Trips and neurotransmitters: Discovering principled patterns across 6850 hallucinogenic experiences

The unique neural signature of your trip: Functional connectome fingerprints of subjective psilocybin experience

The emerging neuroscientific frontier of brain fingerprinting has recently established that human functional connectomes (FCs) exhibit fingerprint-like idiosyncratic features, which map onto heterogeneously distributed behavioral traits. Here, we harness brain-fingerprinting tools to extract FC features that predict subjective drug experience induced by the psychedelic psilocybin. Specifically, in neuroimaging data of healthy volunteers under the acute influence of psilocybin or a placebo, we show that, post psilocybin administration, FCs become more idiosyncratic owing to greater intersubject dissimilarity. Moreover, whereas in placebo subjects idiosyncratic features are primarily found in the frontoparietal network, in psilocybin subjects they concentrate in the default mode network (DMN). Crucially, isolating the latter revealed an FC pattern that predicts subjective psilocybin experience and is characterized by reduced within-DMN and DMN-limbic connectivity, as well as increased connectivity between the DMN and attentional systems. Overall, these results contribute to bridging the gap between psilocybin-mediated effects on brain and behavior, while demonstrating the value of a brain-fingerprinting approach to pharmacological neuroimaging.

Psilocybin analog 4-OH-DiPT enhances fear extinction and GABAergic inhibition of principal neurons in the basolateral amygdala

Psychedelics such as psilocybin show great promise for the treatment of depression and PTSD, but their long duration of action poses practical limitations for patient access. 4-OH-DiPT is a fast-acting and shorter-lasting derivative of psilocybin. Here we characterized the pharmacological profile of 4-OH-DiPT and examined its impact on fear extinction learning as well as a potential mechanism of action. First, we profiled 4-OH-DiPT at all 12 human 5-HT GPCRs. 4-OH-DiPT showed strongest agonist activity at all three 5-HT2A/2B/2C receptors with near full agonist activity at 5-HT2A. Notably, 4-OH-DiPT had comparable activity at mouse and human 5-HT2A/2B/2C receptors. In a fear extinction paradigm, 4-OH-DiPT significantly reduced freezing responses to conditioned cues in a dose-dependent manner with a greater potency in female mice than male mice. Female mice that received 4-OH-DiPT before extinction training had reduced avoidance behaviors several days later in the light dark box, elevated plus maze and novelty-suppressed feeding test compared to controls, while male mice did not show significant differences. 4-OH-DiPT produced robust increases in spontaneous inhibitory postsynaptic currents (sIPSCs) in basolateral amygdala (BLA) principal neurons and action potential firing in BLA interneurons in a 5-HT2A-dependent manner. RNAscope demonstrates that Htr2a mRNA is expressed predominantly in BLA GABA interneurons, Htr2c mRNA is expressed in both GABA interneurons and principal neurons, while Htr2b mRNA is absent in the BLA. Our findings suggest that 4-OH-DiPT activates BLA interneurons via the 5-HT2A receptor to enhance GABAergic inhibition of BLA principal neurons, which provides a potential mechanism for suppressing learned fear.

Deep CANALs: a deep learning approach to refining the canalization theory of psychopathology

Psychedelic therapy has seen a resurgence of interest in the last decade, with promising clinical outcomes for the treatment of a variety of psychopathologies. In response to this success, several theoretical models have been proposed to account for the positive therapeutic effects of psychedelics. One of the more prominent models is "RElaxed Beliefs Under pSychedelics," which proposes that psychedelics act therapeutically by relaxing the strength of maladaptive high-level beliefs encoded in the brain. The more recent "CANAL" model of psychopathology builds on the explanatory framework of RElaxed Beliefs Under pSychedelics by proposing that canalization (the development of overly rigid belief landscapes) may be a primary factor in psychopathology. Here, we make use of learning theory in deep neural networks to develop a series of refinements to the original CANAL model. Our primary theoretical contribution is to disambiguate two separate optimization landscapes underlying belief representation in the brain and describe the unique pathologies which can arise from the canalization of each. Along each dimension, we identify pathologies of either too much or too little canalization, implying that the construct of canalization does not have a simple linear correlation with the presentation of psychopathology. In this expanded paradigm, we demonstrate the ability to make novel predictions regarding what aspects of psychopathology may be amenable to psychedelic therapy, as well as what forms of psychedelic therapy may ultimately be most beneficial for a given individual.

