Color discrimination deficits in Parkinson's disease are related to cognitive impairment and white‐matter alterations
Bibliographic record
Abstract
Color discrimination deficit is a common nonmotor manifestation of Parkinson's disease (PD). However, the pathophysiology of this dysfunction remains poorly understood. Although retinal structure changes found in PD have been suggested to cause color discrimination deficits, the impact of cognitive impairment and cortical alterations remains to be determined. We investigated the contribution of cognitive impairment to color discrimination deficits in PD and correlated them with cortical anomalies. Sixty-six PD patients without dementia and 20 healthy controls performed the Farnsworth-Munsell 100 hue test and underwent a comprehensive neuropsychological assessment for mild cognitive impairment diagnosis. In a subgroup of 26 PD patients, we also used high-definition neuroanatomical magnetic resonance imaging for cortical thickness and diffusion tensor analysis. PD patients with mild cognitive impairment performed poorly on the Farnsworth-Munsell 100 hue test compared with PD patients without mild cognitive impairment and controls. In PD patients, performance on the Farnsworth-Munsell 100 hue test was correlated with measures of visuospatial abilities and executive functions. Neuroimaging analysis revealed higher mean and radial diffusivity values in right posterior white-matter structures that correlated with poor performance on the Farnsworth-Munsell 100 hue test. No cortical thickness correlation reached significance. This study showed that cognitive impairment makes a major contribution to the color discrimination deficits reported in PD. Thus, performance on the Farnsworth-Munsell 100 hue test may reflect cognitive impairment more than color discrimination deficits in PD. Poor performance on the Farnsworth-Munsell 100 hue test was also associated with white-matter alterations in right posterior brain regions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".