrome (AS) is a rare neurodevelopmental disorder caused by the absence of functional UBE3A in neurons. Excess low-frequency oscillations as measured with electroencephalography (EEG) have been identified as a characteristic finding, but the relationship of this EEG finding to the symptomatology of AS and its significance in the pathophysiology of AS remain unknown. METHODS: We used correlations and machine learning to investigate the cross-sectional and longitudinal relationship between EEG spectral power and motor, cognitive, and language skills (Bayley Scales of Infant and Toddler Development, Third Edition); adaptive behavior (Vineland Adaptive Behavior Scales, Second Edition); AS-specific symptoms (AS Clinical Severity Scale); and the age of epilepsy onset in a large sample of children (age: 1-18 years) with AS due to a chromosomal deletion of 15q11-q13 (45 individuals with 72 visits). RESULTS: We found that after accounting for age differences, participants with stronger EEG delta-band abnormality had earlier onset of epilepsy and lower performance scores across symptom domains including cognitive, motor, and communication. Combing spatial and spectral information beyond the delta frequency band increased the cross-sectional association with clinical severity on average by approximately 45%. Furthermore, we found evidence for longitudinal correlations of EEG delta-band power within several performance domains, including the mean across Bayley Scales of Infant and Toddler Development, Third Edition, scores. CONCLUSIONS: Our results show an association between EEG abnormalities and symptom severity in AS, underlining the significance of the former in the pathophysiology of AS. Furthermore, our work strengthens the rationale for using EEG as a biomarker in the development of treatments for AS, a concept that may apply more generally to neurodevelopmental disorders.

Consciousness among delta waves: a paradox?

A common observation in EEG research is that consciousness vanishes with the appearance of delta (1-4 Hz) waves, particularly when those waves are high amplitude. High amplitude delta oscillations are frequently observed in states of diminished consciousness, including slow wave sleep, anaesthesia, generalized epileptic seizures, and disorders of consciousness, such as coma and the vegetative state. This strong correlation between loss of consciousness and high amplitude delta oscillations is thought to stem from the widespread cortical deactivation that occurs during the 'down states' or troughs of these slow oscillations. Recently, however, many studies have reported the presence of prominent delta activity during conscious states, which casts doubt on the hypothesis that high amplitude delta oscillations are an indicator of unconsciousness. These studies include work in Angelman syndrome, epilepsy, behavioural responsiveness during propofol anaesthesia, postoperative delirium, and states of dissociation from the environment such as dreaming and powerful psychedelic states. The foregoing studies complement an older, yet largely unacknowledged, body of literature that has documented awake, conscious patients with high amplitude delta oscillations in clinical reports from Rett syndrome, Lennox-Gastaut syndrome, schizophrenia, mitochondrial diseases, hepatic encephalopathy, and non-convulsive status epilepticus. At the same time, a largely parallel body of recent work has reported convincing evidence that the complexity or entropy of EEG and magnetoencephalographic signals strongly relates to an individual's level of consciousness. Having reviewed this literature, we discuss plausible mechanisms that would resolve the seeming contradiction between high amplitude delta oscillations and consciousness. We also consider implications concerning theories of consciousness, such as integrated information theory and the entropic brain hypothesis. Finally, we conclude that false inferences of unconscious states can be best avoided by examining measures of electrophysiological complexity in addition to spectral power.

Sedation-Induced Burst Suppression Predicts Positive Outcome Following Traumatic Brain Injury.

While electroencephalogram (EEG) burst-suppression is often induced therapeutically using sedatives in the intensive care unit (ICU), there is hitherto no evidence with respect to its association to outcome in moderate-to-severe neurological patients. We examined the relationship between sedation-induced burst-suppression (SIBS) and outcome at hospital discharge and at 6-month follow up in patients surviving moderate-to-severe traumatic brain injury (TBI). For each of 32 patients recovering from coma after moderate-to-severe TBI, we measured the EEG burst suppression ratio (BSR) during periods of low responsiveness as assessed with the Glasgow Coma Scale (GCS). The maximum BSR was then used to predict the Glasgow Outcome Scale extended (GOSe) at discharge and at 6 months post-injury. A multi-model inference approach was used to assess the combination of predictors that best fit the outcome data. We found that BSR was positively associated with outcomes at 6 months (P = 0.022) but did not predict outcomes at discharge. A mediation analysis found no evidence that BSR mediates the effects of barbiturates or propofol on outcomes. Our results provide initial observational evidence that burst suppression may be neuroprotective in acute patients with TBI etiologies. SIBS may thus be useful in the ICU as a prognostic biomarker.

