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

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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Publication Details

Journal
Nature Medicine
Published
2026-04-01
DOI
https://doi.org/10.1038/s41591-026-04287-9
Citations
1
Primary Topic
Psychedelics and Drug Studies
Type
article
Field-Weighted Citation Impact
29.25

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article

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

Olaf Sporns, Manesh Girn, Lorenzo Pasquini, Patrick M. Fisher et al.
1 citations
Nature Medicine
Psychedelics and Drug Studies
29.25
article

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

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

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.

Nature MedicineVol. 32(4)
Montreal Neurological Institute and Hospital (CA), Johns Hopkins University (US), University of California, San Francisco (US), University of Zurich (CH), University of Exeter (GB), University of Cambridge (GB), University Hospital of Basel (CH), Rigshospitalet (DK), Maastricht University (NL), Universidade Federal do Rio Grande do Norte (BR), Multidisciplinary Association for Psychedelic Studies (US), Indiana University Bloomington (US), Mila - Quebec Artificial Intelligence Institute (CA), University of San Francisco (US), The University of Texas at Austin (US)
Canadian Institute for Advanced Research, Fondation Brain Canada, Canada First Research Excellence Fund, Institut de Valorisation des Données, National Institutes of Health, Health Canada, Canadian Institutes of Health Research
Openalex Percentile: Top 1%
Psychedelics and Drug Studies
29.25
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