Early environmental influences on the development of children's brain structure and function
Bibliographic record
Abstract
The developing brain in utero and during the first years of life is highly vulnerable to environmental influences. Experiences occurring during this period permanently modify brain structure and function through epigenetic modifications (alterations of the DNA structure and chromatin function) and consequently affect the susceptibility to mental disorders. In this review, we describe evidence linking adverse environmental variation during early life (from the fetal period to childhood) and long-term changes in brain volume, microstructure, and connectivity, especially in amygdala and hippocampal regions. We also describe genetic variations that moderate the impact of adverse environmental conditions on child neurodevelopment, such as polymorphisms in brain-derived neurotrophic factor and catechol-O-methyltransferase genes, as well as genetic pathways related to glutamate and monoaminergic signaling. Lastly, we have depicted positive early life experiences that could benefit childhood neurodevelopment and reverse some detrimental effects of adversity in the offspring. WHAT THIS PAPER ADDS: Prenatal, peripartum, and postnatal adversities influence child behavior and neurodevelopment. Exposure to environmental enrichment and positive influences may revert these effects. Putative mechanisms involve alterations in neurotrophic factors and neurotransmitter systems. New tools/big data improved the understanding on how early adversity alters neurodevelopment. This permits better translation/application of the findings from animal models to humans.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".