Comparing Stop Signal Reaction Times in Alzheimer’s and Parkinson’s Disease
Bibliographic record
Abstract
ABSTRACT: Background: To investigate the relative contributions of cerebral cortex and basal ganglia to movement stopping, we tested the optimum combination Stop Signal Reaction Time (ocSSRT) and median visual reaction time (RT) in patients with Alzheimer’s disease (AD) and Parkinson’s disease (PD) and compared values with data from healthy controls. Methods: Thirty-five PD patients, 22 AD patients, and 29 healthy controls were recruited to this study. RT and ocSSRT were measured using a hand-held battery-operated electronic box through a stop signal paradigm. Result: The mean ocSSRT was found to be 309 ms, 368 ms, and 265 ms in AD, PD, and healthy controls, respectively, and significantly prolonged in PD compared to healthy controls (p = 0.001). The ocSSRT but not RT could separate AD from PD patients (p = 0.022). Conclusion: Our data suggest that subcortical networks encompassing dopaminergic pathways in the basal ganglia play a more important role than cortical networks in movement-stopping. Combining ocSSRT with other putative indices or biomarkers of AD (and other dementias) could increase the accuracy of early diagnosis.
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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 | 0.003 |
| 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".