Receptor-informed network control theory links LSD and psilocybin to a flattening of the brain’s control energy landscape

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• dc.contributor.author Singleton, S. Parker
• dc.contributor.author Luppi, Andrea I.
• dc.contributor.author Carhart-Harris, Robin L.
• dc.contributor.author Cruzat Grand, Josefina, 1983-
• dc.contributor.author Roseman, Leor
• dc.contributor.author Nutt, David J.
• dc.contributor.author Deco, Gustavo
• dc.contributor.author Kringelbach, Morten L.
• dc.contributor.author Stamatakis, Emmanuel A.
• dc.contributor.author Kuceyeski, Amy
• dc.date.accessioned 2023-03-06T07:30:29Z
• dc.date.available 2023-03-06T07:30:29Z
• dc.date.issued 2022
• dc.description.abstract Psychedelics including lysergic acid diethylamide (LSD) and psilocybin temporarily alter subjective experience through their neurochemical effects. Serotonin 2a (5-HT2a) receptor agonism by these compounds is associated with more diverse (entropic) brain activity. We postulate that this increase in entropy may arise in part from a flattening of the brain’s control energy landscape, which can be observed using network control theory to quantify the energy required to transition between recurrent brain states. Using brain states derived from existing functional magnetic resonance imaging (fMRI) datasets, we show that LSD and psilocybin reduce control energy required for brain state transitions compared to placebo. Furthermore, across individuals, reduction in control energy correlates with more frequent state transitions and increased entropy of brain state dynamics. Through network control analysis that incorporates the spatial distribution of 5-HT2a receptors (obtained from publicly available positron emission tomography (PET) data under non-drug conditions), we demonstrate an association between the 5-HT2a receptor and reduced control energy. Our findings provide evidence that 5-HT2a receptor agonist compounds allow for more facile state transitions and more temporally diverse brain activity. More broadly, we demonstrate that receptor-informed network control theory can model the impact of neuropharmacological manipulation on brain activity dynamics.
• dc.description.sponsorship S.P.S. is supported by the National Science Foundation Graduate Research Fellowship (Grant No. DGE-1650441). A.I.L. is supported by the Gates Cambridge Trust. R.L.C.-H. was supported by the Alex Mosley Charitable Trust and supporters of the Centre for Psychedelic Research during the period of data collection, analysis and write-up and now holds the Ralph Metzner Distinguished Professorship at UCSF. The original study received support from a Crowd Funding Campaign and the Beckley Foundation, as part of the Beckley-Imperial Research Programme. J.C. is supported by the Spanish Ministry of Science and Innovation under the fellowship BES-2017-080364. D.J.N. is the Edmond J. Safra Prof of Neuropsychopharmacology at Imperial College London. G.D. is supported by the Spanish Research Project (ref. PID2019-105772GB-I00 AEI FEDER EU), funded by the Spanish Ministry of Science, Innovation and Universities (MCIU), State Research Agency (AEI) and European Regional Development Funds (FEDER); HBP SGA3 Human Brain Project Specific Grant Agreement 3 (Grant Agreement No. 945539), funded by the EU H2020 FET Flagship program and SGR Research Support Group support (ref. 2017 SGR 1545), funded by the Catalan Agency for Management of University and Research Grants (AGAUR). M.L.K. is supported by the Center for Music in the Brain, funded by the Danish National Research Foundation (DNRF117), and the Centre for Eudaimonia and Human Flourishing, funded by the Pettit and Carlsberg Foundations. EAS is supported by the Stephen Erskine Fellowship from Queens’ College, Cambridge and the Canadian Institute for Advanced Research (L’Institut Canadien de Recherches Avancées; RCZB/072 RG93193). A.K. is supported by the National Institutes of Health (RF1MH123232, R01NS102646 and R21NS104634).
• dc.format.mimetype application/pdf
• dc.identifier.citation Parker Singleton S, Luppi AI, Carhart-Harris RL, Cruzat J, Roseman L, Nutt DJ, Deco G, Kringelbach ML, Stamatakis EA, Kuceyeski A. Receptor-informed network control theory links LSD and psilocybin to a flattening of the brain’s control energy landscape. Nat Commun. 2022;13:5812. DOI: 10.1038/s41467-022-33578-1
• dc.identifier.doi http://dx.doi.org/10.1038/s41467-022-33578-1
• dc.identifier.issn 2041-1723
• dc.identifier.uri http://hdl.handle.net/10230/56052
• dc.language.iso eng
• dc.publisher Nature Research
• dc.relation.ispartof Nature Communications. 2022;13:5812.
• dc.relation.isreferencedby https://openneuro.org/datasets/ds003059/versions/1.0.0
• dc.relation.isreferencedby https://xtra.nru.dk/FS5ht-atlas/
• dc.relation.isreferencedby https://static-content.springer.com/esm/art%3A10.1038%2Fs41467-022-33578-1/MediaObjects/41467_2022_33578_MOESM1_ESM.pdf
• dc.relation.isreferencedby https://static-content.springer.com/esm/art%3A10.1038%2Fs41467-022-33578-1/MediaObjects/41467_2022_33578_MOESM2_ESM.pdf
• dc.relation.isreferencedby https://static-content.springer.com/esm/art%3A10.1038%2Fs41467-022-33578-1/MediaObjects/41467_2022_33578_MOESM3_ESM.pdf
• dc.relation.isreferencedby https://static-content.springer.com/esm/art%3A10.1038%2Fs41467-022-33578-1/MediaObjects/41467_2022_33578_MOESM4_ESM.xlsx
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/945539
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/BES-2017-080364
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2019-105772GB-I00
• dc.rights © Springer Nature Publishing AG https://doi.org/10.1038/s41467-022-33578-1 Creative Commons Attribution Non-Commercial Share Alike
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Functional magnetic resonance imaging
• dc.subject.keyword Network models
• dc.title Receptor-informed network control theory links LSD and psilocybin to a flattening of the brain’s control energy landscape
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion