White matter tracts characteristics in habitual decision-making circuit underlie ritual behaviors in anorexia nervosa
Bibliographic record
Abstract
Anorexia nervosa (AN) is a difficult to treat, pernicious psychiatric disorder that has been linked to decision-making abnormalities. We examined the structural characteristics of habitual and goal-directed decision-making circuits and their connecting white matter tracts in 32 AN and 43 healthy controls across two independent data sets of adults and adolescents as an explanatory sub-study. Total bilateral premotor/supplementary motor area-putamen tracts in the habit circuit had a significantly higher volume in adults with AN, relative to controls. Positive correlations were found between both the number of tracts and white matter volume (WMV) in the habit circuit, and the severity of ritualistic/compulsive behaviors in adults and adolescents with AN. Moreover, we found a significant influence of the habit circuit WMV on AN ritualistic/compulsive symptom severity, depending on the preoccupations symptom severity levels. These findings suggest that AN is associated with white matter plasticity alterations in the habit circuit. The association between characteristics of habit circuit white matter tracts and AN behavioral symptoms provides support for a circuit based neurobiological model of AN, and identifies the habit circuit as a focus for further investigation to aid in development of novel and more effective treatments based on brain-behavior relationships.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".