Socioeconomic status and hippocampal volume in children and young adults
Bibliographic record
Abstract
An individual's socioeconomic status (SES) is often viewed as a proxy for a host of environmental influences. SES disparities have been linked to variance in brain structures particularly the hippocampus, a neural substrate of learning and memory. However, it is unclear whether the association between SES and hippocampal volume is similar in children and adults. We investigated the relationship between hippocampal volume and SES in a group of children (n = 31, age 8-12 years) and a group of young adults (n = 32, age 18-25 years). SES was assessed with four indicators that loaded on a single factor, therefore a composite SES scores was used in the main analyses. Hippocampal volume was measured using manual demarcation on high resolution structural images. SES was associated with hippocampal volume in the children, but not in adults, suggesting that in childhood, but not adulthood, SES-related environmental factors influence hippocampal volume. In addition, hippocampal volume, but not SES, was associated with scores on a memory task, suggesting that net effects of postnatal environmental factors, captured by SES, are more distal determinants of memory performance than hippocampal volume. Longitudinal investigation of the association between SES, hippocampal volume and cognitive functioning may further our understanding of the putative neural mechanisms underlying SES-related environmental effects on cognitive development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.001 | 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".