Hippocampal grey matter changes across scales in Alzheimer’s Disease
Bibliographic record
Abstract
Alzheimer's disease (AD) is a progressive and debilitating neurodegenerative disease of the central nervous system, characterized by deterioration in cognitive function including extensive memory impairment. The hippocampus, a medial temporal lobe region, is a key orchestrator in the encoding and retrieval of memory and is believed to be one of the first regions to deteriorate in AD. In this work we examined hippocampal macrostructure (specifically gyrification and thickness) and microstructure in Alzheimer's disease (AD) and mild cognitive impairment (MCI) relative to healthy aged controls in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. We first utilized an iterative training paradigm to adapt an existing deep learning approach for capturing hippocampal topology to elderly individuals as well as individuals with potential hippocampal degeneration. Using this new model, we found notable decreases in both thickness and gyrification in AD and MCI across both the subfields and anterior-posterior axis. Using the diffusion tensor representation derived from diffusion MRI data, we found significant increases in the mean diffusivity across the extent of the hippocampus in AD and MCI, which may be related to a number of changes such as loss of neuronal cells, decreased fiber density, demyelination, and increased presence of CSF. Examining the primary direction of diffusion relative to canonical hippocampal axes, we found distinct diffusion orientation shifts in AD and MCI throughout the anterior-posterior extent of the subiculum and CA1. Specifically, we found a decrease in diffusion oriented tangentially, and an increase in diffusion oriented along the long-axis. This could potentially be related to the known degeneration of the perforant path, which is greatly affected in AD and is a largely tangential oriented pathway. The AD-related changes in diffusion orientations were found to not have significant spatial overlap with AD-related changes in mean diffusivity, suggesting that they may be capturing distinct spatially-localized disease processes. Finally, we showed that the macro- and microstructure of the hippocampus in AD changed less across age relative to MCI and controls. As well, the age-related hippocampal macrostructure changes in MCI appeared indistinguishable from healthy aging.
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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".