Grey Matter Atrophy in Mild Cognitive Impairment / Early Alzheimer Disease Associated with Delusions: A Voxel-Based Morphometry Study
Bibliographic record
Abstract
OBJECTIVES: Grey matter atrophy in the right hemisphere has been shown to be more severe in dementia patients with delusions, suggesting a neuroanatomical localization that may be pertinent to impending neurodegeneration. Delusional symptoms may arise when atrophy in these areas reduces the regulatory functions of the right hemisphere, in tandem with asymmetric neuropathology in the left hemisphere. We hypothesized that delusional patients with either amnestic mild cognitive impairment (MCI) or early Alzheimer Disease (AD) would experience more pronounced grey matter atrophy in the right frontal lobe compared with matched patients without delusions. METHODS: We used neuroimaging and clinical data obtained from the Alzheimer's Disease Neuroimaging Initiative. A comparison group of twenty-nine nondelusional MCI/early AD participants were compared with twenty-nine delusional participants using voxel-based morphometry, matched at baseline by age, sex, education, and Mini-Mental State Exam score. All included participants were diagnosed with amnestic MCI at study baseline. RESULTS: Fifteen voxel clusters of decreased grey matter in participants with delusions were detected. Prominent grey matter decrease was observed in the right precentral gyrus, right inferior frontal gyrus, right insula, and left middle occipital gyrus, areas that may be involved in control of thought and emotions. CONCLUSION: Greater right fronto-temporal grey matter atrophy was observed in MCI or early AD participants with delusions compared to matched patients without delusions. Consistent with our predictions, asymmetric grey matter atrophy in the right hemisphere may contribute to development of delusions through loss of executive inhibition.
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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".