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Maps by Which We May Not Steer: Why Psychologists Should Expect Low Belief-Behavior Correspondence

Psychological Inquiry 2025年第1期36卷

作者： Joseph Sommer Kerem Oktar a University Center for Human Values/Program in Cognitive Science Princeton University Princeton New Jersey b Department of Psychology Princeton University Princeton New Jersey

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From Efficient Coding to Information Gain: Information-Theoretic Principles in Models of human Decision Making 42

From Efficient Coding to Information Gain: Information-Theor...

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42nd Annual Meeting of the cognitive science Society: Developing a Mind: Learning in humans, Animals, and Machines, CogSci 2020

作者： Akrenius, Mikaela Maloney, Laurence T. Nelson, Jonathan D. Cognitive Science Program Indiana University Bloomington United States Department of Psychology Center for Neural Science New York University United States School of Psychology University of Surrey Max Planck Institute for Human Development Berlin Germany

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ENIGMA-Meditation: Worldwide Consortium for Neuroscientific Investigations of Meditation Practices

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Biological Psychiatry: cognitive Neuroscience and Neuroimaging 2025年第4期10卷 425-436页

作者： Ganesan, Saampras Barrios, Fernando A. Batta, Ishaan Bauer, Clemens C.C. Braver, Todd S. Brewer, Judson A. Brown, Kirk Warren Cahn, Rael Cain, Joshua A. Calhoun, Vince D. Cao, Lei Chetelat, Gaël Ching, Christopher R.K. Creswell, J. David Dagnino, Paulina Clara Davanger, Svend Davidson, Richard J. Deco, Gustavo Dutcher, Janine M. Escrichs, Anira Eyler, Lisa T. Fani, Negar Farb, Norman A.S. Fialoke, Suruchi Fresco, David M. Garg, Rahul Garland, Eric L. Goldin, Philippe Hafeman, Danella M. Jahanshad, Neda Kang, Yoona Khalsa, Sahib S. Kirlic, Namik Lazar, Sara W. Lutz, Antoine McDermott, Timothy J. Pagnoni, Giuseppe Piguet, Camille Prakash, Ruchika S. Rahrig, Hadley Reggente, Nicco Saccaro, Luigi F. Sacchet, Matthew D. Siegle, Greg J. Tang, Yi-Yuan Thomopoulos, Sophia I. Thompson, Paul M. Torske, Alyssa Treves, Isaac N. Tripathi, Vaibhav Tsuchiyagaito, Aki Turner, Matthew D. Vago, David R. Valk, Sofie Zeidan, Fadel Zalesky, Andrew Turner, Jessica A. King, Anthony P. Department of Biomedical Engineering The University of Melbourne Carlton VIC Australia Contemplative Studies Centre Melbourne School of Psychological Sciences The University of Melbourne Melbourne VIC Australia Systems Lab of Neuroscience Neuropsychiatry and Neuroengineering The University of Melbourne Parkville VIC Australia Universidad Nacional Autónoma de México Instituto de Neurobiolgía México Querétaro Mexico Center for Translational Research in Neuroimaging and Data Science: Georgia State University Georgia Institute of Technology and Emory University Atlanta GA United States Department of Psychology Northeastern University Boston Massachusetts Brain and Cognitive Science McGovern Institute for Brain Research Massachusetts Institute of Technology Cambridge Massachusetts Department of Psychological and Brain Sciences Washington University St. Louis Missouri Department of Behavioral and Social Sciences Brown University School of Public Health Providence Rhode Island Department of Psychology Carnegie Mellon University Pittsburgh PA United States University of Southern California Department of Psychiatry & Behavioral Sciences Los Angeles California University of Southern California Center for Mindfulness Science Los Angeles California Institute for Advanced Consciousness Studies Santa Monica California Department of Psychiatry and Behavioral Health The Ohio State University College of Medicine Columbus OH United States Normandie University Université de Caen Normandie INSERM U1237 Neuropresage Team Cyceron Caen France Imaging Genetics Center Mark and Mary Stevens Neuroimaging and Informatics Institute Keck School of Medicine of the University of Southern California Los Angeles California Desert-Pacific Mental Illness Research Education and Clinical Center VA San Diego Healthcare System San Diego California Computational Neuroscience Group Center for Brain and Cognition Department of Information and Communication Technologies Universitat Pompeu Fa

