Neuroimaging of brain changes associated with cognitive impairment in Parkinson's disease
Bibliographic record
Abstract
Cognitive impairment occurs frequently in Parkinson's disease (PD) and the concept of Mild Cognitive Impairment in PD (PD-MCI) has recently emerged. Patients with mild impairment are at risk of developing dementia, and thus it is a topic of growing interest. Many previous studies have investigated the neural correlates of cognitive impairment, in particular executive dysfunction, in PD patients without dementia using neuroimaging techniques including structural MRI, functional MRI and PET imaging. These studies, which have provided a foundation for understanding which brain regions and neurotransmitter systems may be involved in executive dysfunction in PD, will be reviewed. Recent neuroimaging studies that have used specific criteria to classify patients as PD-MCI, in the hopes of gaining further insight into the underlying neural mechanisms will also be discussed. In particular, this review will cover key findings involving structural MRI investigating grey and white matter changes, functional MRI to examine changes in neural activation and PET imaging to investigate metabolic and neurochemical changes that have led to an improved understanding of pathology associated with executive dysfunction in PD without dementia and PD-MCI.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".