Functional connectivity during language processing in 3-month-old infants at familial risk for autism spectrum disorder.

Auditory statistical learning (ASL) plays a role in language development and may lay a foundation for later social communication impairment. As part of a longitudinal study of infant siblings, we asked whether electroencephalography (EEG) measures of connectivity during ASL at 3 months of age-differentiated infants who showed signs of autism spectrum disorder (ASD) at age 18 months. We measured spectral power and phase coherence in the theta (4-6 Hz) and alpha (6-12 Hz) frequency bands within putative language networks. Infants were divided into ASD-concern (n = 14) and No-ASD-concern (n = 49) outcome groups based on their ASD symptoms at 18 months, measured using the Autism Diagnostic Observation Scale Toddler Module. Using permutation testing, we identified a trend toward reduced left fronto-central phase coherence at the electrode pair F9-C3 in both theta and alpha frequency bands in infants who later showed ASD symptoms at 18 months. Across outcome groups, alpha coherence at 3 months correlated with greater word production at 18 months on the MacArthur-Bates Communicative Development Inventory. This study introduces signal processing and analytic tools that account for the challenges inherent in infant EEG studies, such as short duration of recordings, considerable movement artifact, and variable volume conduction. Our results indicate that connectivity, as measured by phase coherence during 2.5 min of ASL, can be quantified as early as 3 months and suggest that early alternations in connectivity may serve as markers of resilience for neurodevelopmental impairments.

Erratum: High-voltage, diffuse delta rhythms coincide with wakeful consciousness and complexity in Angelman syndrome.

[This corrects the article DOI: 10.1093/nc/niaa005.][This corrects the article DOI: 10.1093/nc/niaa005.].

Properties of beta oscillations in Dup15q syndrome.

BACKGROUND: Duplications of 15q11.2-q13.1 (Dup15q syndrome) are highly penetrant for autism, intellectual disability, hypotonia, and epilepsy. The 15q region harbors genes critical for brain development, particularly UBE3A and a cluster of gamma-aminobutyric acid type A receptor (GABAAR) genes. We recently described an electrophysiological biomarker of the syndrome, characterized by excessive beta oscillations (12-30 Hz), resembling electroencephalogram (EEG) changes induced by allosteric modulation of GABAARs. In this follow-up study, we tested a larger cohort of children with Dup15q syndrome to comprehensively examine properties of this EEG biomarker that would inform its use in future clinical trials, specifically, its (1) relation to basic clinical features, such as age, duplication type, and epilepsy; (2) relation to behavioral characteristics, such as cognition and adaptive function; (3) stability over time; and (4) reproducibility of the signal in clinical EEG recordings. METHODS: We computed EEG power and beta peak frequency (BPF) in a cohort of children with Dup15q syndrome (N = 41, age range 9-189 months). To relate EEG parameters to clinical (study 1) and behavioral features (study 2), we examined age, duplication type, epilepsy, cognition, and daily living skills (DLS) as predictors of beta power and BPF. To evaluate stability over time (study 3), we derived the intraclass correlation coefficients (ICC) from beta power and BPF computed from children with multiple EEG recordings (N = 10, age range 18-161 months). To evaluate reproducibility in a clinical setting (study 4), we derived ICCs from beta power computed from children (N = 8, age range 19-96 months), who had undergone both research EEG and clinical EEG. RESULTS: The most promising relationships between EEG and clinical traits were found using BPF. BPF was predicted both by epilepsy status (R2 = 0.11, p = 0.038) and the DLS component of the Vineland Adaptive Behavior Scale (R2 = 0.17, p = 0.01). Beta power and peak frequency showed high stability across repeated visits (beta power ICC = 0.93, BPF ICC = 0.92). A reproducibility analysis revealed that beta power estimates are comparable between research and clinical EEG (ICC = 0.94). CONCLUSIONS: In this era of precision health, with pharmacological and neuromodulatory therapies being developed and tested for specific genetic etiologies of neurodevelopmental disorders, quantification and examination of mechanistic biomarkers can greatly improve clinical trials. To this end, the robust beta oscillations evident in Dup15q syndrome are clinically reproducible and stable over time. With future preclinical and computational studies that will help disentangle the underlying mechanism, it is possible that this biomarker could serve as a robust measure of drug target engagement or a proximal outcome measure in future disease modifying intervention trials.

