Evaluation of Enhanced Attention to Local Detail in Anorexia Nervosa Using the Embedded Figures Test; an fMRI Study
Bibliographic record
Abstract
The behavioural literature in anorexia nervosa and autism spectrum disorders has indicated an overlap in cognitive profiles. One such domain is the enhancement of local processing over global processing. While functional imaging studies of autism spectrum disorder have revealed differential neural patterns compared to controls in response to tests of local versus global processing, no studies have explored such effects in anorexia nervosa. This study uses functional magnetic resonance imaging in conjunction with the embedded figures test, to explore the neural correlates of this enhanced attention to detail in the largest anorexia nervosa cohort to date. On the embedded figures tests participants are required to indicate which of two complex figures contains a simple geometrical shape. The findings indicate that whilst healthy controls showed greater accuracy on the task than people with anorexia nervosa, different brain regions were recruited. Healthy controls showed greater activation in the precuneus whilst people with anorexia nervosa showed greater activation in the fusiform gyrus. This suggests that different cognitive strategies were used to perform the task, i.e. healthy controls demonstrated greater emphasis on visuospatial searching and people with anorexia nervosa employed a more object recognition-based approach. This is in accordance with previous findings in autism spectrum disorder using a similar methodology and has implications for therapies addressing the appropriate adjustment of cognitive strategies in anorexia nervosa.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".