Meditation is a family of ancient and contemporary contemplative mind-body practices that can modulate psychological processes, awareness, and mental states. Over the last 40 years, clinical science has manualized meditation practices and designed various meditation interventions that have shown therapeutic efficacy for disorders including depression, pain, addiction, and anxiety. Over the past decade, neuroimaging has been used to examine the neuroscientific basis of meditation practices, effects, states, and outcomes for clinical and nonclinical populations. However, the generalizability and replicability of current neuroscientific models of meditation have not yet been established, because they are largely based on small datasets entrenched with heterogeneity along several domains of meditation (e.g., practice types, meditation experience, clinical disorder targeted), experimental design, and neuroimaging methods (e.g., preprocessing, analysis, task-based, resting-state, structural magnetic resonance imaging). These limitations have precluded a nuanced and rigorous neuroscientific phenotyping of meditation practices and their potential benefits. Here, we present ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis)–Meditation, the first worldwide collaborative consortium for neuroscientific investigations of meditation practices. ENIGMA-Meditation will enable systematic meta- and mega-analyses of globally distributed neuroimaging datasets of meditation using shared, standardized neuroimaging methods and tools to improve statistical power and generalizability. Through this powerful collaborative framework, existing neuroscientific accounts of meditation practices can be extended to generate novel and rigorous neuroscientific insights that account for multidomain heterogeneity. ENIGMA-Meditation will inform neuroscientific mechanisms that underlie therapeutic action of meditation practices on psychological and cognitive attributes, thereby advancing the f

关键词： Consortium ENIGMA Magnetic resonance imaging (MRI) Meditation Mindfulness Neuroimaging

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Functional redundancy of the posterior hippocampi is selectively disrupted in non-demented older adults with β-amyloid deposition

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NeuroImage: Reports 2025年第2期5卷 100255-100255页

作者： Blujus, Jenna K. Cole, Michael W. Festa, Elena K. Buka, Stephen L. Salloway, Stephen P. Heindel, William C. Oh, Hwamee Department of Cognitive and Psychological Sciences Brown University Providence 02912 United States Center for Molecular & Behavioral Neuroscience Rutgers University Newark 07102 United States Department of Epidemiology and Population Health Brown University Providence 02912 United States Department of Psychiatry and Human Behavior Brown University Providence 02912 United States Memory and Aging Program Butler Hospital Providence 02906 United States Department of Neurology Brown University Providence 02912 United States Carney Institute for Brain Science Brown University Providence 02912 United States

Several neural mechanisms underlying resilience to Alzheimer's disease (AD) have been proposed, including redundant neural connections between the posterior hippocampi and all other brain regions, and global functional connectivity of the left frontal cortex (LFC). Here, we investigated if functional redundancy of the hippocampus (HC) and LFC underscores neural resilience in the presence of early AD pathologies. From the ADNI database, cognitively normal older adults (CN) (N = 220;36 % Aβ+) and patients with Mild cognitive Impairment (MCI) (N = 143;51 % Aβ+) were utilized. Functional redundancy was calculated from resting state fMRI data using a graph theoretical approach by summing the direct and indirect paths (path lengths = 1–4) between each region of interest and its 263 functional connections. Posterior HC, but not anterior HC or LFC, redundancy was significantly lower in Aβ+ than Aβ-groups, regardless of diagnosis. Posterior HC redundancy related to higher education and better episodic memory, but it did not moderate the Aβ-cognition relationships across the diagnostic groups. Together, these findings suggest that posterior HC redundancy captures network disruption that parallels selective vulnerability to Aβ deposition. Further, our findings indicate that functional redundancy may underscore a network metric different from global functional connectivity of the LFC. © 2025

关键词： Aging Alzheimer's disease Beta-amyloid plaques Functional magnetic resonance imaging Graph theory Resilience

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Visual representations in the human brain are aligned with large language models

arXiv

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arXiv 2022年

作者： Doerig, Adrien Kietzmann, Tim C. Allen, Emily Wu, Yihan Naselaris, Thomas Kay, Kendrick Charest, Ian Institute of Cognitive Science University of Osnabrück Germany Donders Institute for Brain Cognition & Behaviour Nijmegen Netherlands Department of Radiology University of Minnesota MinneapolisMN United States Department of Psychology University of Minnesota MinneapolisMN United States Graduate Program in Cognitive Science University of Minnesota MinneapolisMN United States Department of Neuroscience University of Minnesota MinneapolisMN United States cerebrUM Département de Psychologie Université de Montréal Montréal Canada Center for Human Brain Health School of Psychology University of Birmingham Birmingham United Kingdom

