Cannabinoid-glutamate interactions and neural oscillations: implications for psychosis.

Preclinical and clinical data suggest that the cannabinoid and glutamatergic systems are implicated in the pathophysiology of schizophrenia (SZ), the prototypical psychotic disorder. This has led to distinct "cannabis" and "ketamine" models of SZ, respectively. However, these two models need not be mutually exclusive. Indeed, in several brain regions implicated in the putative neural circuitry of SZ (e.g., hippocampus, frontal cortex, cerebellum), cannabinoid receptor type 1 (CB1Rs) and glutamate N-methyl-D-aspartate receptors (NMDARs) have direct and indirect interactions. CB1R agonists and NMDAR antagonists act upon gamma-aminobutyric acid (GABA) interneurons to reduce GABAergic neurotransmission. This would be predicted to result in the unsynchronized activity of pyramidal neurons, disrupting neural network oscillations involved in information processing, thus leading to psychotomimetic effects. Hence, the overarching aim of the current review is to synthesize the known literature on cannabinoids and glutamate in the context of neural oscillations in SZ. First, discussion of SZ and the basic mechanisms of neural oscillations are discussed, including a summary of the role of theta (4-7 Hz) and gamma (30-80 Hz) oscillations in neurocognition. Next, a brief review of the role of the cannabinoid and glutamatergic systems in SZ is outlined, followed by discussion of the known synaptic interactions between these two systems. Finally, the potential role of CB1Rs and NMDARs, both independently and in combination, on neural oscillations in relation to psychotic symptoms is considered. It is hoped that this review will yield a series of testable hypotheses that may be used to further elucidate the pathophysiology of SZ.

A robust deep learning detector for sleep spindles and K-complexes: towards population norms.

Sleep spindles (SSs) and K-complexes (KCs) are brain patterns involved in cognitive functions that appear during sleep. Large-scale sleep studies would benefit from precise and robust automatic sleep event detectors, capable of adapting the variability in both electroencephalography (EEG) signals and expert annotation rules. We introduce the Sleep EEG Event Detector (SEED), a deep learning system that outperforms existing approaches in SS and KC detection, reaching an F1-score of 80.5% and 83.7%, respectively, on the MASS2 dataset. SEED transfers well and requires minimal fine-tuning for new datasets and annotation styles. Remarkably, SEED substantially reduces the required amount of annotated data by using a novel pretraining approach that leverages the rule-based detector A7. An analysis of 11,224 subjects revealed that SEED's detections provide better estimates of SS population statistics than existing approaches. SEED is a powerful resource for obtaining sleep-event statistics that could be useful for establishing population norms.

The Relationship Between Cannabinoids and Neural Oscillations: How Cannabis Disrupts Sensation, Perception, and Cognition.

Disruptions in neural oscillations are believed to be one critical mechanism by which cannabinoids, such as delta-9-tetrahyrdrocannabinol (THC; the primary psychoactive constituent of cannabis), perturbs brain function. Here we briefly review the role of synchronized neural activity, particularly in the gamma (30-80 Hz) and theta (4-7 Hz) frequency range, in sensation, perception, and cognition. This is followed by a review of clinical studies utilizing electroencephalography (EEG) which have demonstrated that both chronic and acute cannabinoid exposure disrupts neural oscillations in humans. We also offer a hypothetical framework through which endocannabinoids modulate neural synchrony at the network level. This also includes speculation on how both chronic and acute cannabinoids disrupt functionally relevant neural oscillations by altering the fine tuning of oscillations and the inhibitory/excitatory balance of neural circuits. Finally, we highlight important clinical implications of such oscillatory disruptions, such as the potential relationship between cannabis use, altered neural synchrony, and disruptions in sensation, perception, and cognition, which are perturbed in disorders such as schizophrenia.

Going deep into schizophrenia with artificial intelligence.

Despite years of research, the mechanisms governing the onset, relapse, symptomatology, and treatment of schizophrenia (SZ) remain elusive. The lack of appropriate analytic tools to deal with the heterogeneity and complexity of SZ may be one of the reasons behind this situation. Deep learning, a subfield of artificial intelligence (AI) inspired by the nervous system, has recently provided an accessible way of modeling and analyzing complex, high-dimensional, nonlinear systems. The unprecedented accuracy of deep learning algorithms in classification and prediction tasks has revolutionized a wide range of scientific fields and is rapidly permeating SZ research. Deep learning has the potential of becoming a valuable aid for clinicians in the prediction, diagnosis, and treatment of SZ, especially in combination with principles from Bayesian statistics. Furthermore, deep learning could become a powerful tool for uncovering the mechanisms underlying SZ thanks to a growing number of techniques designed for improving model interpretability and causal reasoning. The purpose of this article is to introduce SZ researchers to the field of deep learning and review its latest applications in SZ research. In general, existing studies have yielded impressive results in classification and outcome prediction tasks. However, methodological concerns related to the assessment of model performance in several studies, the widespread use of small training datasets, and the little clinical value of some models suggest that some of these results should be taken with caution.

