Volumetric, shape and microstructural alterations of the hippocampal subfields in healthy aging
Bibliographic record
Abstract
Abstract Background Although several volumetric studies have attempted to examine the relationship between hippocampal subfields and age, their findings are heterogenous. Here, in addition to typical volumetric measures, we investigated age‐related alterations of hippocampal subfield shape and microstructure. Method The present work included 161 healthy participants (ages 18‐81) recruited as part of two local datasets. Standard T1‐weighted (T1w; MPRAGE sequence, 1 mm3 voxels) and high‐resolution T2‐weighted (T2w, 0.64 mm3 voxels) magnetic resonance images were acquired. The minc‐bpipe‐library pipeline (https://github.com/CobraLab/minc‐bpipe‐library) was used to preprocess images. The MAGeT‐Brain algorithm (Pipitone et al., 2014) was utilized for segmentation of the hippocampal subfields (Amaral et al., 2016). The volume and shape (i.e. surface area [SA] and displacement) of the grey matter (GM) subfields (i.e. Cornus Ammonis [CA]1, CA2CA3, CA4 and dentate gyrus [CA4DG], stratum radiatum/lacunosum/moleculare and subiculum) and the volume of associated white matter (WM) regions (i.e. fimbria, fornix, alveus and mammillary bodies [MB]) were estimated using T1w images. Mean T1w/T2w signal intensity ratio (Glasser & Van Essen, 2011) of each subfield was calculated to examine microstructural alterations sensitive to myelin. Linear‐mixed effects models and Akaike information criterion were used to select the most appropriate age relationships from multiple fits (i.e. linear, quadratic, and cubic) for each structure of interest. Sex and ipsilateral hippocampal GM or WM volume were included as covariates. Statistical analyses were performed in R 3.5.0; comparisons surviving p<0.05 (Bonferroni‐corrected) were reported. Result Right CA1 and alveus volumes were positively cubically related to age and bilateral CA4DG volumes were negatively linearly related to age. T1w/T2w intensity linearly decreased with age for all subregions except for bilateral fornix and MB, which expressed quadratic evolution with age (Figures 1‐2). Age was also inversely related to bilateral SA reduction in the head and medial‐posterior hippocampus, and lateral outward and medial inward displacement (Figure 3). Conclusion The current work suggests that certain subfields of the hippocampus are more (e.g. CA1) or less (e.g. CA4DG) preserved in healthy aging. These differences do not appear to be explained by microstructural variation.
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 | 0.001 | 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) | 0.002 | 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".