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An international mega-analysis of psychedelic drug effects on brain circuit function

Manesh Girn, Manoj K. Doss, Leor Roseman, Katrin H. Preller, Fernanda Palhano-Fontes, Lorenzo Pasquini, Frederick S. Barrett, Pablo Mallaroni, Natasha L. Mason, Christopher Timmermann, Drummond E. Mcculloch, Patrick M. Fisher, Brian S. Winston, Flora Moujaes, Felix Müller, Matthias E. Liechti, Franz X. Vollenweider, Johannes G. Ramaekers, Kim Kuypers, Dráulio B. Araújo, Olaf Sporns, Joshua Siegel, Nico Dosenbach, David J. Nutt, Robin L. Carhart-Harris, Emmanuel A. Stamatakis, Danilo Bzdok

Nature Medicine April 1, 2026 DOI: 10.1038/s41591-026-04287-9 via OpenAlex

Summary

AI-generated from the abstract

Psychedelic drugs are being studied again for their therapeutic potential, but how they change brain function is not well understood. By combining 11 brain-scanning datasets from five different psychedelics (psilocybin, LSD, mescaline, DMT, and ayahuasca) across three continents, researchers found a common pattern: increased communication between brain networks that handle high-level thinking (default, frontoparietal, and limbic) and those that handle sensory input (visual and somatomotor). Key deep-brain regions (thalamus, caudate, putamen) and the cerebellum also changed how they connect with sensorimotor networks. Contrary to some earlier studies, reductions in within-network connectivity were weak to moderate and varied by drug. These findings help resolve previous inconsistencies and provide a comprehensive map of how psychedelics alter large-scale brain organization.

Study at a glance

Characteristics Mega-analysis Peer reviewed
Population Human participants from 11 independent resting-state functional magnetic resonance imaging datasets
Citations 8
Key finding Psychedelics consistently increase functional connectivity between transmodal (default, frontoparietal, limbic) and unimodal (visual, somatomotor) networks, with selective subcortical involvement, while within-network connectivity reductions are weak to moderate and vary by drug.

Abstract

Psychedelic drugs are re-emerging as promising scientific and clinical tools. However, despite a rapidly expanding literature on their therapeutic value, the neural mechanisms underlying psychedelic effects remain unclear. Resting-state functional magnetic resonance imaging studies of acute psychedelic effects, conducted independently by several research groups, have so far yielded fragmented and sometimes inconsistent findings. Here, to help facilitate greater convergence, we conducted a 'mega-analysis' integrating 11 independent resting-state functional magnetic resonance imaging datasets across five psychedelic drugs (psilocybin, lysergic acid diethylamide, mescaline, N,N-dimethyltryptamine and ayahuasca) from research groups spanning three continents and five countries. By applying a uniform preprocessing pipeline and a Bayesian hierarchical modeling framework, we discovered several common features in the induced alterations to brain function across drugs and sites. Most prominently, we identified a core signature of increased functional connectivity between transmodal (default, frontoparietal and limbic) and unimodal networks (visual and somatomotor), with subnetwork specificity. Furthermore, key subcortical regions (thalamus, caudate and putamen) and the cerebellum exhibited altered coupling with sensorimotor networks. In contrast to several single-site reports, Bayesian modeling revealed weak-to-moderate and selective reductions in within-network functional connectivity, with substantial variability across drugs and networks. Together, these findings extend past work by demonstrating that psychedelics reconfigure large-scale cortical organization while selectively engaging subcortical circuitry. This study provides the most comprehensive synthesis of psychedelic brain action to date, helping resolve inconsistencies and offering a probabilistic map of how psychedelics alter large-scale brain organization. We hereby provide a cornerstone to benchmark and shepherd future psychedelic neuroimaging research.

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