Representational maps in the brain: concepts, approaches, and applications

Neural systems have evolved to process sensory stimuli in a way that allows for efficient and adaptive behavior in a complex environment. Recent technological advances enable us to investigate sensory processing in animal models by simultaneously recording the activity of large populations of neurons with single-cell resolution, yielding high-dimensional datasets. In this review, we discuss concepts and approaches for assessing the population-level representation of sensory stimuli in the form of a representational map. In such a map, not only are the identities of stimuli distinctly represented, but their relational similarity is also mapped onto the space of neuronal activity. We highlight example studies in which the structure of representational maps in the brain are estimated from recordings in humans as well as animals and compare their methodological approaches. Finally, we integrate these aspects and provide an outlook for how the concept of representational maps could be applied to various fields in basic and clinical neuroscience.

Data science opportunities of large language models for neuroscience and biomedicine

Large language models (LLMs) are a new asset class in the machine-learning landscape. Here we offer a primer on defining properties of these modeling techniques. We then reflect on new modes of investigation in which LLMs can be used to reframe classic neuroscience questions to deliver fresh answers. We reason that LLMs have the potential to (1) enrich neuroscience datasets by adding valuable meta-information, such as advanced text sentiment, (2) summarize vast information sources to overcome divides between siloed neuroscience communities, (3) enable previously unthinkable fusion of disparate information sources relevant to the brain, (4) help deconvolve which cognitive concepts most usefully grasp phenomena in the brain, and much more.

Exploring Novel Antidepressants Targeting G Protein-Coupled Receptors and Key Membrane Receptors Based on Molecular Structures

Major Depressive Disorder (MDD) is a complex mental disorder that involves alterations in signal transmission across multiple scales and structural abnormalities. The development of effective antidepressants (ADs) has been hindered by the dominance of monoamine hypothesis, resulting in slow progress. Traditional ADs have undesirable traits like delayed onset of action, limited efficacy, and severe side effects. Recently, two categories of fast-acting antidepressant compounds have surfaced, dissociative anesthetics S-ketamine and its metabolites, as well as psychedelics such as lysergic acid diethylamide (LSD). This has led to structural research and drug development of the receptors that they target. This review provides breakthroughs and achievements in the structure of depression-related receptors and novel ADs based on these. Cryo-electron microscopy (cryo-EM) has enabled researchers to identify the structures of membrane receptors, including the N-methyl-D-aspartate receptor (NMDAR) and the 5-hydroxytryptamine 2A (5-HT2A) receptor. These high-resolution structures can be used for the development of novel ADs using virtual drug screening (VDS). Moreover, the unique antidepressant effects of 5-HT1A receptors in various brain regions, and the pivotal roles of the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) and tyrosine kinase receptor 2 (TrkB) in regulating synaptic plasticity, emphasize their potential as therapeutic targets. Using structural information, a series of highly selective ADs were designed based on the different role of receptors in MDD. These molecules have the favorable characteristics of rapid onset and low adverse drug reactions. This review offers researchers guidance and a methodological framework for the structure-based design of ADs.

Human-like dissociations between confidence and accuracy in convolutional neural networks

Prior research has shown that manipulating stimulus energy by changing both stimulus contrast and variability results in confidence-accuracy dissociations in humans. Specifically, even when performance is matched, higher stimulus energy leads to higher confidence. The most common explanation for this effect is the positive evidence heuristic where confidence neglects evidence that disconfirms the choice. However, an alternative explanation is the signal-and-variance-increase hypothesis, according to which these dissociations arise from low-level changes in the separation and variance of perceptual representations. Because artificial neural networks lack built-in confidence heuristics, they can serve as a test for the necessity of confidence heuristics in explaining confidence-accuracy dissociations. Therefore, we tested whether confidence-accuracy dissociations induced by stimulus energy manipulations emerge naturally in convolutional neural networks (CNNs). We found that, across three different energy manipulations, CNNs produced confidence-accuracy dissociations similar to those found in humans. This effect was present for a range of CNN architectures from shallow 4-layer networks to very deep ones, such as VGG-19 and ResNet -50 pretrained on ImageNet. Further, we traced back the reason for the confidence-accuracy dissociations in all CNNs to the same signal-and-variance increase that has been proposed for humans: higher stimulus energy increased the separation and variance of the CNNs' internal representations leading to higher confidence even for matched accuracy. These findings cast doubt on the necessity of the positive evidence heuristic to explain human confidence and establish CNNs as promising models for adjudicating between low-level, stimulus-driven and high-level, cognitive explanations of human behavior.

