Developmental changes in diffusion markers of neurite vary across the hippocampus and covary with the cellular composition of hippocampal tissue
Bibliographic record
Abstract
Abstract The hippocampus is a critical brain structure supporting memory encoding and retrieval, yet the development of its microstructure in humans remains unknown. Understanding this development may provide insight into the mechanisms underlying memory and their disruption in disease. To address this, we non-invasively estimated the density and branching complexity of neurite (dendrites, axons, glial processes) using diffusion-weighted MRI in 364 participants aged 8–21. With development, we observed large increases in neurite density and branching complexity that persisted until approximately 15 years of age before stabilizing at adult-like values. Increases in neurite density were relatively homogenous across hippocampal axes, whereas increases in branching complexity were heterogeneous; increasing primarily in CA1, SRLM, subiculum, and anterior hippocampus. To assess whether this development may be attributable to specific cell-types, we tested for spatial overlap between age-related change in neurite and the cell-type composition of hippocampal tissue via cross-reference with an out-of-sample gene-expression atlas. We found age-related changes in neurite density spatially overlapped with a granule cell component; whereas age-related changes in neurite branching complexity overlapped with a pyramidal neuron component. These results provide the first glimpse at the nonlinear maturation of hippocampal microstructure and the cell-type composition of hippocampal tissue underlying these changes.
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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 | 0.001 |
| 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 | 0.000 |
| 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".