The human brain extracts complex information from visual inputs, including objects, their spatial and semantic interrelations, and their interactions with the environment. However, a quantitative approach for studying this information remains elusive. Here, we test whether the contextual information encoded in large language models (LLMs) is beneficial for modelling the complex visual information extracted by the brain from natural scenes. We show that LLM embeddings of scene captions successfully characterise brain activity evoked by viewing the natural scenes. This mapping captures selectivities of different brain areas, and is sufficiently robust that accurate scene captions can be reconstructed from brain activity. Using carefully controlled model comparisons, we then proceed to show that the accuracy with which LLM representations match brain representations derives from the ability of LLMs to integrate complex information contained in scene captions beyond that conveyed by individual words. Finally, we train deep neural network models to transform image inputs into LLM representations. Remarkably, these networks learn representations that are better aligned with brain representations than a large number of state-of-the-art alternative models, despite being trained on orders-of-magnitude less data. Overall, our results suggest that LLM embeddings of scene captions provide a representational format that accounts for complex information extracted by the brain from visual inputs. Copyright © 2022, The Authors. All rights reserved.

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Consciousness in Artificial Intelligence: Insights from the science of Consciousness

arXiv

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arXiv 2023年

作者： Butlin, Patrick Long, Robert Elmoznino, Eric Bengio, Yoshua Birch, Jonathan Constant, Axel Deane, George Fleming, Stephen M. Frith, Chris Ji, Xu Kanai, Ryota Klein, Colin Lindsay, Grace Michel, Matthias Mudrik, Liad Peters, Megan A.K. Schwitzgebel, Eric Simon, Jonathan VanRullen, Rufin Future of Humanity Institute University of Oxford United Kingdom Center for AI Safety United States University of Montreal MILA - Quebec AI Institute Canada Centre for Philosophy of Natural and Social Science London School of Economics and Political Science United Kingdom School of Engineering and Informatics The University of Sussex Centre de Recherche en Éthique University of Montreal United Kingdom Department of Philosophy University of Montreal Canada Department of Experimental Psychology Wellcome Centre for Human Neuroimaging University College London United Kingdom Wellcome Centre for Human Neuroimaging University College London Institute of Philosophy University of London United Kingdom Araya Inc. School of Philosophy The Australian National University Australia Department of Psychology Center for Data Science New York University United States Center for Mind Brain and Consciousness New York University United States School of Psychological Sciences and Sagol School of Neuroscience Tel-Aviv University CIFAR Program in Brain Mind and Consciousness Israel Department of Cognitive Sciences University of California Irvine and CIFAR Program in Brain Mind and Consciousness United States Department of Philosophy University of California Riverside United States Centre de Recherche Cerveau et Cognition CNRS Université de Toulouse France

Whether current or near-term AI systems could be conscious is a topic of scientific interest and increasing public concern. This report argues for, and exemplifies, a rigorous and empirically grounded approach to AI consciousness: assessing existing AI systems in detail, in light of our best-supported neuroscientific theories of consciousness. We survey several prominent scientific theories of consciousness, including recurrent processing theory, global workspace theory, higher-order theories, predictive processing, and attention schema theory. From these theories we derive"indicator properties" of consciousness, elucidated in computational terms that allow us to assess AI systems for these properties. We use these indicator properties to assess several recent AI systems, and we discuss how future systems might implement them. Our analysis suggests that no current AI systems are conscious, but also suggests that there are no obvious technical barriers to building AI systems which satisfy these indicators.1 © 2023, CC BY-NC-SA.

关键词： Neurophysiology

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Liver function and Alzheimer's brain pathologies: A longitudinal study: Liver and Alzheimer's pathologies

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The journal of prevention of Alzheimer's disease 2025年第1期12卷 100012-100012页

