Neural representations of anxiety in adolescents with anorexia nervosa: a multivariate approach
Bibliographic record
Abstract
Anorexia nervosa (AN) is characterized by low body weight, fear of gaining weight, and distorted body image. Anxiety may play a role in the formation and course of the illness, especially related to situations involving food, eating, weight, and body image. To understand distributed patterns and consistency of neural responses related to anxiety, we enrolled 25 female adolescents with AN and 22 non-clinical female adolescents with mild anxiety who underwent two fMRI sessions in which they saw personalized anxiety-provoking word stimuli and neutral words. Consistency in brain response patterns across trials was determined using a multivariate representational similarity analysis (RSA) approach within anxiety circuits and in a whole-brain voxel-wise searchlight analysis. In the AN group there was higher representational similarity for anxiety-provoking compared with neutral stimuli predominantly in prefrontal regions including the frontal pole, medial prefrontal cortex, dorsolateral prefrontal cortex, and medial orbitofrontal cortex, although no significant group differences. Severity of anxiety correlated with consistency of brain responses within anxiety circuits and in cortical and subcortical regions including the frontal pole, middle frontal gyrus, orbitofrontal cortex, thalamus, lateral occipital cortex, middle temporal gyrus, and cerebellum. Higher consistency of activation in those with more severe anxiety symptoms suggests the possibility of a greater degree of conditioned brain responses evoked by personally-relevant emotional stimuli. Anxiety elicited by disorder-related stimuli may activate stereotyped, previously-learned neural responses within- and outside of classical anxiety circuits. Results have implications for understanding consistent and automatic responding to environmental stimuli that may play a role in maintenance of AN.
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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 | 0.001 | 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".