Daily Archives: July 21, 2024

Regulatory approvals and registrations

Written informed consent was obtained from all participants in accordance with the Declaration of Helsinki and procedures established by the Washington University in Saint Louis Institutional Review Board. All participants were compensated for their time. All aspects of this study were approved by the Washington University School of Medicine (WUSOM) Internal Review Board, the Washington University Human Research Protection Office (WU HRPO), the Federal Drug Administration (IND no. 202002165) and the Missouri Drug Enforcement Agency (DEA) under a federal DEA schedule 1 research licence and registered with ClinicalTrials.gov identifier NCT04501653. Psilocybin was supplied by Usona Institute through Almac Clinical Services.

Healthy young adults (n=7, 1845years) were enrolled between April 2021 and March 2023 in a randomized cross-over precision functional brain mapping study at Washington University in Saint Louis (seeSupplementary Methods for inclusion and exclusion criteria). The purpose of the study was to evaluate differences in individual-level connectomics before, during and afterpsilocybin exposure. Participants underwent imaging during drug sessions (with MRI starting 1h after drug ingestion) with 25 mgpsilocybin or 40 mgMTP, as well as non-drug imaging sessions. Drug condition categories were (1) baseline, (2) drug 1 (MTP or psilocybin), (3) between, (4) drug 2 and (5) after. Randomization allocation was conducted using REDCap and generated by team members who prepared study materials including drug or placebo but otherwise had no contact with participants. A minimum of three non-drug imaging sessions were completed during each non-drug window: baseline, between and after drug sessions. The number of non-drug MRI sessions was dependent on availability of the participant, scanner and scanner support staff. Dosing day imaging sessions were conducted 60180min following drug administration during peak blood concentration98. One participant (P2) was not able tolerate fMRI while on psilocybin,and had trouble staying awake on numerous fMRI visits after psilocybin and was thus excluded from analysis (except for data quality metrics in Extended Data Fig. 1).

MTP was selected as the active control condition to simulate the cardiovascular effects and physiological arousal (that is, controlling for dopaminergic effects) associated with psilocybin99. Usona Institute, a US non-profit medical research organization, provided good manufacturing practices for psilocybin.

Drug sessions were facilitated by two clinical research staff who completed an approved in-person or online facilitator training programme provided by Usona Institute, as part of the phase 2 study (ClinicalTrials.gov identifier NCT03866174). The role of the study facilitators was to build a therapeutic alliance with the participant throughout the study, prepare them for their drug dosing days and to observe and maintain participant safety during dosing day visits64. The pair consisted of an experienced clinician (lead clinical facilitator) and a trainee (cofacilitator).

The predefined primary outcome measure was precision functional mapping (numerous visits, very long scans to produce individual connectomes) examining the effects of psilocybin on cortical and cortico- subcortical brain networks that could explain its rapid and sustained behavioural effects. Predefined secondary outcome measures included (1) assessment of hemodynamic response to evaluate how 5-HT2A receptor agonism by psychedelics may alter neurovascular coupling, (2) assessment of acute psychological effects of psilocybin using the MEQ30 score (Supplementary Methods) and (3) assessment of personality change using the International Personality Item Pool-Five-Factor Model100. Changes in pulse rate and respiratory rate during psilocybin and placebo were later added as secondary outcome measures and personality change was abandoned because it was clear that we would not be powered to detect personality change.

Participants were invited to return 612months after completing the initial cross-over study for a replication protocol. This included 12 baseline fMRIs, a psilocybin session (identical to the initial session, except for lack of blinding) and 12 after sessions within 4days of the dose.

Healthy adults aged 1845years were recruited by campus-wide advertisement and colleague referral. Participants (n=7) were enrolled from March 2021 to May 2023. Participants were required to have had at least one previous lifetime psychedelic exposure (for example, psilocybin, mescaline, ayahuasca, LSD), but no psychedelics exposure within the past 6months. Individuals with psychiatric illness (depression, psychosisor addiction) based on the DSM-5 were excluded. Demographics and data summary details are provided in Supplementary Table 1. One of the authors (N.U.F.D.) was a study participant.

Participants were scanned roughly every other day over the course of the experiment (Extended Data Fig. 1). Imaging was performed at a consistent time of day to minimize diurnal effects in FC101. Neuroimaging was performed on a Siemens Prisma scanner (Siemens) in the neuroimaging laboratories at the Washington University Medical Center.

Structural scans (T1w and T2w) were acquired for each participant at 0.9mm isotropic resolution, with real-time motion correction. Structural scans from different sessions were averaged together for the purposes of Freesurfer segmentation and nonlinear atlas registrations.

To capture high-resolution images of blood oxygenation level-dependent (BOLD) signal, we used an echo-planar imaging sequence102 with 2mm isotropic voxels, multiband 6, multi-echo 5 (times to echo: 14.20, 38.93, 63.66, 88.39, 113.12ms)103, repetition or relaxation time: 1,761ms, flip angle of 68 and in-plane acceleration104 (IPAT or grappa) of 2. This sequence acquired 72 axial slices (144mm coverage). Each resting scan included 510 frames (lasting 15min, 49s) as well as three frames at the end used to provide estimate electronic noise.

Every session included two 15-min resting-state fMRI (rs-fMRI) scans, during which participants were instructed to hold still and look at a white fixation crosshair presented on a black background. Head motion was tracked in real time using Framewise Integrated Real-time MRI Monitoring software (FIRMM)105. An eye-tracking camera (EyeLink) was used to monitor participants for drowsiness.

