Early life stress impairs hippocampal subfield myelination
Bibliographic record
Abstract
The hippocampus is an archicortical structure that is highly sensitive to experience and is made up of individual subfields. These subfields, crucial for learning and memory, rapidly develop and are vulnerable to early stress, yet the mechanisms are unknown. Here, we analyse data from 520 neonates born between 23 and 42 weeks' gestation to assess how early extrauterine exposure-related stress influences subfield maturation. Subfields are segmented automatically by training a U-net model on infant data using HippUnfold, a novel tool for subfield segmentation. Results indicate that subfield volumes are resilient to early stress, while myelination shows greater vulnerability and variation, which may contribute to long-term outcomes. Notably, subfields are not uniformly impacted by stress, with CA1 and CA2 showing the largest effects. Developmental context, including time spent in and ex utero, primarily influences hippocampal subfield myelination.
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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 | 0.000 | 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".