Trajectories of sentiment in 11,816 psychoactive narratives

OBJECTIVE

Can machine learning (ML) enable data-driven discovery of how changes in sentiment correlate with different psychoactive experiences? We investigate by training models directly on text testimonials from a diverse 52-drug pharmacopeia.

METHODS

Using large language models (i.e. BERT) and 11,816 publicly-available testimonials, we predicted 28-dimensions of sentiment across each narrative, and then validated these predictions with adjudication by a clinical psychiatrist. BERT was then fine-tuned to predict biochemical and demographic information from these narratives. Lastly, canonical correlation analysis linked the drugs' receptor affinities with word usage, revealing 11 statistically-significant latent receptor-experience factors, each mapped to a 3D cortical Atlas.

RESULTS

These methods elucidate a neurobiologically-informed, sequence-sensitive portrait of drug-induced subjective experiences. The models' results converged, revealing a pervasive distinction between the universal psychedelic heights of feeling in contrast to the grim, mundane, and personal experiences of addiction and mental illness. Notably, MDMA was linked to "Love", DMT and 5-MeO-DMT to "Mystical Experiences" and "Entities and Beings", and other tryptamines to "Surprise", "Curiosity" and "Realization".

CONCLUSIONS

ML methods can create unified and robust quantifications of subjective experiences with many different psychoactive substances and timescales. The representations learned are evocative and mutually confirmatory, indicating great potential for ML in characterizing psychoactivity.

Patient-specific models link neurotransmitter receptor mechanisms with motor and visuospatial axes of Parkinson's disease

Parkinson's disease involves multiple neurotransmitter systems beyond the classical dopaminergic circuit, but their influence on structural and functional alterations is not well understood. Here, we use patient-specific causal brain modeling to identify latent neurotransmitter receptor-mediated mechanisms contributing to Parkinson's disease progression. Combining the spatial distribution of 15 receptors from post-mortem autoradiography with 6 neuroimaging-derived pathological factors, we detect a diverse set of receptors influencing gray matter atrophy, functional activity dysregulation, microstructural degeneration, and dendrite and dopaminergic transporter loss. Inter-individual variability in receptor mechanisms correlates with symptom severity along two distinct axes, representing motor and psychomotor symptoms with large GABAergic and glutamatergic contributions, and cholinergically-dominant visuospatial, psychiatric and memory dysfunction. Our work demonstrates that receptor architecture helps explain multi-factorial brain re-organization, and suggests that distinct, co-existing receptor-mediated processes underlie Parkinson's disease.

Discovery and In Vitro Characterization of SPL028: Deuterated N,N-Dimethyltryptamine

The psychedelic N,N- dimethyltryptamine (DMT) is in clinical development for the treatment of major depressive disorder. However, when administered via intravenous infusion, its effects are short-lived due to rapid clearance. Here we describe the synthesis of deuterated analogues of DMT with the aim of prolonging the half-life and decreasing the clearance rate while maintaining similar pharmacological effects. The molecule with the greatest degree of deuteration at the α-carbon (N,N-D2-dimethyltryptamine, D2-DMT) demonstrated the longest half-life and intrinsic clearance in hepatocyte mitochondrial fractions when compared with DMT. The in vitro receptor binding profile of D2-DMT was comparable to that of DMT, with the highest affinity at the 5-HT1A, 5-HT2A, and 5-HT2C receptors. D2-DMT was therefore the preferred candidate to consider for further evaluation.

The default network dominates neural responses to evolving movie stories

Neuroscientific studies exploring real-world dynamic perception often overlook the influence of continuous changes in narrative content. In our research, we utilize machine learning tools for natural language processing to examine the relationship between movie narratives and neural responses. By analyzing over 50,000 brain images of participants watching Forrest Gump from the studyforrest dataset, we find distinct brain states that capture unique semantic aspects of the unfolding story. The default network, associated with semantic information integration, is the most engaged during movie watching. Furthermore, we identify two mechanisms that underlie how the default network liaises with the amygdala and hippocampus. Our findings demonstrate effective approaches to understanding neural processes in everyday situations and their relation to conscious awareness.

