Asymmetric neuromodulation of motor circuits in Parkinson's disease: The role of subthalamic deep brain stimulation
Bibliographic record
Abstract
Whereas hemispheric dominance is well-established for appendicular motor control in humans, the evidence for dominance in axial motor control is still scarce. In Parkinson's disease (PD), unilateral (UL) onset of appendicular motor symptoms corresponds with asymmetric neurodegeneration predominantly affecting contralateral nigrostriatal circuits. Disease progression yields bilateral and axial motor symptoms but the initial appendicular asymmetry usually persists. Furthermore, there is evidence for hemispheric dominance for axial motor dysfunction in some of these patients. Dopaminergic medications improve appendicular symptoms but can also produce motor complications over time. Once these complications develop, bilateral (BL) deep brain stimulation (DBS) of the subthalamic nuclei (STN) can significantly improve appendicular symptoms while reducing medication doses and motor complications. Conversely, axial motor symptoms remain a significant source of disability, morbidity, and mortality for patients with PD. These axial symptoms do not necessarily improve with dopaminergic therapy, might not respond, and could even worsen after BL-DBS. In contrast to medications, DBS provides the opportunity to modify stimulation parameters for each cerebral hemisphere. Identical, BL-DBS of motor circuits with hemispheric dominance in PD might produce overstimulation on one side and/or understimulation on the other side, which could contribute to motor dysfunction. Several studies based on asymmetry of appendicular motor symptoms already support an initial UL rather than BL approach to DBS in some patients. The response of axial motor symptoms to UL versus BL-DBS remains unclear. Nonetheless, UL-DBS, staged BL-DBS, or asymmetric programming of BL-DBS could also be considered in patients with PD.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".