Participants also completed a previously validated event-related fMRI task. This was a suprathreshold auditoryvisual matching task in which participants were presented with a naturalistic visual image (duration 500ms) and coincident spoken English phrase, and were asked to respond with a button press to indicate whether the image and phrase were congruent (for example, an image of a beach and the spoken word beach) or incongruent. Both accuracy and response time of button presses were recorded. Each trial was followed by a jittered inter-stimulus interval optimized for event-related designs. In a subset of imaging sessions, two task fMRI scans were completed following the two resting scans. Task fMRI scans used the same sequence used in resting fMRI, included 48 trials (24 congruent, 24 incongruent) and lasted a total of 410s. In analyses, high motion frames were censored106 andthe two task scans were concatenated to better match the length of the rs-fMRI scans. Note the stimulus order in the two trials did not vary across session. The order of rest and task scans was not counterbalanced across sessions to avoid concern that task scans may influence subsequent rest scans.

Resting fMRI data were preprocessed using an in-house processing pipeline. In brief, this included removal of thermal noise using NORDIC denoising107,108,109, correction for slice timing and field distortions, alignment, optimal combination of many echoes by weighted summation110, normalization, nonlinear registration, bandpass filtering and scrubbing at a movement threshold of 0.3mm to remove reduce the influence of confounds111. Tissue-based regressors were computed in volume (white matter, ventricles, extra-axial cerebrospinal fluid)112 and applied following projection to surface. Task-based regressors were only applied when indicated. Details on rs-fMRI preprocessing are provided inSupplementary Methods. Visualizations of motion, physiological traces and signal across the brain (grayplots) before and after processing113 are provided in Supplementary Video1.

Surface generation and processing of functional data followed similarprocedures to Glasser et al.114. To compare FC and resting-state networks across participants, we used a group-based surface parcellation and community assignments generated previously62.

For subcortical regions, we used a set of regions of interest115 generated to achieve full coverage and optimal region homogeneity. A subcortical limbic network was defined on the basis of neuroanatomy: amygdala, anteromedial thalamus, nucleus accumbens, anterior hippocampus and posterior hippocampus116,117. These regions were expanded to cover anatomical structures (for example, anterior hippocampus)31.

To generate region-wise connectivity matrices, time courses of all surface vertices or subcortical voxels within a region were averaged. FC was then computed between each region timeseries using a bivariate correlation andthen Fisher z-transformed for group comparison.

We identified canonical large-scale networks using the individual-specific network matching approach described previously43,44,62. In brief, cortical surface and subcortical volume assignments were derived using the graph-theory-based Infomap algorithm118. In this approach, we calculated the correlation matrix from all cortical vertices and subcortical voxels, concatenated across all a participants scans. Correlations between vertices within 30mm of each other were set to zero. The Infomap algorithm was applied to each participants correlation matrix thresholded at a range of edge densities spanning from 0.01 to 2%. At each threshold, the algorithm returned community identities for each vertex and voxel. Communities were labelled by matching them at each threshold to a set of independent group average networks described previously62. In each individual and in the average, a consensus network assignment was derived by collapsing assignments across thresholds, giving each node the assignment it had at the sparsest possible threshold at which it was successfully assigned to one of the known group networks. See Extended Data Fig. 4 and Supplementary Fig. 1 for individual and group mode assignments, respectively. The following networks were included: the association networks including the DMN, fronto-parietal, dorsal attention, parietal memory, ventral attention, action-mode, salience and context networks; and the primary networks including the visual, somato-motor, somato-motor face and auditory networks.

To compute local (areal) desynchronization, we also defined brain areas at the individual level using a previously described areal parcellation approach39. In brief, for each participant, vertex-wise FC was averaged across all sessions to generate a dense connectome. Then, abrupt transitions in FC values across neighbouring vertices were used to identify boundaries between distinct functional areas.

To take advantage of the multilevel precision functional mapping study design, a LME model was used. Every scan was labelled on the following dimensions: participant identity (ID), MRI visit, task (task or rest), drug condition (prepsilocybin, psilocybin, MTP, postpsilocybin) and head motion (average framewise displacement). The rs-fMRI metrics (described below) were set as the dependent variable, drug (drug condition), task, framewise displacement (motion) and drugtask were defined as fixed effects, and participant ID and MRI session were random effects.

Let yij be the rs-fMRI metric (for example, FC change score at a given vertex) for the jth observation (15min fMRI scan) within the ith participant. The LME model can be written as:

$$begin{array}{l}{y}_{ij}={beta }_{0}+{beta }_{{rm{d}}{rm{r}}{rm{u}}{rm{g}}}cdot {{rm{d}}{rm{r}}{rm{u}}{rm{g}}}_{ij}+{beta }_{{rm{F}}{rm{D}}}cdot {{rm{F}}{rm{D}}}_{ij}+{beta }_{{rm{t}}{rm{a}}{rm{s}}{rm{k}}}cdot {{rm{t}}{rm{a}}{rm{s}}{rm{k}}}_{ij}\ ,,+{beta }_{{rm{task}} mbox{-} {rm{by}} mbox{-} {rm{drug}}}cdot {{rm{t}}{rm{a}}{rm{s}}{rm{k}}}_{ij}cdot {{rm{d}}{rm{r}}{rm{u}}{rm{g}}}_{ij}+{u}_{0i}+{v}_{0j}+{{varepsilon }}_{ij}end{array}$$

(1)

0 is the intercept term.

drug, FD, task and task-by-drug are the coefficients for the fixed effects predictors.

drugij, frame displacementij (FDij)and taskij are the values of the fixed effects predictors for the jth observation within the ith group.

u0i represents the random intercept for the ith participant, accounting for individual-specific variability.

v0j represents the random intercept for the jth observation within the ith participant, capturing scan-specific variability.

ij is the error term representing unobserved random variation.