In vivo mapping of pharmacologically induced functional reorganization onto the human brain's neurotransmitter landscape

To understand how pharmacological interventions can exert their powerful effects on brain function, we need to understand how they engage the brain's rich neurotransmitter landscape. Here, we bridge microscale molecular chemoarchitecture and pharmacologically induced macroscale functional reorganization, by relating the regional distribution of 19 neurotransmitter receptors and transporters obtained from positron emission tomography, and the regional changes in functional magnetic resonance imaging connectivity induced by 10 different mind-altering drugs: propofol, sevoflurane, ketamine, lysergic acid diethylamide (LSD), psilocybin, N,N-Dimethyltryptamine (DMT), ayahuasca, 3,4-methylenedioxymethamphetamine (MDMA), modafinil, and methylphenidate. Our results reveal a many-to-many mapping between psychoactive drugs' effects on brain function and multiple neurotransmitter systems. The effects of both anesthetics and psychedelics on brain function are organized along hierarchical gradients of brain structure and function. Last, we show that regional co-susceptibility to pharmacological interventions recapitulates co-susceptibility to disorder-induced structural alterations. Collectively, these results highlight rich statistical patterns relating molecular chemoarchitecture and drug-induced reorganization of the brain's functional architecture.

Dynamic regulation of the extracellular matrix in reward memory processes: a question of time

Substance use disorders are a global health problem with increasing prevalence resulting in significant socioeconomic burden and increased mortality. Converging lines of evidence point to a critical role of brain extracellular matrix (ECM) molecules in the pathophysiology of substance use disorders. An increasing number of preclinical studies highlight the ECM as a promising target for development of novel cessation pharmacotherapies. The brain ECM is dynamically regulated during learning and memory processes, thus the time course of ECM alterations in substance use disorders is a critical factor that may impact interpretation of the current studies and development of pharmacological therapies. This review highlights the evidence for the involvement of ECM molecules in reward learning, including drug reward and natural reward such as food, as well as evidence regarding the pathophysiological state of the brain's ECM in substance use disorders and metabolic disorders. We focus on the information regarding time-course and substance specific changes in ECM molecules and how this information can be leveraged for the development of therapeutic strategies.

Pharmacokinetics of N,N-dimethyltryptamine in Humans

BACKGROUND AND OBJECTIVE

N,N-dimethyltryptamine (DMT) is a psychedelic compound under development for the treatment of major depressive disorder (MDD). This study evaluated the preclinical and clinical pharmacokinetics and metabolism of DMT in healthy subjects.

METHODS

The physiochemical properties of DMT were determined using a series of in vitro experiments and its metabolic profile was assessed using monoamine oxidase (MAO) and cytochrome P450 (CYP) inhibitors in hepatocyte and mitochondrial fractions. Clinical pharmacokinetics results are from the phase I component of a phase I/IIa randomised, double-blind, placebo-controlled, parallel-group, dose-escalation trial (NCT04673383). Healthy adults received single escalating doses of DMT fumarate (SPL026) via a two-phase intravenous (IV) infusion. Dosing regimens were calculated based on pharmacokinetic modelling and predictions with progression to each subsequent dose level contingent upon safety and tolerability.

RESULTS

In vitro clearance of DMT was reduced through the inhibition of MAO-A, CYP2D6 and to a lesser extent CYP2C19. Determination of lipophilicity and plasma protein binding was low, indicating that a high proportion of DMT is available for distribution and metabolism, consistent with the very rapid clinical pharmacokinetics. Twenty-four healthy subjects received escalating doses of DMT administered as a 10-min infusion over the dose range of 9-21.5 mg (DMT freebase). DMT was rapidly cleared for all doses: mean elimination half-life was 9-12 min. All doses were safe and well tolerated and there was no relationship between peak DMT plasma concentrations and body mass index (BMI) or weight.

CONCLUSION

This is the first study to determine, in detail, the full pharmacokinetics profile of DMT following a slow IV infusion in humans, confirming rapid attainment of peak plasma concentrations followed by rapid clearance. These findings provide evidence which supports the development of novel DMT infusion regimens for the treatment of MDD.

CLINICAL TRIAL REGISTRATION

Registered on ClinicalTrials.gov (NCT04673383).

