Perinatal environmental enrichment affects murine neonates’ brain structure before their active engagement with environment
Bibliographic record
Abstract
Abstract Early life experiences shape individuals. Environmental enrichment, an experimental paradigm used to study the effect of increased environmental complexity and novelty in animal models, has long been recognised for its broad effect on nervous system function and behaviour. In adult rodents, structural changes in the brain due to enriched environments are well documented, notably in the hippocampus. However, the effect of environmental enrichment on the developing brain during early life is not well understood. This study aims to investigate how environmental enrichment affects brain development during the critical perinatal period, and how such effects compare to those observed during adulthood. We use high-resolution MRI to measure the brain structure of mouse neonates at postnatal day 7, born either in an enriched or a standard environment. We show that rodents exhibit brain structure differences as early as postnatal day 7. However, the regional changes observed differ from those in adulthood: hippocampal changes are limited, but changes in the hindbrain, the dorsal striatum, and the medial habenula are strong. Given the lack of direct interaction between neonates and the environment at P7, we hypothesised that maternal care may mediate these effects. We show that maternal care differs between enriched and standard environments, that maternal care correlates with brain structure changes in the neonates, and that maternal care and enriched environment affect brain structure similarly. This suggests that early changes in brain structure due to environmental enrichment are at least partly mediated by maternal care. This study provides novel insight into the differential effect of enriched environment on early brain development in rodents.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".