Exploring cognitive and emotional symptoms associated with hippocampal subfield atrophy in drug-induced Parkinsonism
Bibliographic record
Abstract
Background: Drug-induced Parkinsonism (DIP) is a secondary Parkinsonism with limited research on its hippocampal structural changes. This study explores hippocampal subfield volumes in DIP compared to Parkinson's disease (PD) and healthy controls (HCs), investigating correlations with cognitive (Montreal Cognitive Assessment, MoCA), emotional (Hamilton Depression Rating Scale, HAMD; Hamilton Anxiety Rating Scale, HAMA), and motor (Unified Parkinson's Disease Rating Scale, UPDRS) symptoms. Methods: A total of 19 DIP patients, 20 PD patients, and 20 HCs were enrolled. MRI-based hippocampal subfield volumes were assessed using FreeSurfer, and clinical scores were evaluated for cognitive, emotional, and motor functions. Statistical analyses compared group differences and examined correlations. Results: Significant atrophy was observed in the DIP group in multiple hippocampal subfields compared to HCs, including the presubiculum, subiculum, Granule cell and molecular layer of the dentate gyrus (GC-ML-DG), molecular_layer_HP, Cornu ammonis (CA) 1, CA4, hippocampal tail, and fimbria. MoCA scores positively correlated with volumes in bilateral hippocampus and subfields such as subiculum and CA4, while HAMD scores mainly showed negative correlations in both DIP and PD group. UPDRS scores revealed group-specific patterns, with DIP showing stronger associations between non-motor symptoms and hippocampal volume. Conclusion: This study first reported significant hippocampal subfield atrophy in DIP, distinct from PD, and links structural changes to cognitive, emotional, and motor impairments. These findings advance understanding of DIP pathophysiology and underscore the hippocampus's role in non-motor symptoms.
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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 | 0.001 | 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".