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Record W4411642243 · doi:10.1101/2025.06.24.25330245

Psilocybin Modulates TPJ Effective Connectivity during Out-of-Body Experiences

2025· preprint· en· W4411642243 on OpenAlexaff
Devon Stoliker, Fosco Bernasconi, Olaf Blanke, Adeel Razi

Bibliographic record

VenuemedRxiv · 2025
Typepreprint
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsCanadian Institute for Advanced Research
FundersNational Health and Medical Research CouncilMedical Research Council
KeywordsPsilocybinHallucinogenPsychologyFunctional connectivityCognitive psychologyNeurosciencePsychiatry

Abstract

fetched live from OpenAlex

Abstract Serotonergic psychedelics alter self-boundaries and can induce out-of-body experiences (OBEs)—the sense of being located outside one’s physical body. While OBEs also occur in clinical conditions and can be experimentally induced, their neural basis under psychedelics remains underexplored. In an open-label, baseline-controlled MRI study of 62 healthy adults administered psilocybin, we examined effective connectivity changes in regions implicated in clinical and induced OBEs. Spectral dynamic causal modelling (spDCM) was applied to resting-state and music-listening scans to estimate connectivity changes from baseline and assess their consistency across contexts. Participants were grouped by self-reported OBE symptom intensity at the end of the dosing day. In those reporting high-intensity OBEs, psilocybin reduced effective connectivity from the right to left anterior insula and between the right anterior insula and right temporoparietal junction (TPJ), inhibiting these connections across both scan types. These changes parallel known disruptions in TPJ–insula circuits linked to OBEs in clinical and experimental settings, particularly in the right hemisphere. Our findings highlight how psilocybin-induced disembodiment corresponds to altered effective connectivity and demonstrate the utility of spDCM for mapping causal neural dynamics underlying bodily self-consciousness.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.355
Teacher spread0.325 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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