Research on the clinical applications of psychedelic-assisted psychotherapy has demonstrated promising early results for treatment of alcohol dependence. Detailed description of the content and methods of psychedelic-assisted psychotherapy, as it is conducted in clinical settings, is scarce.Methods: An open-label pilot (proof-of-concept) study of psilocybin-assisted treatment of alcohol dependence (NCT01534494) was conducted to generate data for a phase 2 RCT (NCT02061293) of a similar treatment in a larger population. The present paper presents a qualitative content analysis of the 17 debriefing sessions conducted in the pilot study, which occurred the day after corresponding psilocybin medication sessions.Results: Participants articulated a series of key phenomena related to change in drinking outcomes and acute subjective effects of psilocybin.Discussion: The data illuminate change processes in patients' own words during clinical sessions, shedding light on potential therapeutic mechanisms of change and how participants express effects of psilocybin. This study is unique in analyzing actual clinical sessions, as opposed to interviews of patients conducted separately from treatment.
Salvinorin A (SA) is a κ-opioid receptor agonist and atypical dissociative hallucinogen found in Salvia divinorum. Despite the resurgence of hallucinogen studies, the effects of κ-opioid agonists on human brain function are not well-understood. This placebo-controlled, within-subject study used functional magnetic resonance imaging for the first time to explore the effects of inhaled SA on strength, variability, and entropy of functional connectivity (static, dynamic, and entropic functional connectivity, respectively, or sFC, dFC, and eFC). SA tended to decrease within-network sFC but increase between-network sFC, with the most prominent effect being attenuation of the default mode network (DMN) during the first half of a 20-min scan (i.e., during peak effects). SA reduced brainwide dFC but increased brainwide eFC, though only the former effect survived multiple comparison corrections. Finally, using connectome-based classification, most models trained on dFC network interactions could accurately classify the first half of SA scans. In contrast, few models trained on within- or between-network sFC and eFC performed above chance. Notably, models trained on within-DMN sFC and eFC performed better than models trained on other network interactions. This pattern of SA effects on human brain function is strikingly similar to that of other hallucinogens, necessitating studies of direct comparisons.
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