Uncovering the Neuroanatomical Signature of the Transition from Normal Cognition to Mild Cognitive Impairment in Parkinson's Disease: A VBM and Brain Age Estimation Study
Bibliographic record
Abstract
Abstract The progression of Parkinson’s disease (PD) is often accompanied by cognitive decline. This study aims to uncover neuroanatomical indicators of the transition from healthful cognition to mild cognitive impairment (MCI) in PD using brain age estimation methodologies and structural neuroimaging data. Structural MRI data for 244 subjects from the Parkinson Progression Markers Initiative (PPMI) was acquired. 192 of these were PD patients with stable healthy cognitive function from baseline out to 5 years (PD-SHC), and as the remaining 52 were PD patients who had unstable healthy cognition and developed MCI within 5 years (PD-UHC). We conducted voxel-based morphometry (VBM), deformation-based morphometry, and cortical thickness analyses to measure structural brain differences between these groups at baseline and to assess any differences in brain aging. The VBM analysis revealed that PD-SHC patients have larger grey matter volumes compared to PD-UHC subjects at baseline. This difference was located entirely within the cerebellum with significant clusters found within the posterior and anterior lobes and on the declive and culmen regions of the vermis. No differences were observed in the white matter, local brain tissue volumetry or cortical thickness measurements between the two groups. At baseline, PD-UHC patients exhibited significantly greater brain aging than PD-SHC patients (mean difference = 3.24 years, Cohen’s d = 0.43; t(242) = 2.78, p = 0.005). Our analysis provides an in-depth understanding of the neuroanatomical signatures of cognitive decline in PD by demonstrating the role of the cerebellum as a site of early anatomical change that accompanies the transition from healthy cognition to MCI. This could aid in elucidating further changes along the structural-functional continuum which accompany this cognitive transition, serve as a biomarker of the earliest form of cognitive decline in patients with PD and enrich trials of cognitive intervention in this patient population.
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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 | 0.001 |
| 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".