Impaired social attention detected through eye movements in children with early‐onset epilepsy
Bibliographic record
Abstract
OBJECTIVES: Children with early-onset epilepsy (CWEOE; epilepsy onset before 5 years) exhibit impaired social functioning, but social attention has not yet been examined. In this study we sought to explore visual attention via eye tracking as a component of social attention and examine its relationship with social functioning and Autism Spectrum Disorder (ASD) risk scores. METHODS: Forty-seven CWEOE (3-63 months) and 41 controls (3-61 months) completed two eye-tracking tasks: (1) preference for social versus nonsocial naturalistic scenes, and (2) face region preference task. ASD risk was measured via the Modified Checklist for Autism in Toddlers or Conners Early Childhood Total Score. Social functioning was assessed via the Greenspan Social-Emotional Growth Chart, or Infant-Toddler Social & Emotional Assessment Competence Scale, or Conners Early Childhood Social Functioning Scale, depending on age. Fixation preferences for social scenes and eyes were compared between groups and evaluated by age and social functioning scores. RESULTS: Regression analysis revealed that CWEOE viewed the social scene to a significantly less degree than controls. The greatest difference was found between the youngest CWEOE and controls. Fixation duration was independently and significantly related to social functioning scores. There were no significant differences between CWEOE and controls in the face scanning task, and there was no significant relationship between either task and ASD risk scores. SIGNIFICANCE: CWEOE exhibit task-specific atypical social attention early in the course of the disease. This may be an early marker of impaired social development, and it suggests abnormal social brain development.
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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 | 0.002 |
| 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 | 0.001 |
| 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".