Age-related patterns of resting EEG power in infancy: Associations with prenatal socioeconomic disadvantage
Bibliographic record
Abstract
The brain develops rapidly during the prenatal period and first two years of life, making it particularly sensitive to environmental influences. Family socioeconomic disadvantage is one environmental factor that may shape the development of brain function in infancy. However, it is unclear how brain function changes across infancy or whether prenatal family socioeconomic disadvantage is associated with age-related differences in brain function during this period. Here, we examine whether resting electroencephalography (EEG) power (theta, alpha, beta, and gamma) shows linear and/or non-linear age-related patterns across four assessments from 1 to 18 months of age (N = 165), and whether these patterns are moderated by prenatal family socioeconomic disadvantage. We find that lower-frequency (relative theta) and higher-frequency (relative alpha, beta, and gamma) power show non-linear age-related patterns during the first 18 months of life. Prenatal family socioeconomic disadvantage moderates these patterns, such that infants from lower-income families show less steep age-related decreases in lower-frequency (relative theta) power and less steep increases in higher-frequency (relative beta) power. These associations hold when adjusting for other prenatal and postnatal experiences, as well as infant demographic and health-related factors. These data suggest that lower prenatal family income is associated with age-related differences in brain function during infancy.
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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 | 0.000 | 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) | 0.001 | 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".