Volumetric analysis of medial temporal lobe subregions in developmental amnesia using high‐resolution magnetic resonance imaging
Bibliographic record
Abstract
There is great interest in the cognitive consequences of hippocampal volume loss in developmental amnesia (DA). In many DA cases, volume loss occurs before the hippocampus is fully developed, and yet little is known about the locus, extent, and distribution of damage in these cases. We used high-resolution MRI to manually segment the medial temporal lobe (MTL) subregions in H.C., an adult with DA, and a group of sex-, age- and education-matched control participants (n = 10). The hippocampus was defined and divided into anterior (head) and posterior (body and tail) segments. Within the body of the hippocampus, the subregions (CA1 , DG/CA2/3 , and subiculum) were defined. Finally, the entorhinal (ERC), perirhinal (PRC), and parahippocampal (PHC) cortices were segmented. Anterior hippocampus was reduced bilaterally and posterior hippocampus was significantly reduced on the right. In the body of the hippocampus, all three subregions were reduced in the left hemisphere, whereas CA1 and subiculum were reduced in the right hemisphere. No group differences were observed in the PRC and ERC, whereas left PHC volume was marginally increased in H.C. compared to controls. These results can be used to inform patterns of spared and impaired cognitive abilities in DA and perhaps in amnesia more generally.
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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 | 0.001 | 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".