High-voltage, diffuse delta rhythms coincide with wakeful consciousness and complexity in Angelman syndrome.

Abundant evidence from slow wave sleep, anesthesia, coma, and epileptic seizures links high-voltage, slow electroencephalogram (EEG) activity to loss of consciousness. This well-established correlation is challenged by the observation that children with Angelman syndrome (AS), while fully awake and displaying volitional behavior, display a hypersynchronous delta (1-4 Hz) frequency EEG phenotype typical of unconsciousness. Because the trough of the delta oscillation is associated with down-states in which cortical neurons are silenced, the presence of volitional behavior and wakefulness in AS amidst diffuse delta rhythms presents a paradox. Moreover, high-voltage, slow EEG activity is generally assumed to lack complexity, yet many theories view functional brain complexity as necessary for consciousness. Here, we use abnormal cortical dynamics in AS to assess whether EEG complexity may scale with the relative level of consciousness despite a background of hypersynchronous delta activity. As characterized by multiscale metrics, EEGs from 35 children with AS feature significantly greater complexity during wakefulness compared with sleep, even when comparing the most pathological segments of wakeful EEG to the segments of sleep EEG least likely to contain conscious mentation and when factoring out delta power differences across states. These findings (i) warn against reverse inferring an absence of consciousness solely on the basis of high-amplitude EEG delta oscillations, (ii) corroborate rare observations of preserved consciousness under hypersynchronization in other conditions, (iii) identify biomarkers of consciousness that have been validated under conditions of abnormal cortical dynamics, and (iv) lend credence to theories linking consciousness with complexity.

Correction to: Mechanisms underlying the EEG biomarker in Dup15q syndrome.

[This corrects the article DOI: 10.1186/s13229-019-0280-6.].

Mechanisms underlying the EEG biomarker in Dup15q syndrome.

Background: Duplications of 15q11.2-q13.1 (Dup15q syndrome), including the paternally imprinted gene UBE3A and three nonimprinted gamma-aminobutyric acid type-A (GABAA) receptor genes, are highly penetrant for neurodevelopmental disorders such as autism spectrum disorder (ASD). To guide targeted treatments of Dup15q syndrome and other forms of ASD, biomarkers are needed that reflect molecular mechanisms of pathology. We recently described a beta EEG phenotype of Dup15q syndrome, but it remains unknown which specific genes drive this phenotype. Methods: To test the hypothesis that UBE3A overexpression is not necessary for the beta EEG phenotype, we compared EEG from a reference cohort of children with Dup15q syndrome (n = 27) to (1) the pharmacological effects of the GABAA modulator midazolam (n = 12) on EEG from healthy adults, (2) EEG from typically developing (TD) children (n = 14), and (3) EEG from two children with duplications of paternal 15q (i.e., the UBE3A-silenced allele). Results: Peak beta power was significantly increased in the reference cohort relative to TD controls. Midazolam administration recapitulated the beta EEG phenotype in healthy adults with a similar peak frequency in central channels (f = 23.0 Hz) as Dup15q syndrome (f = 23.1 Hz). Both paternal Dup15q syndrome cases displayed beta power comparable to the reference cohort. Conclusions: Our results suggest a critical role for GABAergic transmission in the Dup15q syndrome beta EEG phenotype, which cannot be explained by UBE3A dysfunction alone. If this mechanism is confirmed, the phenotype may be used as a marker of GABAergic pathology in clinical trials for Dup15q syndrome.