Gray matter atrophy in patients with mild cognitive impairment/Alzheimer's disease over the course of developing delusions
Bibliographic record
Abstract
OBJECTIVE: We conducted a neuroimaging analysis to understand the neuroanatomical correlates of gray matter loss in a group of mild cognitive impairment and early Alzheimer's disease patients who developed delusions. METHODS: With data collected as part of the Alzheimer's Disease Neuroimaging Initiative, we conducted voxel-based morphometry to determine areas of gray matter change in the same Alzheimer's Disease Neuroimaging Initiative participants, before and after they developed delusions. RESULTS: We identified 14 voxel clusters with significant gray matter decrease in patient scans post-delusional onset, correcting for multiple comparisons (false discovery rate, p < 0.05). Major areas of difference included the right and left insulae, left precuneus, the right and left cerebellar culmen, the left superior temporal gyrus, the right posterior cingulate, the right thalamus, and the left parahippocampal gyrus. CONCLUSIONS: Although contrary to our initial predictions of enhanced right frontal atrophy, our preliminary work identifies several neuroanatomical areas, including the cerebellum and left posterior hemisphere, which may be involved in delusional development in these patients.
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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 | 0.001 | 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".