The Impact of Parent–Child Interaction on Brain Structures: Cross-sectional and Longitudinal Analyses
Bibliographic record
Abstract
There is a vast amount of evidence from psychological studies that the amount of parent-child interaction affects the development of children's verbal skills and knowledge. However, despite the vast amount of literature, brain structural development associated with the amount of parent-child interaction has never been investigated. In the present human study, we used voxel-based morphometry to measure regional gray matter density (rGMD) and examined cross-sectional correlations between the amount of time spent with parents and rGMD among 127 boys and 135 girls. We also assessed correlations between the amount of time spent with parents and longitudinal changes that occurred a few years later among 106 boys and 102 girls. After correcting for confounding factors, we found negative effects of spending time with parents on rGMD in areas in the bilateral superior temporal gyrus (STG) via cross-sectional analyses as well as in the contingent areas of the right STG. We also confirmed positive effects of spending time with parents on the Verbal Comprehension score in cross-sectional and longitudinal analyses. rGMD in partly overlapping or contingent areas of the right STG was negatively correlated with age and the Verbal Comprehension score in cross-sectional analyses. Subsequent analyses revealed verbal parent-child interactions have similar effects on Verbal Comprehension scores and rGMD in the right STG in both cross-sectional and longitudinal analyses. These findings indicate that parent-child interactions affect the right STG, which may be associated with verbal skills.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".