作者： Kim, Jee Wook Byun, Min Soo Yi, Dahyun Jung, Joon Hyung Kong, Nayeong Chang, Yoon Young Jung, Gijung Ahn, Hyejin Lee, Jun-Young Kang, Koung Mi Sohn, Chul-Ho Lee, Yun-Sang Kim, Yu Kyeong Lee, Dong Young Department of Neuropsychiatry Hallym University Dongtan Sacred Heart Hospital 7 Keunjaebong-gil Hwaseong Gyeonggi 18450 Republic of Korea Department of Psychiatry Hallym University College of Medicine Chuncheon Gangwon 24252 Republic of Korea. Electronic address: 38549@hallym.ac.kr Department of Neuropsychiatry Seoul National University Hospital Seoul 03080 Republic of Korea Department of Psychiatry Seoul National University College of Medicine Seoul 03080 Republic of Korea. Electronic address: bminsoo@*** Institute of Human Behavioral Medicine Medical Research Center Seoul National University 03080 Seoul South Korea Department of Psychiatry Chungbuk National University Hospital Cheongju 28644 South Korea Department of Psychiatry Keimyung University Dongsan Hospital 42601 Daegu South Korea Department of Psychiatry Inje University Sanggye Paik Hospital 01757 Seoul South Korea Department of Neuropsychiatry Seoul National University Hospital 03080 Seoul South Korea Interdisciplinary Program of Cognitive Science Seoul National University College of Humanities 08826 Seoul South Korea Department of Psychiatry Seoul National University College of Medicine Seoul 03080 Republic of Korea Department of Neuropsychiatry SMG-SNU Boramae Medical Center Seoul 07061 Republic of Korea. Electronic address: benji@snu.ac.kr Department of Radiology Seoul National University Hospital 03080 Seoul South Korea Department of Radiology Seoul National University Hospital 03080 Seoul South Korea Department of Nuclear Medicine Seoul National University College of Medicine 03080 Seoul South Korea Department of Nuclear Medicine SMG-SNU Boramae Medical Center 07061 Seoul South Korea Department of Neuropsychiatry Seoul National University Hospital Seoul 03080 Republic of Korea Department of Psychiatry Seoul National University College of Medicine Seoul 03080 Republic of Korea Institute of Human Behavioral Medicine Medical Research Center Seoul National University Seoul 0

IMPORTANCE: The neuropathological links underlying the association between changes in liver function and AD have not yet been clearly elucidated. OBJECTIVE: We aimed to examine the relationship between liver function markers and longitudinal changes in Alzheimer's disease (AD) core pathologies. DESIGN: Data from the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's Disease, a longitudinal cohort study initiated in 2014, were utilized. SETTING: Community and memory clinic setting. PARTICIPANTS: Three hundred forty-seven older adults. MAIN OUTCOME AND MEASURES: Participants underwent baseline and 2-year follow-up evaluations, including liver function assessments and various brain imaging techniques, such as amyloid and tau PET, FDG-PET, and MRI). Liver function indicators [alanine aminotransferase (ALT), aspartate aminotransferase (AST), and total bilirubin] were examined as exposure variables. RESULTS: Higher baseline ALT levels were associated with a greater increase in beta-amyloid deposition over 2 years [β = 0.166, Bonferroni-corrected P (PB) = 0.012], while lower total bilirubin levels were associated with a greater increase in tau deposition over the same period (β = -0.570, PB < 0.001). In contrast, AST alone showed no significant association with changes of AD pathologies. CONCLUSIONS AND RELEVANCE: The findings suggest a possible link between lower liver function and the accumulation of core AD pathologies in the brain. These results also support the possibility that the liver-brain axis could be a potential target for therapeutic or preventive strategies against AD. Copyright © 2024. Published by Elsevier Masson SAS.

关键词： alanine aminotransferase Alzheimer's disease Aβ tau total bilirubin

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Corrigendum to "First few seconds for flow: A comprehensive proposal of the neurobiology and neurodynamics of state onset" [Neurosci. Biobehav. Rev. 143 (2022)]

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Neuroscience and biobehavioral reviews 2023年 147卷 105086页

作者： Steven Kotler Michael Mannino Scott Kelso Richard Huskey Flow Research Collective United States. Human Brain & Behavior Laboratory Center for Complex Systems and Brain Sciences Florida Atlantic University United States Intelligent Systems Research Centre Ulster University Derry∼Londonderry North Ireland. Cognitive Communication Science Lab Department of Communication University of California Davis United States Cognitive Science Program University of California Davis United States Center for Mind and Brain University of California Davis United States. Electronic address: rwhuskey@ucdavis.edu.