In MATLAB (Wilkinsonian notation), this model is expressed for every vertex Y(vertex)=fitlme(groupd, FC_Change(vertex)~drug+framewise displacement+ task+task-by-drug+(1|SubID)+(1 |session)).

To compensate for the implementations of this LME model on many rs-fMRI-related dependent variables, differences were highlighted when P<0.001. All P values reported are not corrected for multiple comparisons.

FC change (distance) was calculated at the vertex level to generate FC change maps and a LME model (equation (1)) was used in combination with wild bootstrapping119,120 and threshold-free cluster enhancement (TFCE)95,121 to estimate P values for t-statistic maps resulting from the model (Figs. 1ad and4). Wild bootstrapping is an approach to permutation testing that was designed for models that are not independent and identically distributed, and are heteroscedastic.

First, a FC change map was generated for every scan by computing, for each vertex, the average distance between its FC seedmap and the FC seedmap for each of that participants baseline scans. As each participant had several baseline visits, FC change was computed for baseline scans by computing distance from all other baseline scans (excluding scans within the same visit). This provided a measure of day-to-day variability. Second, the distance value was used as the dependent variable yij in the LME model to generate a t-statistic. Third, a wild bootstrapping procedure was implemented as follows. Several bootstrap samples (B=1,000) were generated using the Rademacher procedure120, in which the residuals were randomly inverted. Specifically, a Rademacher vector was generated by randomly assigning 1 or 1 values with equal probability to the residual ofeach observation. By element-wise multiplication of the original residuals with the Rademacher vector, bootstrap samples were created to capture the variability in the data.

For the observed t-statistic-map and each bootstrap sample, the TFCE algorithm was applied to enhance the sensitivity to clusters of significant voxels or regions while controlling for multiple comparisons. The value of the enhanced cluster statistic derived from the bootstrap samples was used to create a null distribution under the null hypothesis. By comparing the original observed cluster statistic with the null distribution, P values were derived to quantify the statistical significance of the observed effect. The P values were obtained on the basis of the proportion of bootstrap samples that produced a maximum cluster statistic exceeding the observed cluster statistic.

The combined approach of wild bootstrapping with the Rademacher procedure and TFCE provided themethod to estimate P values for our multilevel (drug condition, participant, session, task) design. This methodology accounted for the complex correlation structure, effectively controlled for multiple comparisons and accommodated potential autocorrelation in the residuals through the Rademacher procedure. By incorporating these techniques, association with psilocybin and other conditions was reliably identified amid noise and spatial dependencies.

For analyses in Figs. 1e,g, 2 and 4a (bottom), Extended Data Fig. 3 and Supplementary Figs. 3, 4 and 6, distance calculations were computed on the FC matrix using z-transformed bivariate correlation of time courses from parcellated brain areas62. The effects of day-to-day, drug condition, task and framewise displacement and drugtask were directly examined by calculating the distance between functional network matrices generated from each scan. Root-mean-squared Euclidean distance was computed between the linearized upper triangles of the parcellated FC matrix between each pair of 15min fMRI scans, creating a second-order distance matrix (Extended Data Fig. 3). Subsequently, the average distance (reported as whole-brain FC change) was examined for FC matrices that were from the same individual within a single session, from the same individual across days (day-to-day), from the same participant between drug and baseline (for example, psilocybin), from the same individual but different tasks (task:rest), from the same individual between highest motion scans and baseline (hi:lo motion), from different individuals (between person). In the high head motion comparison (hi:lo motion in Supplementary Fig. 3), the two non-drug scans with the highest average framewise displacement were labelled and compared against all other baseline scans.

A LME model (equation (1)) and post hoc t-tests were used to assess statistical differences between drug conditions. A related approach using z-transformed bivariate correlation (similarity rather than distance) was also taken and results were unchanged (Supplementary Fig. 3c).

To test whether variability in participant-specific response to psilocybin was larger than would be expected by chance, we used a likelihood ratio test for variance of random slopes for a participant-specific response to psilocybin48. The difference in log likelihood ratios was compared to a null distribution of 1million draws from a mixture of chi-squared distributions with degrees of freedom 1 and 2. We note that the likelihood ratio test of variance components is a non-standard problem47 as the covariance matrix of the random effects is positive definite and the variances of random effects are non-negative. Finally,the test statistic for the likelihood ratio in this LME model was compared against a 50/50 mixture of two independent chi-squared distributions, each with one and two degrees of freedom, respectively.

Subjective experience was assessed for drug sessions using the MEQ3046(Supplementary Methods). The MEQ30 is designed to capture the core domains of the subjective effects of psychedelics (as compared to the altered states of consciousness rating scales that more broadly assess effects of psychoactive drugs122) and is related to the therapeutic benefits of psychedelics. We applied a LME model across all drug sessions, similar to the one described above, but with MEQ30 total score as the dependent variable. Whole-brain FC change and framewise displacement were modelled as fixed effects, and participant was modelled as a random effect. The same model was solved using FC change from every vertex to generate a vertex-wise map of the FC change versus MEQ30.

The conditions above were compared by calculating normalized FC change scores using the following procedure: we (1) determined FC change for each condition compared to baseline as described above, (2) subtracted within-session distance for all conditions (such that within-session FC change was 0), (3) divided all conditions by day-to-day distance (such that day-to-day FC change was equal to 1). Thus, normalized whole-brain FC change values (for example, psilocybin versus base was 3.52) could be thought of as proportional to day-to-day variability.

