The Psychedelic Reset: How Psychedelics May Reshape the Corticostriatal Circuit in Anorexia Nervosa
Bibliographic record
Abstract
Anorexia nervosa (AN) is an eating disorder characterized by compulsive eating restrictions and cognitive inflexibility, which is linked to dysregulation within the cortico-striatal-thalamo cortical (CSTC) circuitry. Dysfunction within the dorsolateral prefrontal cortex and dorsal striatum has been implicated in habitual decision making and impaired cognitive flexibility, contributing to disordered eating patterns. Neuroimaging studies show that dysregulation in the CSTC circuitry reinforces maladaptive behaviours, making it difficult for individuals with AN to withdraw from rigid eating habits and habitual behaviours. Current treatment options, such as cognitive behavioural therapy and pharmacological interventions, are ineffective in targeting underlying neural dysfunctions. Recent research suggests the efficacy of psychedelics such as psilocybin in modulating cortico-striatal function to alleviate symptoms of AN. Animal studies and human trials provide strong evidence for the positive effects of psilocybin therapy on improving rigid behavioural patterns, which restores goal-directed control over eating habits. Psilocybin regulates activity within the CSTC circuitry, promoting cognitive flexibility and disrupting maladaptive decision-making associated with AN. Psychedelics show strong therapeutic potential for treating eating disorders by restoring functional connectivity in CSTC circuits and facilitating the shift from habit-driven to goal-directed behaviour. This poster explores how psychedelics may effectively target cortico-striatal dysfunction to promote behavioural change in individuals with AN. Future research should examine the long-term therapeutic effects of psilocybin in humans to differentiate if positive impact is due to neural changes or emotional experiences.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".