Non-linear effects of socioeconomic status on brain development: associations between parental occupation, cortical thickness and language skills in childhood and adolescence
Bibliographic record
Abstract
Abstract Studies have pointed to the role of the brain in mediating the effects of the social environment of the developing child on life outcomes. Since brain development involves nonlinear trajectories, these effects of the child’s social context will likely have age-related differential associations with the brain. However, there is still a dearth of integrative research investigating the interplay between neurodevelopmental trajectories, social milieu and life outcomes. We set out to fill this gap, focusing specifically on the role of socioeconomic status, SES (indexed by parental occupation) on brain and cognitive development by analyzing MRI scans from 757 typically-developing subjects (age = 3-21 years). We observed nonlinear interaction of age and SES on cortical thickness, specifically a significant positive association between SES and thickness around 9-13 years at several cortical regions. Using a moderated mediation model, we observed that cortical thickness mediated the link between SES and language abilities, and this mediation was moderated by ‘age’ in a quadratic pattern, indicating a pronounced SES-effect during early adolescence. Our results, drawn from cross-sectional data, provide a basis for further longitudinal studies to test whether early adolescence may be a sensitive time window for the impact of SES on brain and cognitive 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 | 0.001 | 0.002 |
| 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".