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A consensus protocol for functional connectivity analysis in the rat brain (vol 26, pg 673, 2023)

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NATURE NEUROscience 2023年第6期26卷 1127-1128页

作者： Grandjean, Joanes Desrosiers-Gregoire, Gabriel Anckaerts, Cynthia Angeles-Valdez, Diego Ayad, Fadi Barriere, David A. Blockx, Ines Bortel, Aleksandra Broadwater, Margaret Cardoso, Beatriz M. Celestine, Marina Chavez-Negrete, Jorge E. Choi, Sangcheon Christiaen, Emma Clavijo, Perrin Colon-Perez, Luis Cramer, Samuel Daniele, Tolomeo Dempsey, Elaine Diao, Yujian Doelemeyer, Arno Dopfel, David Dvorakova, Lenka Falfan-Melgoza, Claudia Fernandes, Francisca F. Fowler, Caitlin F. Fuentes-Ibanez, Antonio Garin, Clement M. Gelderman, Eveline Golden, Carla E. M. Guo, Chao C. G. Henckens, Marloes J. A. G. Hennessy, Lauren A. Herman, Peter Hofwijks, Nita Horien, Corey Ionescu, Tudor M. Jones, Jolyon Kaesser, Johannes Kim, Eugene Lambers, Henriette Lazari, Alberto Lee, Sung-Ho Lillywhite, Amanda Liu, Yikang Liu, Yanyan Y. Lopez-Castro, Alejandra Lopez-Gil, Xavier Ma, Zilu MacNicol, Eilidh Madularu, Dan Mandino, Francesca Marciano, Sabina McAuslan, Matthew J. McCunn, Patrick McIntosh, Alison Meng, Xianzong Meyer-Baese, Lisa Missault, Stephan Moro, Federico Naessens, Daphne M. P. Nava-Gomez, Laura J. Nonaka, Hiroi Ortiz, Juan J. Paasonen, Jaakko Peeters, Lore M. Pereira, Mickael Perez, Pablo D. Pompilus, Marjory Prior, Malcolm Rakhmatullin, Rustam Reimann, Henning M. Reinwald, Jonathan Del Rio, Rodrigo Triana Rivera-Olvera, Alejandro Ruiz-Perez, Daniel Russo, Gabriele Rutten, Tobias J. Ryoke, Rie Sack, Markus Salvan, Piergiorgio Sanganahalli, Basavaraju G. Schroeter, Aileen Seewoo, Bhedita J. Selingue, Erwan Seuwen, Aline Shi, Bowen Sirmpilatze, Nikoloz Smith, Joanna A. B. Smith, Corrie Sobczak, Filip Stenroos, Petteri J. Straathof, Milou Strobelt, Sandra Sumiyoshi, Akira Takahashi, Kengo Torres-Garcia, Maria E. Tudela, Raul van den Berg, Monica van der Marel, Kajo van Hout, Aran T. B. Vertullo, Roberta Vidal, Benjamin Vrooman, Roel M. Wang, Victora X. Wank, Isabel Watson, David J. G. Yin, Ting Zhang, Yongzhi Zurbruegg, Stefan Achard, Sophie Alcauter, Sarael Auer, Dorothee P. Barbier, Emmanuel L. Baudewig, Juergen Beckmann, Chri Donders Institute for Brain Behaviour and Cognition Radboud University Nijmegen The Netherlands Department for Medical Imaging Radboud University Medical Center Nijmegen The Netherlands Cerebral Imaging Centre Douglas Mental Health University Institute Verdun QC Canada Integrated Program in Neuroscience McGill University Montreal QC Canada Bio-imaging Lab University of Antwerp Antwerp Belgium µNEURO Research Centre of Excellence University of Antwerp Antwerp Belgium Instituto de Neurobiología Universidad Nacional Autónoma de México Campus Juriquilla Querétaro Mexico Biological and Biomedical Engineering McGill University Montreal QC Canada McConnell Brain Imaging Centre McGill University Montreal QC Canada Montreal Neurological Institute McGill University Montreal QC Canada UMR INRAE/CNRS 7247 Physiologie des Comportements et de la Reproduction Physiologie de la reproduction et des comportements Centre de recherche INRAE de Nouzilly Tours France Department of Neurology and Neurosurgery McGill University Montreal QC Canada Center for Animal MRI University of North Carolina at Chapel Hill Chapel Hill NC USA Department of Neurology University of North Carolina at Chapel Hill Chapel Hill NC USA Biomedical Research Imaging Center University of North Carolina at Chapel Hill Chapel Hill NC USA Preclinical MRI Champalimaud Research Champalimaud Centre for the Unknown Lisbon Portugal Laboratoire des Maladies Neurodégénératives Molecular Imaging Research Center (MIRCen) Université Paris-Saclay Commissariat à l’Énergie Atomique et aux Énergies Alternatives (CEA) CNRS Fontenay-aux-Roses France Departamento de Neurobiología Conductual y Cognitiva Instituto de Neurobiología Universidad Nacional Autónoma de México Campus Juriquilla Querétaro México Translational Neuroimaging and Neural Control Group High-Field Magnetic Resonance Max Planck Institute for Biological Cybernetics Tuebingen Germany Graduate Training Centre of Neuroscience International Max

Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows for comparisons with data modalities collected under invasive or terminal procedures. Currently, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. Here we introduce StandardRat, a consensus rat functional magnetic resonance imaging acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired from rats across 46 centers. We developed a reproducible pipeline for analyzing rat data acquired with diverse protocols and determined experimental and processing parameters associated with the robust detection of functional connectivity across centers. We show that the standardized protocol enhances biologically plausible functional connectivity patterns relative to previous acquisitions. The protocol and processing pipeline described here is openly shared with the neuroimaging community to promote interoperability and cooperation toward tackling the most important challenges in neuroscience.

关键词： Databases Neural circuits

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On Minimizing Risk and Harm in the Use of Psychedelics

Psychiatric research and clinical practice

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Psychiatric research and clinical practice 2025年第1期7卷 4-8页

作者： Jules Evans Marc Aixalà Brian T Anderson William Brennan Rebecka Bremler Joost J Breeksema Lisa Burback Abigail E Calder Robin L Carhart-Harris Katherine Cheung Neşe Devenot Ingmar Gorman Jakub Greń Peter S Hendricks Brian Holoyda Edward Jacobs Joy Krecké Daniel J Kruger David Luke Tomislav Majić Amy L McGuire Nicky J Mehtani David S Mathai Kristin Nash Tehseen Noorani Roman Palitsky Oliver C Robinson Otto Simonsson Elin Stahre Michiel van Elk David B Yaden The Challenging Psychedelic Experiences Project London UK. International Center for Ethnobotanical Education Research and Services (ICEERS) Barcelona Spain. Department of Psychiatry & Behavioral Sciences University of California San Francisco California USA. Center for the Science of Psychedelics University of California Berkeley Berkeley California USA. GuideSite Consulting LLC New York City New York USA. Centre for Psychedelic Research Imperial College London London UK. Department of Psychiatry Research School of Behavioural and Cognitive Neurosciences University Medical Center Groningen University of Groningen Groningen The Netherlands. Department of Psychiatry University of Alberta Edmonton Alberta Canada. Molecular Psychiatry Lab Faculty of Science and Medicine University of Fribourg Fribourg Switzerland. Psychedelics Division - Neuroscape Department of Neurology University of California San Francisco San Francisco California USA. Department of Health Policy and Management Johns Hopkins Bloomberg School of Public Health and the Berman Institute of Bioethics Johns Hopkins University Baltimore Maryland USA. University Writing Program Johns Hopkins University Baltimore Maryland USA. Fluence Training LLC Woodstock New York USA. Institute of Psychiatry and Neurology Warsaw Poland. Department of Psychiatry and Behavioral Neurobiology University of Alabama at Birmingham Birmingham Alabama USA. Department of Psychiatry & Behavioral Medicine Medical College of Wisconsin Milwaukee Wisconsin USA. Contra Costa County Detention Health Services Martinez California USA. Medical Sciences Division Department of Psychiatry University of Oxford Oxford UK. Department of Psychology Psychopharmacology and Addiction Research Centre University of Exeter Exeter UK. Jacobs School of Medicine and Biomedical Sciences University at Buffalo Buffalo New York USA. School of Human Sciences University of Greenwich London UK. Psychedelic Substances Research Group Psychiatric University Clinic of Charité at St. Hedwig Hospital Charité - Unive

Objective:This article outlines recommendations from 30 psychedelic researchers on how to create a better psychedelic safety net. Methods:A survey of 30 psychedelic researchers asked them to identify key critical research gaps around psychedelic harm and safety. Results:The critical research gaps identified by the authors included defining the main types of psychedelic harm, the predictors of those harms, and the most effective way to treat those harms. They also call for better support for those experiencing post-psychedelic difficulties, including better online information, peer support groups, affordable therapy, and psychiatric consultation and medication. Finally, the authors call for better funding to create a psychedelic safety net, and suggest psychedelic philanthropists, investors and companies could commit 1% of their investment in psychedelics into supporting safety measures such as research and support services. Conclusions:The authors identify several practical steps to create a better psychedelic safety net and call for more funding to psychedelic safety measures such as research and support services. Relevance to clinical practice:The authors outline important gaps in our knowledge around the safety and risk profile of psychedelic medicines and identify practical steps forward for researchers and clinical practitioners to make this promising field safer.

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