Perceived changes in mental health and social engagement attributed to a single psychedelic experience in autistic adults: results from an online survey.

Rationale: Anecdotal reports suggest that psychedelic drugs can improve psychological wellbeing and social engagement in autistic people. However, there are few contemporary studies on this topic.

Objectives: To examine autistic participants' experiences with psychedelic drugs and the extent to which they attributed changes in mental health and social engagement to their most 'impactful' psychedelic experience.

Can Psychedelic Use Benefit Meditation Practice? Examining Individual, Psychedelic, and Meditation-Related Factors.

Introduction: Meditation practice and psychedelic use have attracted increasing attention in the public sphere and scientific research. Both methods induce non-ordinary states of consciousness that may have significant therapeutic benefits. Thus, there is growing scientific interest in potential synergies between psychedelic use and meditation practice with some research suggesting that psychedelics may benefit meditation practice.

Cannabidiol reverses attentional bias to cigarette cues in a human experimental model of tobacco withdrawal.

Background And Aims: Cannabidiol (CBD), a non-intoxicating cannabinoid found in cannabis, may be a promising novel smoking cessation treatment due to its anxiolytic properties, minimal side effects and research showing that it may modify drug cue salience. We used an experimental medicine approach with dependent cigarette smokers to investigate if (1) overnight nicotine abstinence, compared with satiety, will produce greater attentional bias (AB), higher pleasantness ratings of cigarette-related stimuli and increased craving and withdrawal; and (2) CBD in comparison to placebo, would attenuate AB, pleasantness of cigarette-related stimuli, craving and withdrawal and not produce any side effects.

Design: Randomized, double-blind cross-over study with a fixed satiated session followed by two overnight abstinent sessions.

Natural speech algorithm applied to baseline interview data can predict which patients will respond to psilocybin for treatment-resistant depression.

Background: Natural speech analytics has seen some improvements over recent years, and this has opened a window for objective and quantitative diagnosis in psychiatry. Here, we used a machine learning algorithm applied to natural speech to ask whether language properties measured before psilocybin for treatment-resistant can predict for which patients it will be effective and for which it will not.

Methods: A baseline autobiographical memory interview was conducted and transcribed.