Lower-limb express visuomotor responses are spared in Parkinson’s disease during step initiation from a stable position
Bibliographic record
Abstract
OBJECTIVE: While motor impairments in Parkinson's Disease are well-studied, less is known about how people with Parkinson's Disease (PwPD) can nevertheless rapidly transform vision into action. These transformations can be studied by measuring express visuomotor responses (EVRs), which are stimulus-directed bursts of muscle activity thought to originate from the superior colliculus, reaching the periphery via the tecto-reticulospinal pathway. METHODS: We examined EVRs in the lower limbs during goal-directed step initiation in 20 PwPD and 20 healthy controls (HC). As lower-limb EVRs in the young have been shown to interact with postural control - which are often affected in PwPD - we manipulated postural demands by varying stance width and target location. RESULTS: Under low postural demand, both groups expressed consistent EVRs. EVR magnitudes were significantly higher in PwPD, yet decreased with greater disease severity. Under high postural demands, EVRs were suppressed and followed by strong anticipatory postural adjustments, which were smaller in PwPD compared to HC. CONCLUSIONS: The circuit mediating EVRs may be upregulated in early PD to compensate for motor deficits experienced in daily life, but becomes progressively impaired as PD advances. SIGNIFICANCE: These findings provide novel insight into the neural underpinnings of rapid stepping in health and disease.
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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 | 0.000 | 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) | 0.002 | 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".