Joint attention in infants at high familial risk for autism spectrum disorder and the association with thalamic and hippocampal macrostructure
Bibliographic record
Abstract
Abstract Autism spectrum disorder (ASD) is a heritable neurodevelopmental disorder. Infants diagnosed with ASD can show impairments in spontaneous gaze-following and will seldom engage in joint attention (JA). The ability to initiate JA (IJA) can be more significantly impaired than the ability to respond to JA (RJA). In a longitudinal study, 101 infants who had a familial risk for ASD were enrolled (62% males). Participants completed magnetic resonance imaging scans at 4 or 6 months of age. Subcortical volumes (thalamus, hippocampus, amygdala, basal ganglia, ventral diencephalon, and cerebellum) were automatically extracted. Early gaze and JA behaviors were assessed with standardized measures. The majority of infants were IJA nonresponders (n = 93, 92%), and over half were RJA nonresponders (n = 50, 52%). In the nonresponder groups, models testing the association of subcortical volumes with later ASD diagnosis accounted for age, sex, and cerebral volumes. In the nonresponder IJA group, using regression method, the left hippocampus (B = −0.009, aOR = 0.991, P = 0.025), the right thalamus (B = −0.016, aOR = 0.984, P = 0.026), as well as the left thalamus (B = 0.015, aOR = 1.015, P = 0.019), predicted later ASD diagnosis. Alterations in thalamic and hippocampal macrostructure in at-risk infants who do not engage in IJA may reflect an enhanced vulnerability and may be the key predictors of later ASD 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 | 0.001 |
| 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".