Among psychedelic-experienced users, only past use of psilocybin reliably predicts nature relatedness

BACKGROUND

Past research reports a positive relationship between experience with classic serotonergic psychedelics and nature relatedness (NR). However, these studies typically do not distinguish between different psychedelic compounds, which have a unique psychopharmacology and may be used in specific contexts and with different intentions. Likewise, it is not clear whether these findings can be attributed to substance use per se or unrelated variables that differentiate psychedelic users from nonusers.

AIMS

The present study was designed to determine the relative degree to which lifetime experience with different psychedelic substances is predictive of self-reported NR among psychedelic-experienced users.

METHODS

We conducted a combined reanalysis of five independent datasets (N = 3817). Using standard and regularized regression analyses, we tested the relationship between degree of experience with various psychedelic substances (binary and continuous) and NR, both within a subsample of psychedelic-experienced participants as well as the complete sample including psychedelic-naïve participants.

RESULTS/OUTCOMES

Among people experienced with psychedelics, only past use of psilocybin (versus LSD, mescaline, Salvia divinorum, ketamine, and ibogaine) was a reliable predictor of NR and its subdimensions. Weaker, less reliable results were obtained for the pharmacologically similar N,N-dimethyltryptamine (DMT). Results replicate when including psychedelic-naïve participants. In addition, among people exclusively experience with psilocybin, use frequency positively predicted NR.

CONCLUSIONS/INTERPRETATION

Results suggest that experience with psilocybin is the only reliable (and strongest) predictor of NR. Future research should focus on psilocybin when investigating effects of psychedelic on NR and determine whether pharmacological attributes or differences in user expectations/use settings are responsible for this observation.

The topological space of subjective experience

Subjective experiences often feel rich, yet are most often quantified with simple metrics, such as a few levels on a predefined scale. What are the dimensions and topological organization of subjective experience? How do they relate to behavioral output? And how do they map onto the classical cognitive domains?

Animal Behavior in Psychedelic Research

Psychedelic-assisted psychotherapy holds great promise in the treatment of mental health disorders. Research into 5-hydroxytryptamine 2A receptor (5-HT_2AR) agonist psychedelic compounds has increased dramatically over the past two decades. In humans, these compounds produce drastic effects on consciousness, and their therapeutic potential relates to changes in the processing of emotional, social, and self-referential information. The use of animal behavior to study psychedelics is under debate, and this review provides a critical perspective on the translational value of animal behavior studies in psychedelic research. Acute activation of 5-HT_2ARs produces head twitches and unique discriminative cues, disrupts sensorimotor gating, and stimulates motor activity while inhibiting exploration in rodents. The acute treatment with psychedelics shows discrepant results in conventional rodent tests of depression-like behaviors but generally induces anxiolytic-like effects and inhibits repetitive behavior in rodents. Psychedelics impair waiting impulsivity but show discrepant effects in other tests of cognitive function. Tests of social interaction also show conflicting results. Effects on measures of time perception depend on the experimental schedule. Lasting or delayed effects of psychedelics in rodent tests related to different behavioral domains appear to be rather sensitive to changes in experimental protocols. Studying the effects of psychedelics on animal behaviors of relevance to effects on psychiatric symptoms in humans, assessing lasting effects, publishing negative findings, and relating behaviors in rodents and humans to other more translatable readouts, such as neuroplastic changes, will improve the translational value of animal behavioral studies in psychedelic research. SIGNIFICANCE STATEMENT: Psychedelics like LSD and psilocybin have received immense interest as potential new treatments of psychiatric disorders. Psychedelics change high-order consciousness in humans, and there is debate about the use of animal behavior studies to investigate these compounds. This review provides an overview of the behavioral effects of 5-HT_2AR agonist psychedelics in laboratory animals and discusses the translatability of the effects in animals to effects in humans. Possible ways to improve the utility of animal behavior in psychedelic research are discussed.

From Brain-Body Function to Conscious Interactions

In this review, we discuss empirical results inspiring the introduction of a formal mathematical multilayer model for the biological neuroscience of conscious experience. First, we motivate the discussion through evidence regarding the dynamic brain. Second, we review different brain-body couplings associated with conscious experience and its potential role in driving brain dynamics. Third, we introduce the machinery of multilayer networks to account for several types of interactions in brain-body systems. Then, a multilayer structure consists of two main generalizations: a formal semantic to study biological systems, and an integrative account for several signatures and models of consciousness. Finally, under this framework, we define composition of layers to account for entangled features of brain-body systems related to conscious experience. As such, a multilayer mathematical framework is highly integrative and thus may be more complete than other models. In this short review, we discuss a variety of empirical results inspiring the introduction of a formal mathematical multilayer model for the biological neuroscience of conscious experience.