We used a classical MDS approach to cluster parcellated connectomes across fMRI scans, as previouslydescribed38. This data-driven approach was used to identify how different parameters (for example, task, drug, individual) affect similarity and/or distance between networks. MDS places data in multidimensional space on the basis of the dissimilarity (Euclidean distance) among data points, which in this case means a data point represents the linearized upper triangle of a FC matrix. Every matrix was entered into the classical MDS algorithm (implemented using MATLAB 2019, cmdscale.m). Many dimensions of the data were explored. The eigenvectors were multiplied by the original FC matrices to generate a matrix of eigenweights that corresponded to each dimension. These eigenweights were also applied to other rs-fMRI psychedelics datasets to generate dimensions scores (section Other datasets).

To assess network specificity of FC change values, we calculated average FC change of matched null networks consisting of randomly rotated networks with preserved size, shape and relative position to each other62,97. To create matched random networks, we rotated each hemisphere of the original networks a random amount around the x, y and z axes on the spherical expansion of the cortical surface62. This procedure randomly relocated each network while maintaining networks sizes, shapes and relative positions to each other. Random rotation followed by computation of network-average FC change score was repeated 1,000 times to generate null distributions of FC change scores. Vertices rotated into the medial wall were not included in the calculation. Actual psilocybin FC change was then compared to null rotation permutations to generate a P value for the 12 networks that were consistently present across every participants Infomap parcellation. For bar graph visualization (Fig. 1 and Supplementary Fig. 1b), networks with greater change (P<0.05 based on null rotation permutations) are shownin their respective colour and other networks are shown in grey.

We used an approach previously validated to assess spatial complexity (termed entropy) or neural signals61. Temporal principal component analysis was conducted on the full BOLD dense timeseries, which yielded m principal components (m roughly 80K surface vertices and subcortical voxels) and associated eigenvalues. The normalized eigenvalue of the ith principal component was calculated as

$${lambda }_{i}^{{prime} }=frac{{lambda }_{i}}{{sum }_{i=1}^{m}{lambda }_{i}^{{prime} }}$$

(2)

where m is the number of principal components, and i and i represent the eigenvalue and the normalized eigenvalue of the ith principal component, respectively. Last, the NGSC, defined as the normalized entropy of normalized eigenvalues, was computed using the equation:

$${rm{NGSC}}=-frac{{sum }_{i=1}^{m}{lambda }_{i}^{{prime} }log {lambda }_{i}^{i},}{log m}$$

(3)

The NGSC computed above attains values from the interval 0 to 1. The lowest value NGSC=0 would mean the brain-wide BOLD signal consisted of exactly one principal component or spatial mode, and there is maximum global FC between all vertices. The highest value NGSC=1 would mean the total data variance is uniformly distributed across all m principal components, and a maximum spatial complexity or a lowest FC is found.

NGSC was additionally calculated at the parcel level. To respect areal boundaries, this was done by first generating a set of individual-specific parcels in every participant (on all available resting fMRI sessions concatenated) using procedures described oreviously39,62.

NGSC maps were compared to PET-based 5-HT2A receptor binding maps published in ref. 33. Similarity was assessed by computing the bivariate correlation between NGSC values and 5-HT2A binding across 324 cortical parcels from the GordonLaumann parcellation.

To assess the persistent effects of psilocybin, we compared FC changes 121days postpsilocybin to predrug baseline. The FC change analysis (described above) indicated that connectivity at the whole-brain level did not change following psilocybin (Supplementary Fig. 1). A screen was conducted with P<0.05 threshold to identify brain networks or areas showing persistent effects. This analysis identified the anterior hippocampus as a candidate region of interest for persistent FC change (section Baseline/after psilocybin FC change analysis inSupplementary Methods).

We assessed change in anterior hippocampus FC change pre- versus postpsilocybin using the LME model described previously. In this model, all sessions before psilocybin (irrespective or cross-over order) were labelled as prepsilocybin and all sessions within 21days after psilocybin were labelled as postpsilocybin.

As a control, we tested anterior hippocampus FC change pre- versus post-MTP using both the LME model, and an equivalence test. To control for potential persistent psilocybin effects, only the block of scans immediately before and after MTP were used (for example, if a participant took MTP as drug 1, then all baseline scans were labelled as pre-MTP and all scans between drugs 1 and 2 were labelled post-MTP).

Equivalence testing (to conclude no change in anterior hippocampus after MTP) was accomplished by setting =0.5 standard deviation of FC change across pre-MTP sessions. We computed the 90% CI of change in FC change between pre- and post-MTP sessions. If the bounds of the 90% CI were within , then equivalence was determined123.

Raw fMRI and structural datapublished previously55,56 were run through our in-house registration and processing pipeline described above. These datasets were used for replication, external validation and generalization to another classic psychedelic (that is, LSD) for the measures described above (for example, NGSC and the MDS-derived psilocybin FC dimension, dimension 1).

Using the data from ref. 55: n=15 healthy adults (five women, mean age 34.1years, s.d. 8.2) completed two scanning sessions (psilocybin and saline) that included an eyes-closed resting-state BOLD scan for 6min before and following i.v. infusion of drug. fMRI data were acquired using a gradient-echo-planar imaging sequence, TR and TE of 3,000 and 35ms, field-of-view 192mm, 6464 acquisition matrix, parallel acceleration factor of 2 and 90 flip angle.

