Subregional analysis of the amygdala, thalamus, and hypothalamus at the pre-decline stage in Parkinson’s disease with later cognitive impairment
Bibliographic record
Abstract
Cognitive decline in Parkinson's disease (PD) significantly impacts patients' quality of life, yet early detection remains challenging. While structural brain abnormalities in cortical regions have been widely documented using magnetic resonance imaging (MRI), subcortical regions have received less analytical attention despite their potential role as early biomarkers. This study investigated changes in specific subregions of the amygdala, thalamus, and hypothalamus in patients with PD before cognitive decline development. We analyzed MRI data from 163 participants (97 healthy controls [HC] and 66 patients with PD) from the Parkinson's Progression Markers Initiative database. The patients with PD were classified based on cognitive status during a four-year follow-up: 21 who developed cognitive impairment (PDCI) and 45 who maintained normal cognition (PDNC). Cognitive function was assessed using the Montreal Cognitive Assessment and domain-specific tests. The PDCI group showed significantly lower corrected brain volumes in specific subregions of the amygdala (left basal nucleus), thalamus (bilateral lateral geniculate nuclei, right medial dorsal nucleus, and right anterior pulvinar nucleus), and hypothalamus (bilateral anterior-superior and left superior tubular parts) compared to that of HC. A significant difference between the PDCI and PDNC groups was observed only in the left lateral geniculate nucleus. In contrast, widespread structural changes were observed in cortical regions in the PDCI group, which showed stronger correlations with memory, attention, executive function, and visuospatial abilities. Hazard ratio analysis confirmed that structural changes in multiple cortical regions were significant predictors of cognitive decline. Although structural alterations were observed in subcortical regions, cortical changes demonstrated stronger associations with cognitive decline. These findings suggest that structural abnormalities may appear in the cerebral cortex before the stage proposed by conventional α-synuclein propagation models, potentially involving multiple mechanisms beyond α-synuclein, including global neural circuit dysfunction, disruption of neurotransmitter systems, breakdown of compensatory mechanisms, and coexisting pathologies (beta-amyloid and tau proteins). This study provides insights into early brain changes in PD and emphasizes the need for a comprehensive approach considering multiple mechanisms in early diagnosis and intervention strategies for PD-related cognitive impairment.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".