Multimodal oculomotor assessment reveals prodromal markers of Parkinson’s disease in non-manifesting LRRK2 G2019S mutation carriers
Bibliographic record
Abstract
Oculomotor behaviour changes in patients with Parkinson's disease (PD) are a promising source of prodromal disease markers. Capitalizing on this phenomenon to facilitate early diagnosis requires oculomotor assessment in prodromal cohorts. We examined oculomotor behaviour in non-manifesting LRRK2 G2019S mutation carriers (LRRK2-NM), who have heightened PD risk.Seventeen LRRK2-NM participants, 47 patients with idiopathic PD, and 63 healthy age-matched control participants completed an interleaved pro- and antisaccade task while undergoing video-based eye-tracking. We analyzed between-group differences in saccade, pupil, blink, and fixation acquisition behaviour. Patients with PD showed previously demonstrated abnormalities (saccade hypometria, antisaccade errors). Relative to controls, LRRK2-NM participants and patients with PD both displayed increased short-latency prosaccades and reduced pupil velocity, plus altered fixation acquisition-less preemptive returning of gaze to the future fixation point location. Interestingly, the effect on blink probability was opposite-higher than controls in LRRK2-NM participants but lower in patients with PD. Future longitudinal studies must confirm the viability of these features as prodromal PD markers.
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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) | 0.000 | 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".