Using the data from ref. 56: healthy adults completed two scanning sessions (LSD and saline), which included an eyes-closed resting-state BOLD scan acquired for 22min following i.v. drug infusion lasting 12min. n=20 participants completed the protocol, but data were used for n=15 (four women; mean age 30.5, standard deviation 8.0) deemed suitable for BOLD analyses. fMRI data were acquired using a gradient-echo-planar imaging sequence, TR and TE of 2,000 and 35ms, field-of-view 220mm, 6464 acquisition matrix, parallel acceleration factor of 2, 90 flip angle and 3.4mm isotropic voxels.

The ABCD database resting-state functional MRI59 (annual release v.2.0, https://doi.org/10.15154/1503209) was used to replicate the effects of stimulant use on FC. Preprocessing included framewise censoring with a criterion of frame displacement less than or equal to 0.2mm in addition the standard predefined preprocessing procedures124. Participants with fewer than 600 frames (equivalent to 8min of data after censoring) were excluded from the analysis. Parcel-wise group-averaged FC matrices were constructed for each participant as described above for 385 regions on inter-test in the brain.

Use of a stimulant (for example, MTP, amphetamine salts, lisdexamfetamine) in the last 24h was assessed by parental report. Participants with missing data were excluded. Regression analysis was used to assess the relationship between FC (edges) and stimulant use in the last 24h. Framewise displacement (averaged over frames remaining after censoring) was used as a covariate to account for motion-related effects. The t-values that reflect the relationship between stimulant use and FC were visualized on a colour scale from 5 to +5 to provide a qualitative information about effect of stimulant use on FC.

Further information on research design is available in theNature Portfolio Reporting Summary linked to this article.

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Psilocybin desynchronizes the human brain - Nature.com

Users of hip Amazonian psychedelic ayahuasca favored by celebrities are having a bad trip at Alcoholics Anonymous meetings.

At least five recovering alcoholics who also indulge in ayahuasca and other psychedelics told The Post they are getting shunned by the group.

Jennifer Bruce described being berated when she continued to participate in mainstream 12-step meetings after taking ayahuasca to address past trauma.

When she picked up a chip denoting her length of sobriety at a meeting, attendees shouted she needed to turn my chip back in and start over because I had relapsed, Bruce said.

So it was very difficult to be there, she said.

At another meeting she shared her story, including her experience with ibogaine, a naturally occurring psychoactive compound.

I got attacked so bad that I was sobbing in tears at the end, Bruce said.

AA members who use psychedelics or even cannabis are often seen as breaching the organizations premise of total abstinence, though AA as an organization has no opinions on controversial issues and its co-founder, Bill Wilson, experimented with LSD.

Those who take psychedelics say they maintain their sobriety because the plant-based psychedelic is non-addictive and is being used medicinally or for spiritual enlightenment not to numb out.

Ayahuasca, the psychedelic brew, is popular with celebrities including pop star Miley Cyrus, actress Megan Fox and her boyfriend, pop-punk musician Machine Gun Kelly.

This is not about using a mind-altering substance for anything, said Michele Medal, who is in recovery for 20 years and has several psychedelic businesses. This is about healing at a cellular level. And once you heal at a cellular level, really heal, then that addiction is gone not that it cant come back.

Psychedelics, which advocates refer to as plant-based drugs, remain under heavy regulation federally and in most states. Oregon and Colorado have legalized some uses and legislation is pending in nine other states, including New Jersey, but legalization proposals in New York have gone nowhere so far.

Limited research suggests that use of psychedelic drugs does not typically lead to addiction, according to the National Institute on Drug Abuse. Ongoing studies supported by the federal agency are exploring whether they can be used to treat substance use disorders.

Erin V., who said a weeklong shaman-led ayahuasca ceremonial retreat in Peru can run anywhere between $600 and $3,000, was too afraid in 12-step meetings to reveal she indulged medicinally, and said she ditched AA because she feared being banished.

Members are being punished and expelled from their recovery groups and fellowships due to ignorance, judgment and misinformation in direct violation of our traditions, Vanessa Crites, a person in long-term recovery who uses psychedelic medicines and remains in a mainstream 12-step program,postedon LinkedIn.

Alcoholics Anonymous insisted it doesnt kick anyone out, a spokesperson said in an email, and it does not have a position or opinion on this matter.

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Recovered alcoholics tripping on ayahuasca say theyre being ostracized at AA meetings - New York Post

Early next year, the state of Colorado will start issuing licenses for psychedelic therapy centers, places where people can pay to take a supervised dose of psychedelic mushrooms and other forms of psilocybin.

Close to 100 people have told the state theyre interested in opening psilocybin businesses, including mushroom cultivation facilities, testing labs and therapy centers. Those therapy centers will be the only formal, legal businesses that are able to sell psilocybin, and the drug will have to be taken under supervision.

It will be the fulfillment of a change that voters approved back in 2021.

But what will those healing centers look like? What forms will the psilocybin come in? Who will produce the drug, and who can work in the industry?

Those are questions the state is trying to answer now. On Thursday, regulators published the latest draft rules that will govern the psilocybin industry here.

Its a key step. With the new publication, facilitators and businesses really have what they need to make informed decisions, said Shawn Hauser, a partner at Vicente LLP, a law firm that has been closely involved in Colorados cannabis and psilocybin industries.

Therapy centers could take a variety of forms, from a typical therapists office to a retreat or even an outdoor setting. Although each facility would need to be based in a building, regulators said they know customers might want to go outside.

They want to be able to move around and be in nature, said Allison Robinette, policy director for the Department of Revenues natural medicine and cannabis teams.

The industry could be allowed to offer psilocybin in multiple forms, including dried mushrooms; capsules; tea bags; tinctures; and chocolates and confections.

The idea of psilocybin chocolates is stirring some debate, with childrens safety advocates worried that it will normalize the idea of sweet and candy-based doses, similar to what happened with cannabis gummies and soda.