Phenomenology and content of the inhaled N, N-dimethyltryptamine (N, N-DMT) experience

Understanding the phenomenology and content of the inhaled N, N, dimethyltryptamine (N, N-DMT) experience is critical to facilitate and support ongoing research and therapeutic models targeting mental health conditions and central nervous system pathology. A qualitative analysis was conducted of all N, N-DMT experiences posted to the r/DMT Reddit community over a 10-year period from 2009 to 2018. A total of 3778 experiences from 3305 posts were included in this study. A median dose of N, N-DMT of 40.0 mg [interquartile range (IQR), 27.5 to 50.0] and a median experience duration of 10 min (IQR, 5.0 to 15.0) were identified. The most common somatic effects were somaesthesias (n = 1415, 37.5%) and an auditory ringing (n = 583, 15.4%). Visualizations predominantly consisted of fractals, shapes, patterns (n = 1231, 32.6%) and vivid colours (n = 953, 25.2%). Entity encounters were reported in 45.5% (n = 1719) of the experiences and involved predominantly a feminine phenotype (n = 416, 24.2%); deities (n = 293, 17.0%); aliens (n = 281, 16.3%); creature-based entities (n = 158, 9.2%, including reptilian and insectoid beings); mythological beings (n = 144, 8.4%, including machine elves); and jesters (n = 112, 6.5%). Entity interactions were predominantly positive (n = 600, 34.9% of encounters) involving benevolent, comforting, protecting, or outwardly caring interactions. A companion-type, pedagogical, or guide-type interaction was identified 32.4% of encounters (n = 557). Common typology, architecture, and structural features of the "DMT world" included descriptions of alternate or higher dimensions (n = 952, 25.2%); rooms [n = 582, 15.4%, including the "waiting room" (n = 105, 2.8%)], and a tunnel (n = 390, 10.3%). Features of mystical and ego-dissolution experiences were common. Additional rewarding aspects were identified, including a sense of familiarity and the acceptance/removal of the fear of death. Challenging and difficult responses were less frequent but also documented. Statements of profundity were identified in 232 experiences (6.1%), including pronouncing the experience or an aspect of the experience as the most "beautiful" or feeling the most "beautiful" of their life (n = 47, 1.2%). This study identified common phenomenological themes and content of naturalistic inhaled N, N-DMT experiences. Major thematic domains included (1) physical and somatic experiences; (2) visualizations and imagery; (3) entity encounters including entity phenotype, descriptors, attributes, disposition, and characteristics of the interaction; (4) typology, architectural features, structural characteristics, and scenery of the "DMT world"; (5) alerations in consciousness (including mystical experiences, out-of-body experiences, and ego-dissolution); (6) emotional responses (including positive, rewarding, difficult, and challenging); and (7) statements of profundity.

Language as a Window Into the Altered State of Consciousness Elicited by Psychedelic Drugs

Psychedelics are drugs capable of eliciting profound alterations in the subjective experience of the users, sometimes with long-lasting consequences. Because of this, psychedelic research tends to focus on human subjects, given their capacity to construct detailed narratives about the contents of their consciousness experiences. In spite of its relevance, the interaction between serotonergic psychedelics and language production is comparatively understudied in the recent literature. This review is focused on two aspects of this interaction: how the acute effects of psychedelic drugs impact on speech organization regardless of its semantic content, and how to characterize the subjective effects of psychedelic drugs by analyzing the semantic content of written retrospective reports. We show that the computational characterization of language production is capable of partially predicting the therapeutic outcome of individual experiences, relate the effects elicited by psychedelics with those associated with other altered states of consciousness, draw comparisons between the psychedelic state and the symptomatology of certain psychiatric disorders, and investigate the neurochemical profile and mechanism of action of different psychedelic drugs. We conclude that researchers studying psychedelics can considerably expand the range of their potential scientific conclusions by analyzing brief interviews obtained before, during and after the acute effects. Finally, we list a series of questions and open problems that should be addressed to further consolidate this approach.

The doors of precision: Reenergizing psychiatric drug development with psychedelics and open access computational tools

Psychedelics paired with new applications of computational tools might help bypass the imprecision of psychiatric diagnosis and connect measures of behavior to specific physiologic targets.