Highs and lows of cannabinoid-dopamine interactions: effects of genetic variability and pharmacological modulation of catechol-O-methyl transferase on the acute response to delta-9-tetrahydrocannabinol in humans.

RATIONALE: The catechol-O-methyl transferase (COMT) enzyme has been implicated in determining dopaminergic tone and the effects of delta-9-tetrahydrocannabinol (THC) in the human brain. OBJECTIVE: This study was designed to evaluate the effect of (1) a functional polymorphism and (2) acute pharmacological inhibition of COMT on the acute response to THC in humans. METHODS: Sub-study I: The effect of intravenous (IV) THC (0.05 mg/kg) was investigated in 74 healthy subjects genotyped for the COMT rs4680 (Val/Met) polymorphism in a 2-test-day double-blind, randomized, placebo-controlled study. Sub-study II: COMT rs4680 homozygous subjects (Val/Val and Met/Met) from sub-study I received the COMT enzyme inhibitor tolcapone (200 mg) followed by IV THC or placebo on two additional test days. Subjective, behavioral, and cognitive data were obtained periodically on each test day. RESULTS: Sub-study I: Val/Val individuals were most sensitive to THC-induced attention and working memory deficits. In contrast, the psychotomimetic and subjective effects of THC were not influenced by COMT genotype. Sub-study II: Tolcapone reduced THC-induced working memory deficits, but not THC's psychotomimetic effects. Tolcapone and COMT genotype (met/met) were associated with an increased report of feeling "mellow." CONCLUSIONS: The interaction between COMT rs4680 polymorphisms and tolcapone on the cognitive, but not on the psychotomimetic and overall subjective effects of THC, suggests that modulation of dopaminergic signaling may selectively influence specific cannabinoid effects in healthy individuals. The role of dopaminergic signaling in the cognitive effects of cannabinoids should be considered in drug development efforts targeting these effects. CLINICALTRIALS.GOV REGISTRATION: https://clinicaltrials.gov/ct2/show/NCT00678730?term=NCT00678730&rank=1 ClinicalTrials.gov Identifier: NCT00678730.

The dose-dependent psychomotor effects of intravenous delta-9-tetrahydrocannabinol (Δ9-THC) in humans.

BACKGROUND: Binding studies have demonstrated that levels of the cannabinoid receptor type-1 are highest in the basal ganglia and cerebellum, two areas critical for motor control. However, no studies have systematically examined the dose-related effects of intravenous delta-9-tetrahydrocannabinol, the primary cannabinoid receptor type-1 partial agonist in cannabis, on broad domains of psychomotor function in humans. AIMS: Therefore, three domains of psychomotor function were assessed in former cannabis users (cannabis abstinent for a minimum of three months; n=23) in a three test-day, within-subject, double-blind, randomized, cross-over, and counterbalanced study during which they received intravenous delta-9-tetrahydrocannabinol (placebo, 0.015 mg/kg, and 0.03 mg/kg). METHODS: Gross motor function was assessed via the Cambridge Neuropsychological Test Automated Battery Motor Screening Task, fine motor control via the Lafayette Instrument Grooved Pegboard task, and motor timing via a Paced Finger-Tapping Task. In addition, the Cambridge Neuropsychological Test Automated Battery Rapid Visual Processing Task was utilized to determine whether delta-9-tetrahydrocannabinol-induced motor deficits were confounded by disruptions in sustained attention. RESULTS/OUTCOMES: Delta-9-tetrahydrocannabinol resulted in robust dose-dependent deficits in fine motor control (Grooved Pegboard Task) and motor timing (Paced Finger-Tapping Task), while gross motor performance (Motor Screening Task) and sustained attention (Rapid Visual Processing Task) were unimpaired. Interestingly, despite the observed dose-dependent increases in motor impairment and blood levels of delta-9-tetrahydrocannabinol, subjects reported similar levels of intoxication in the two drug conditions. CONCLUSIONS/INTERPRETATION: These data suggest that while several domains of motor function are disrupted by delta-9-tetrahydrocannabinol, subjective feelings of intoxication are dissociable from cannabinoid-induced psychomotor effects. Results are discussed in terms of the potential neural mechanisms of delta-9-tetrahydrocannabinol in motor structures.

Cannabinoid receptor-mediated disruption of sensory gating and neural oscillations: A translational study in rats and humans.

