Alterations in brain network connectivity and subjective experience induced by psychedelics: a scoping review
Bibliographic record
Abstract
Intense interest surrounds current research on psychedelics, particularly regarding their potential in treating mental health disorders. Various studies suggest a link between the subjective effects produced by psychedelics and their therapeutic efficacy. Neuroimaging evidence indicates an association of changes in brain functional connectivity with the subjective effects of psychedelics. We conducted a review focusing on psychedelics and brain functional connectivity. The review focused on four psychedelic drugs: ayahuasca, psilocybin and LSD, and the entactogen MDMA. We conducted searches in databases of MEDLINE, Embase, APA PsycInfo and Scopus from inception to Jun 2023 by keywords related to functional connectivity and psychedelics. Using the PRISMA framework, we selected 24 articles from an initial pool of 492 for analysis. This scoping review and analysis investigated the effects of psychedelics on subjective experiences and brain functional connectivity in healthy individuals. The studies quantified subjective effects through psychometric scales, revealing significant experiences of altered consciousness, mood elevation, and mystical experiences induced by psychedelics. Neuroimaging results indicated alterations in the functional connectivity of psychedelics, with consistent findings across substances of decreased connectivity within the default mode network and increased sensory and thalamocortical connectivity. Correlations between these neurophysiological changes and subjective experiences were noted, suggesting a brain network basis of the psychedelics' neuropsychological impact. While the result of the review provides a potential neural mechanism of the subjective effects of psychedelics, direct clinical evidence is needed to advance their clinical outcomes. Our research serves as a foundation for further exploration of the therapeutic potential of psychedelics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".