Neurobiological Correlates of Psilocybin Response in Depression
Bibliographic record
Abstract
To synthesize the neurobiological basis of brain-resetting effects of psilocybin and identify neuroimaging correlates of psilocybin response in depressed patients. MEDLINE(R), Embase, APA PsycINFO, Cochrane, and CINAHL were systematically searched on June 3, 2022, with no date restrictions using the following string: (psilocybin) AND (psychedelics) AND (MRI) OR (fMRI)) OR (PET)) OR (SPECT)) OR (imaging)) OR (neuroimaging)). After duplicates were removed from 946 studies, 391 studies remained, of which 8 qualified for full-text analysis, but only 5 fulfilled the eligibility criteria of randomized, double-blind, or open-label neuroimaging study with psilocybin treatment in depressed patients. data points included concomitant psychological intervention, modality of neuroimaging technique, changes in depression scores, brain functional changes, and association between functional and psilocybin response. Assessment bias was assessed with the standard risk of bias tool for randomized controlled trials and the tool for risk of bias in nonrandomized studies of interventions. Four studies were open-label, and one was a combined open-label and randomized controlled trial using functional magnetic resonance imaging. Psilocybin-assisted psychotherapy was administered in 3 studies, 1 in refractory and 2 in nonrefractory patients. The remaining 2 studies were in refractory patients. The transient increase in psilocybin-induced global connectivity in major neural tracts and specific areas of brain activation was associated with antidepressant response. Transient functional brain changes with psilocybin therapy resemble the "brain reset" phenomenon and may serve as the putative predictors of psilocybin antidepressant response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".