Exploring the neurobiological correlates of psilocybin-assisted psychotherapy in eating disorders: a review of potential methodologies and implications for the psychedelic study design
Bibliographic record
Abstract
Eating disorders (EDs) are a group of debilitating mental illnesses characterized by maladaptive eating behaviors and severe cognitive-emotional dysfunction, directly affecting 1–3% of the population. Standard treatments are not effective in approximately one third of ED cases, representing the need for scientific advancement. There is emerging evidence for the safety and efficacy of psilocybin-assisted psychotherapy (PAP) to improve treatment outcomes in individuals with EDs. However, the limited knowledge of the neurobiological mechanisms underlying the therapeutic effects of PAP restricts the ability to confirm its clinical utility. This narrative review presents an overview of methodologies used to elucidate the pathophysiological mechanisms of EDs or the effects of psilocybin that could be employed to probe the neurobiological correlates of PAP in EDs, including magnetic resonance imaging and molecular neuroimaging techniques, electrophysiological approaches, and neuroplasticity markers. Finally, the implications of these methodologies are described in relation to the unique features of the psychedelic study design, challenges, limitations, and future directions to advance the field. This paper represents a valuable resource for scientists during study conceptualization and design phases and stimulates advancement in the identification of effective therapeutic interventions for EDs. Eating disorders (EDs) are serious mental health conditions that impact eating behaviors, thoughts, and emotions, directly affecting up to 3% of people worldwide. Current treatments are not effective in about one third of cases, highlighting the need for new approaches. Psilocybin-assisted psychotherapy (PAP) is an emerging treatment option that shows promise for improving outcomes in people with EDs. However, there is a lack of understanding for the mechanisms in which PAP may support recovery, making it difficult to confirm its benefits. This review presents several research methods that could help uncover how PAP influences the brain in EDs, including neuroimaging approaches and neuroplasticity markers. The challenges of incorporating these methods into the psychedelic study design and future research directions are also discussed. Together, this review presents a valuable resource for scientists and stimulates advancements in the development of more effective treatments for EDs.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".