Cannabis use has been associated with altered sensory gating and neural oscillations. However, it is unclear which constituent in cannabis is responsible for these effects, or whether these are cannabinoid receptor 1 (CB1R) mediated. Therefore, the present study in humans and rats examined whether cannabinoid administration would disrupt sensory gating and evoked oscillations utilizing electroencephalography (EEG) and local field potentials (LFPs), respectively. Human subjects (n = 15) completed four test days during which they received intravenous delta-9-tetrahydrocannabinol (Δ9-THC), cannabidiol (CBD), Δ9-THC + CBD, or placebo. Subjects engaged in a dual-click paradigm, and outcome measures included P50 gating ratio (S2/S1) and evoked power to S1 and S2. In order to examine CB1R specificity, rats (n = 6) were administered the CB1R agonist CP-55940, CP-55940+AM-251 (a CB1R antagonist), or vehicle using the same paradigm. LFPs were recorded from CA3 and entorhinal cortex. Both Δ9-THC (p < 0.007) and Δ9-THC + CBD (p < 0.004) disrupted P50 gating ratio compared to placebo, while CBD alone had no effect. Δ9-THC (p < 0.048) and Δ9-THC + CBD (p < 0.035) decreased S1 evoked theta power, and in the Δ9-THC condition, S1 theta negatively correlated with gating ratios (r = -0.629, p < 0.012 (p < 0.048 adjusted)). In rats, CP-55940 disrupted gating in both brain regions (p < 0.0001), and this was reversed by AM-251. Further, CP-55940 decreased evoked theta (p < 0.0077) and gamma (p < 0.011) power to S1, which was partially blocked by AM-251. These convergent human/animal data suggest that CB1R agonists disrupt sensory gating by altering neural oscillations in the theta-band. Moreover, this suggests that the endocannabinoid system mediates theta oscillations relevant to perception and cognition.

It's All in the Rhythm: The Role of Cannabinoids in Neural Oscillations and Psychosis.

Evidence has accumulated over the past several decades suggesting that both exocannabinoids and endocannabinoids play a role in the pathophysiology of schizophrenia. The current article presents evidence suggesting that one of the mechanisms whereby cannabinoids induce psychosis is through the alteration in synchronized neural oscillations. Neural oscillations, particularly in the gamma (30-80 Hz) and theta (4-7 Hz) ranges, are disrupted in schizophrenia and are involved in various areas of perceptual and cognitive function. Regarding cannabinoids, preclinical evidence from slice and local field potential recordings has shown that central cannabinoid receptor (cannabinoid receptor type 1) agonists decrease the power of neural oscillations, particularly in the gamma and theta bands. Further, the administration of cannabinoids during critical stages of neural development has been shown to disrupt the brain's ability to generate synchronized neural oscillations in adulthood. In humans, studies examining the effects of chronic cannabis use (utilizing electroencephalography) have shown abnormalities in neural oscillations in a pattern similar to those observed in schizophrenia. Finally, recent studies in humans have also shown disruptions in neural oscillations after the acute administration of delta-9-tetrahydrocannabinol, the primary psychoactive constituent in cannabis. Taken together, these data suggest that both acute and chronic cannabinoids can disrupt the ability of the brain to generate synchronized oscillations at functionally relevant frequencies. Hence, this may represent one of the primary mechanisms whereby cannabinoids induce disruptions in attention, working memory, sensory-motor integration, and many other psychosis-related behavioral effects.

Targeting the ecology within: The role of the gut-brain axis and human microbiota in drug addiction.

Despite major advances in our understanding of the brain using traditional neuroscience, reliable and efficacious treatments for drug addiction have remained elusive. Hence, the time has come to utilize novel approaches, particularly those drawing upon contemporary advances in fields outside of established neuroscience and psychiatry. Put another way, the time has come for a paradigm shift in the addiction sciences. Apropos, a revolution in the area of human health is underway, which is occurring at the nexus between enteric microbiology and neuroscience. It has become increasingly clear that the human microbiota (the vast ecology of bacteria residing within the human organism), plays an important role in health and disease. This is not surprising, as it has been estimated that bacteria living in the human body (approximately 1kg of mass, roughly equivalent to that of the human brain) outnumber human cells 10 to 1. While advances in the understanding of the role of microbiota in other areas of human health have yielded intriguing results (e.g., Clostridium difficile, irritable bowel syndrome, autism, etc.), to date, no systematic programs of research have examined the role of microbiota in drug addiction. The current hypothesis, therefore, is that gut dysbiosis plays a key role in addictive disorders. In the context of this hypothesis, this paper provides a rationale for future research to target the "gut-brain axis" in addiction. A brief background of the gut-brain axis is provided, along with a series of hypothesis-driven ideas outlining potential treatments for addiction via manipulations of the "ecology within."

Rapid Changes in CB1 Receptor Availability in Cannabis Dependent Males after Abstinence from Cannabis.

