KIBRA Polymorphism Is Associated with Individual Differences in Hippocampal Subregions: Evidence from Anatomical Segmentation using High-Resolution MRI
Bibliographic record
Abstract
The KIBRA gene has been associated with episodic memory in several recent reports; carriers of the T-allele show enhanced episodic memory performance relative to noncarriers. Gene expression studies in human and rodent species show high levels of KIBRA in the hippocampus, particularly in the subfields. The goal of the present study was to determine whether the KIBRA C→T polymorphism is also associated with volume differences in the human hippocampus and whether specific subfields are differentially affected by KIBRA genotype. High-resolution magnetic resonance imaging (T2-weighted, voxel size=0.4×0.4 mm, in-plane) was used to manually segment hippocampal cornu ammonis (CA) subfields, dentate gyrus (DG), and the subiculum as well as adjacent medial temporal lobe cortices in healthy carriers and noncarriers of the KIBRA T-allele (rs17070145). Overall, we found that T-carriers had a larger hippocampal volume relative to noncarriers. The structural differences observed were specific to the CA fields and DG regions of the hippocampus, suggesting a potential neural mechanism for the effects of KIBRA on episodic memory performance reported previously.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".