Proponents say chocolates may be more palatable for some than whole mushrooms or capsules, and may help quell nausea. The state is considering more safeguards for psilocybin chocolates, such as limits on how they are handled and transferred, Robinette said. Psilocybin will only be available to people 21 and older for use in controlled settings.

The state is set to offer a micro-cultivation license that may be more practical to obtain for smaller growers. That might be helpful for healing centers that want to grow their own mushrooms.

Applicants for psilocybin businesses will have to demonstrate a commitment to minimum environmental and social impact criteria, which they can achieve through strategies like waste reduction and inclusive hiring.

The new rules will be up for public comment at a hearing on July 25.

So far, the strongest interest from entrepreneurs has been in opening healing centers, rather than the other potential related businesses, Robinette said.

The 120-page draft also touches on numerous other requirements, including for testing, packaging, labeling and tracking products.

Weve looked across what other state agencies do. Weve leaned on our experience regulating in the cannabis space, she said.

At the meeting next Thursday, we will walk through every section, well provide context, well ask any outstanding question we as the division will still have, Robinette said.

State officials have been working on these rules since earlier this year. Regulators are trying to learn from Colorados experience with legal cannabis, in which an initial lack of regulation allowed an explosion of different THC products.

They have also been talking to cultivators of gourmet culinary mushrooms, who have shared their expertise on how larger-scale mushroom facilities might be run. And theyve also looked to Oregon, the only state with a similar program.

Despite all the interest, the industry may get a slow start, compared to legal marijuana, said Tasia Poinsatte, director of the Healing Advocacy Fund of Colorado, a major force behind the new law.

The scale of this is astronomically smaller than cannabis. The information weve gotten from Oregon is that the entire state program has only consumed in the vicinity of 20 to 30 kilograms of dried mushrooms so far, she said.

Hauser similarly said its unclear just how profitable and attractive the new industry will be to businesses, especially with competition from the current gray market.

The economics and viability of the program will really remain to be seen, she said, though she praised state officials for their work on the rules.

One big question still hasnt been answered: How much will businesses have to pay to get licensed? That will be addressed in the next and final rulemaking process.

The new draft rules cover how the various businesses will operate. But the state has already drafted or approved several other sets of rules for the individual facilitators who will oversee each psilocybin trip.

Facilitators will have to take coursework of at least 150 hours and undergo 40 hours of supervised training and 50 hours of consultation. Other draft rules offer guidance on more specific topics, like when and how a facilitator can offer a supportive touch to a participant, or how to respond to health problems during a session.

The Department of Regulatory Agencies is already accepting applications from organizations that would like to offer training programs for the psilocybin industry. These rules only cover the regulated part of the new world of psychedelics. Meanwhile, a flourishing gray market has emerged. The new laws allowances for personal use and sharing have led to people openly growing and offering psilocybin mushrooms, and touting their services as guides. While it is still illegal to charge for mushrooms, ads selling them abound online.

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Tinctures, chocolates and more: The future of Colorados psychedelic industry is coming into focus - Colorado Public Radio

A study finds that psilocybin can desynchronize networks in the brain, potentially enhancing its plasticity. Sara Moser/Washington University School of Medicine in St. Louis hide caption

In the name of science, Dr. Nico Dosenbach had scanned his own brain dozens of times. But this was the first time he'd taken a mind-bending substance before sliding into the MRI tunnel.

"I was, like, drifting deeper into weirdness," he recalls. "I didn't know where I was at all. Time stopped, and I was everyone."

Dosenbach, an associate professor of neurology at Washington University School of Medicine in St. Louis, had been given a high dose of psilocybin, the active substance in magic mushrooms, by his colleagues.

It was all part of a study of seven people designed to show how psilocybin produces its mind-altering effects.

The results, which appear in the journal Nature, suggest that psychedelic drugs work by disrupting certain brain networks, especially one that helps people form a sense of space, time and self.

"For the first time, with a really high degree of detail, we're understanding which networks are changing, how intensely they're changing and what persists after the experience," says Dr. Petros Petridis of New York University's Langone Center for Psychedelic Medicine, who wrote an editorial accompanying the study.

The research also provided a close look at how these drugs temporarily enhance the brain's ability to adapt and change, an ability known as plasticity.

The disruptions in brain networks appear to be "where the plasticity effects of psychedelics are coming from," says Dr. Joshua Siegel, a researcher at Washington University and the study's lead author.

If that's true, he says, it could explain why psychedelics appear to help people with addiction or depression.

Dosenbach and other participants were randomly assigned to receive either a stimulant or 25 milligrams of psilocybin, a dose high enough to cause hallucinations.

"It was definitely an awesome experience for a neuroscientist," he says.

"It's really fascinating how your brain can fall apart because how something breaks tells you how something works."

Dosenbach's trip took him places only a neuroscientist is likely to go.

"I was inside the brain, and I was riding brain waves, and I was Marc Raichle," he says, referring to Dr. Marcus Raichle, a colleague and co-author of the study, who also happens to be a towering figure in the world of neuroscience.

As part of the study, participants' brains were scanned an average of 18 times over a three-week period. Four repeated the experiment six to 12 months later.

"You're bringing in single individuals many times," Siegel says, "and that allows you to get a very detailed and precise map of their brain networks."

The scans showed that psilocybin caused swift and dramatic changes to certain brain networks. Usually the neurons in a given network become active at the same time often in tandem with other networks too.

"What's going on during psilocybin is that populations of neurons that are normally in synchrony are out of synchrony," Siegel says.

The brain "falls apart." And it appears to respond by entering a state of enhanced plasticity that can last for weeks.

"Desynchronization probably is a critical clue as to where the plasticity effects of psychedelics are coming from," Siegel says.

The loss of synchrony was greatest in a brainwide group of neurons called the default mode network, which is active when the brain is daydreaming or otherwise not focused on the outside world.

This network was discovered by scientists including Raichle, the man who became Dosenbach's alter ego in the scanner.

The default mode network is critical to self-referential memory, which helps the brain keep track of information like, Who am I? And what was I doing? Siegel says.

The study hints at how psychedelic drugs could be incorporated into the treatment of people with addiction, depression or post-traumatic stress.

"There seems to be this time of increased change that could be taken advantage of by therapists," Petridis says.

A patient with addiction, for example, might be able to reframe their relationship with substances in the days and weeks following a dose of psilocybin, he says.

But the approach has risks, says Dr. Ginger Nicol, a psychiatrist at Washington University whose husband was in the study and took psilocybin twice.

"He had an almost religious experience the first time," she says. "The second time, he saw demons."

Even so, psychedelics may offer a way to help psychiatric patients recognize their own capacity to change, Nicol says.

"It takes years to figure that out in therapy," she says. "This gives us a different way of thinking about learning and recovery."

Original post:

A scientist took a psychedelic drug and watched his own brain 'fall apart' - NPR

Are psychedelic drugs about to begin a long, strange trip toward use in a clinical setting? Or do the challenges of studying psychedelics, and the ethical risks of therapy, raise too many questions to introduce them into mainstream medicine?

Dominic Sisti, an associate professor of medical ethics and health policy in the Perelman School of Medicine, is part of a group of nearly 30 experts including bioethicists, psychiatrists, Indigenous scholars, researchers, and others to begin charting a path toward crafting guidelines for the ethical use of psychedelics. The groups work is published in JAMA Network Open, setting the stage for the next phase of psychedelics in psychiatry.

As debate continues ifand howpsychedelics should be used, a Food and Drug Administration advisory committee recently voted down a proposal brought by a drugmaker to use MDMA to treat post-traumatic stress disorder (PTSD), in combination with talk therapy. The committee recognized the promise of psychedelics but raised serious concerns about the science and the ethics of psychedelic treatments.

However, the FDA can still eventually approve its use. If so, there is a growing movement of cross disciplinary experts crafting guardrails for how psychedelic drugs should be used.

Though popular culture often depicts psychedelic drug use as a product of 1960s counterculture, mind-altering drugs have been used by humans in some form for millennia. In 2008, archeologists at a 1,000-year-old site in Bolivia discovered psychoactive botanical substances found in a hallucinogenic cocktail known as ayahuasca.

According to Sisti, recognizing history like this was a central theme of his groups work examining the potential for psychedelic use in modern medicine.

Just imagining that if psilocybin is commercializedshould shamans in Mexico and Central America, where some of these medicines originated, receive some sort of direct benefit from the research? Sisti says. Its an issue at the intersection of ethnobotany, colonialism, research ethics, reciprocity, and respect.

Read more at Penn Medicine News.

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Charting a new frontier with psychedelic drugs - Penn Today

A new study led by the Washington University School of Medicine in St. Louis has shown how psilocybin, the psychedelic compound in magic mushrooms, affects the brain.

A single dose of psilocybin, a psychedelic that acutely causes distortions of space-time perception and ego dissolution, produces rapid and persistent therapeutic effects in human clinical trials, wrote the study authors.

In animal models, psilocybin induces neuroplasticity in cortex and hippocampus. It remains unclear how human brain network changes relate to subjective and lasting effects of psychedelics.

The researchers discovered that psilocybin temporarily disrupts the default mode network, a crucial brain area involved in introspective thinking, such as daydreaming and remembering.

This desynchronization leads to the characteristic psychedelic experience and could explain psilocybins potential to treat mental illnesses like depression and PTSD.

Theres a massive effect initially, and when its gone, a pinpoint effect remains, said so-senior author Dr. Nico U. F. Dosenbach of WUSTL. Thats exactly what youd want to see for a potential medicine.

Dosenbach went on to explain that you wouldnt want peoples brain networks to be obliterated for days, but you also wouldnt want everything to snap back to the way it was immediately. You want an effect that lasts long enough to make a difference.

The experts utilized functional MRI scans to observe the brain activity of seven healthy adults before, during, and after consuming psilocybin or methylphenidate. The researchers aimed to correlate changes in brain networks with subjective experiences.

These days, we know a lot about the psychological effects and the molecular/cellular effects of psilocybin, said first author Dr. Joshua S. Siegel. But we dont know much about what happens at the level that connects the two the level of functional brain networks.

Psilocybin caused profound but temporary changes in the brains functional networks, particularly the default mode network.

After the acute effects of the drug wore off, small differences from pre-psilocybin scans persisted for weeks.

The idea is that youre taking this system thats fundamental to the brains ability to think about the self in relation to the world, and youre totally desynchronizing it temporarily, explained Dr. Siegel.

In the short term, this creates a psychedelic experience. The longer-term consequence is that it makes the brain more flexible and potentially more able to come into a healthier state.

During the experience, participants rated their feelings of transcendence, connectedness, and awe using the validated Mystical Experience Questionnaire.

The changes in functional networks corresponded with the intensity of each participants subjective experience.

We were able to get very precise data on the effects of the drug in each individual, said co-senior author Dr. Ginger E. Nicol.

This is a step toward precision clinical trials. In psychiatry, we often dont know who should get a particular medicine and how much or how often. By using this approach in clinical trials, we can identify the factors that determine who benefits and who doesnt, and make better use of the medicines we have.