BACKGROUND: The widespread use of cannabis, the increasing legalization of "medical" cannabis, the increasing potency of cannabis and the growing recreational use of synthetic cannabinoid 1 receptor (CB1R) full agonists underscores the importance of elucidating the effects of cannabinoids on the CB1R system. Exposure to cannabinoids is known to result in CB1R downregulation. However, the precise time course of changes in CB1R availability in cannabis dependent subjects (CDs) following short and intermediate term abstinence has not been determined. METHODS: Using High Resolution Research Tomography (HRRT) and [11C]OMAR, CB1R availability as indexed by the volume of distribution (VT) [11C]OMAR was measured in male CDs (n=11) and matched healthy controls (HCs) (n=19). CDs were scanned at baseline (while they were neither intoxicated nor in withdrawal), and after 2 days and 28 days of monitored abstinence. HCs were scanned at baseline and a subset (n=4) was rescanned 28 days later. RESULTS: Compared to HCs, [11C]OMAR VT was 15% lower in CDs (effect size Cohen's d=-1.11) at baseline in almost all brain regions. However, these group differences in CB1R availability were no longer evident after just 2 days of monitored abstinence from cannabis. There was a robust negative correlation between CB1R availability and withdrawal symptoms after 2 days of abstinence. Finally, there were no significant group differences in CB1R availability in CDs after 28 days of abstinence. CONCLUSIONS: Cannabis dependence is associated with CB1R downregulation, which begins to reverse surprisingly rapidly upon termination of cannabis use and may continue to increase over time.

Rapid Changes in Cannabinoid 1 Receptor Availability in Cannabis-Dependent Male Subjects After Abstinence From Cannabis.

BACKGROUND: The widespread use of cannabis, the increasing legalization of "medical" cannabis, the increasing potency of cannabis, and the growing recreational use of synthetic cannabinoid 1 receptor (CB1R) full agonists all underscore the importance of elucidating the effects of cannabinoids on the CB1R system. Exposure to cannabinoids is known to result in CB1R downregulation. However, the precise time course of changes in CB1R availability in cannabis-dependent (CD) subjects after short-term and intermediate-term abstinence has not been determined. METHODS: Using high-resolution research tomography and the reversible ligand [11C]OMAR, CB1R availability as indexed by the [11C]OMAR volume of distribution was measured in male CD subjects (n = 11) and matched healthy control (HC) subjects (n = 19). The CD subjects were scanned at baseline (while they were neither intoxicated nor in withdrawal) and after 2 days and 28 days of monitored abstinence. The HC subjects were scanned at baseline, and a subset (n = 4) was scanned again 28 days later. RESULTS: Compared with HC subjects, [11C]OMAR volume of distribution was 15% lower in CD subjects (effect size Cohen's d = -1.11) at baseline in almost all brain regions. However, these group differences in CB1R availability were no longer evident after just 2 days of monitored abstinence from cannabis. There was a robust negative correlation between CB1R availability and withdrawal symptoms after 2 days of abstinence. There were no significant group differences in CB1R availability in CD subjects after 28 days of abstinence. CONCLUSIONS: Cannabis dependence is associated with CB1R downregulation, which begins to reverse rapidly on termination of cannabis use and may continue to increase over time.

The psychosis-like effects of Δ(9)-tetrahydrocannabinol are associated with increased cortical noise in healthy humans.

BACKGROUND: Drugs that induce psychosis may do so by increasing the level of task-irrelevant random neural activity or neural noise. Increased levels of neural noise have been demonstrated in psychotic disorders. We tested the hypothesis that neural noise could also be involved in the psychotomimetic effects of delta-9-tetrahydrocannabinol (Δ(9)-THC), the principal active constituent of cannabis. METHODS: Neural noise was indexed by measuring the level of randomness in the electroencephalogram during the prestimulus baseline period of an oddball task using Lempel-Ziv complexity, a nonlinear measure of signal randomness. The acute, dose-related effects of Δ(9)-THC on Lempel-Ziv complexity and signal power were studied in humans (n = 24) who completed 3 test days during which they received intravenous Δ(9)-THC (placebo, .015 and .03 mg/kg) in a double-blind, randomized, crossover, and counterbalanced design. RESULTS: Δ(9)-THC increased neural noise in a dose-related manner. Furthermore, there was a strong positive relationship between neural noise and the psychosis-like positive and disorganization symptoms induced by Δ(9)-THC, which was independent of total signal power. Instead, there was no relationship between noise and negative-like symptoms. In addition, Δ(9)-THC reduced total signal power during both active drug conditions compared with placebo, but no relationship was detected between signal power and psychosis-like symptoms. CONCLUSIONS: At doses that produced psychosis-like effects, Δ(9)-THC increased neural noise in humans in a dose-dependent manner. Furthermore, increases in neural noise were related with increases in Δ(9)-THC-induced psychosis-like symptoms but not negative-like symptoms. These findings suggest that increases in neural noise may contribute to the psychotomimetic effects of Δ(9)-THC.