Neuropsychiatric symptoms and brain morphology in patients with mild cognitive impairment, cerebrovascular disease and Parkinson disease: A cross sectional and longitudinal study
Bibliographic record
Abstract
OBJECTIVES: Neuropsychiatric symptoms (NPS) increase risk of developing dementia and are linked to various neurodegenerative conditions, including mild cognitive impairment (MCI due to Alzheimer's disease [AD]), cerebrovascular disease (CVD), and Parkinson's disease (PD). We explored the structural neural correlates of NPS cross-sectionally and longitudinally across various neurodegenerative diagnoses. METHODS: The study included individuals with MCI due to AD, (n = 74), CVD (n = 143), and PD (n = 137) at baseline, and at 2-years follow-up (MCI due to AD, n = 37, CVD n = 103, and PD n = 84). We assessed the severity of NPS using the Neuropsychiatric Inventory Questionnaire. For brain structure we included cortical thickness and subcortical volume of predefined regions of interest associated with corticolimbic and frontal-executive circuits. RESULTS: Cross-sectional analysis revealed significant negative correlations between appetite with both circuits in the MCI and CVD groups, while apathy was associated with these circuits in both the MCI and PD groups. Longitudinally, changes in apathy scores in the MCI group were negatively linked to the changes of the frontal-executive circuit. In the CVD group, changes in agitation and nighttime behavior were negatively associated with the corticolimbic and frontal-executive circuits, respectively. In the PD group, changes in disinhibition and apathy were positively associated with the corticolimbic and frontal-executive circuits, respectively. CONCLUSIONS: The observed correlations suggest that underlying pathological changes in the brain may contribute to alterations in neural activity associated with MBI. Notably, the difference between cross-sectional and longitudinal results indicates the necessity of conducting longitudinal studies for reproducible findings and drawing robust inferences.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".