However, the researchers caution against self-medicating with psilocybin, which is not FDA-approved and carries risks if taken without professional supervision.

The dramatic departure from typical synchronized patterns of co-activity may be key to understanding the acute effects of psilocybin and also its persistent neurotrophic effects, wrote the researchers.

Changes in resting activity are linked to shifts in glutamate-dependent signaling during psilocybin exposure.

This phenomenon, shared by ketamine and psychedelics, engages homeostatic plasticity mechanisms, a neurobiological response to large deviations in typical network activity patterns.

Psychedelics rapidly induce synaptogenesis in the hippocampus and cortex, effects that seem to be necessary for rapid antidepressant-like effects in animal models.

However, understanding the underpinnings of the behavioral effects of psychedelics requires human studies.

Advances in precision functional mapping and individual-level characterization enabled us to identify desynchronization of resting-state fMRI signals, connect these changes with subjective psychedelic effects and localize these changes to depression-relevant circuits (DMN, hippocampus).

These analyses rely on precise characterization of an individuals baseline brain organization (for example, individual definition of brain areas, networks and day-to-day variability) to understand how that organization is altered by an intervention.

The study is published in the journal Nature.

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Psychedelics give the brain flexibility to enter a healthier state - Earth.com

Healing centers in Colorado may be allowed to offer the drug psilocybin in a few different forms when the voter-approved psychedelic therapy industry launches next year.

Some customers will choose to eat dried mushrooms or to swallow a capsule. But the most controversial option may be chocolates and confections laced with psilocybin.

Advocates for child safety are raising a red flag, saying that allowing psilocybin to be packaged as a treat may be the wrong move.

There were so many lessons learned after the legalization of cannabis, that we're just trying to make sure the state is being a little more forward-looking when it comes to this new substance, said Alton Dillard, a spokesman for One Chance to Grow Up, a nonprofit that advocates for youth drug safety.

The chocolate controversy comes as the state is finalizing the rules and regulations for the industry. A draft proposal, which is open for public comment until July 25, would allow the industry to offer chocolates and soft confections to customers.

The industry will only serve people 21 and older. And, unlike with cannabis, there will be no retail sales. Instead, the drugs would be consumed on-site under the supervision of a trained professional.

Industry advocates say that using chocolates and confections to consume psilocybin are not meant to appeal to children. Instead, chocolates may be easier for some adults to stomach than dried mushrooms, which can taste unpleasant. Chocolate also may help to soothe the nausea that comes with a mushroom trip, advocates say. Some cultivators are also interested in adding other herbal supplements, like lions mane mushrooms, to their products.

The bottom line is really just trying to create the best options for the folks out there that are looking for access to support their mental health, or in contexts like terminal or advanced illness, said Tasia Poinsatte, director of the Healing Advocacy Fund of Colorado, a major force behind the new law.

Dillard acknowledged that children will likely have little access to the product. But he worries that allowing psilocybin sweets now, even in a therapeutic setting, could send the wrong message for the future. It could open the door for allowing chocolates and confections in the retail market, he argued, if the state were to eventually legalize retail sales of psychedelics.

Were just wanting to make sure that any protections that are in place for kids get factored into the discussion early, instead of the light bulb going on six, eight, ten years down the road, Dillard said.

The most common effects of psilocybin are sensory distortions and hallucinations, said Dr. Chris Hoyte, medical director of the Rocky Mountain Poison Center. Those effects can be frightening or potentially dangerous, for example, if they impair a persons ability to drive.

Those hallucinations could take various sorts of forms and have different risks, depending on your age, or what you're doing at the time, Hoyte said.

Dillard urged the state to learn lessons from the rollout of the cannabis industry. A lack of early regulation led to an explosion of different products, from gummies to sodas, nasal sprays and inhalers, often with playful and appealing packaging.

Thats a valuable perspective, according to Allison Robinette, who is overseeing some of the rulemaking as a policy director at the Department of Revenue.

In the early days of legal cannabis, the state didnt have any limits or restrictions on product types, Robinette said. By the time Colorado changed its legal approach, the range of products we are seeing in the cannabis space was way outpacing our regulations. We took that lesson very much to heart.

With the psilocybin process, the state is instead creating a short list of allowable uses. That includes dried mushrooms, chocolates, confections, teas, tinctures, capsules and tablets.

You can only make certain product types. And you have to do it in line with the regulations around manufacturing procedures, she said. Our intent is not to stifle someone's ability to make products that participants want. But it gives us the forethought and to be proactive about instilling regulations.

Shawn Hauser is a partner at Vicente LLP, a law firm that has been closely involved in Colorados cannabis and psilocybin industries.

She said the state had done a good job of listening to various parties as it drafts the industry rules. But she warned that if officials create too many onerous regulations, customers will instead buy less safe products from unregulated and illegal sources. The gray market is already growing fast under the new law.

The intent of the program is to give consumers access to these products where they're safe, she said. What we don't want is someone getting sick because they got an unsafe product on the illicit market because they don't have access through the regulated system.

Hoyte, of Rocky Mountain Poison Center, urged the state to ensure that products are tested and clearly labeled, so people are very clear on what theyre actually consuming.

The state has heard from close to 100 people who are interested in launching psilocybin businesses, ranging from mushroom cultivators to product manufacturers, testing labs and healing centers. The first licenses are expected to be granted early in 2025.

Like cannabis, psilocybin remains illegal under federal law.

Link:

Why sweet treats may be the most controversial part of Colorados new psychedelic mushrooms program - Colorado Public Radio