Callosal Atrophy Correlates with Temporal Lobe Volume and Mental Status in Alzheimer's Disease
Bibliographic record
Abstract
BACKGROUND: Recent studies have reported significant atrophy of the corpus callosum (CC) in Alzheimer's Disease (AD). However, it is currently unknown whether CC atrophy is associated with specific cortical volume changes in AD. Moreover, possible atrophy in extra-callosal commissures has not been examined to date. The purpose of the present study was to quantify atrophy in two cerebral commissures [the CC and the anterior commissure (AC)], to correlate this measure with cognitive status, and to relate commissural size to independent measures of temporal lobe volume in AD patients. METHODS: A sample of AD patients and of age- and education-matched normal control subjects (NCs) underwent MRI and a cognitive test battery including the Dementia Rating Scale and Mini Mental State examination. Mid-sagittal regional areas within CC and AC were measured along with superior, middle and inferior temporal lobes volumes. RESULTS: Alzheimer's Disease patients had significantly smaller callosa than did NCs. The callosal regions most affected in AD included the midbody, isthmus and genu. The isthmus and midbody areas of the CC were positively correlated with cognitive performance and with superior temporal lobe volume in AD patients. The mid-sagittal area of the AC and the superior temporal volumes did not differ between AD patients and NCs. CONCLUSIONS: The study demonstrated that the regional morphology of the CC correlates with current cognitive status and temporal lobe atrophy in AD. As well, the lack of difference for the AC suggests that commissural atrophy in AD is regionally specific.
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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".