Longitudinal evaluations of somatosensory-motor inhibition in Dopa-responsive dystonia
Bibliographic record
Abstract
INTRODUCTION: GCH1 mutations have been linked to decreased striatal dopamine and development of dopa-responsive dystonia (DRD) and Parkinsonism. Sensory and sensorimotor integration impairments have been documented in various forms of dystonia. DRD patients with confirmed GCH1 mutations have demonstrated normal short-latency afferent inhibition (SAI), a measure of sensorimotor inhibition, under chronic dopaminergic replacement therapy (DRT), but reduced inhibition after a single l-dopa dose following 24 h withdrawal. Studies have revealed normal SAI in other forms of dystonia but reductions with DRT in Parkinson's disease. Longitudinal changes in sensorimotor inhibition are unknown. METHODS: We analyzed sensorimotor inhibition using two different measures: SAI and somatosensory-motor inhibition using dual-site transcranial magnetic stimulation (ds-TMS). SAI was measured using digit stimulation 25 ms prior to contralateral primary motor cortex (M1) TMS. DS-TMS was measured using TMS over the somatosensory cortex 1 or 2.5 ms prior to ipsilateral M1 stimulation. A total of 20 GCH1 mutation carriers and 20 age-matched controls were included in the study. SAI and ds-TMS were evaluated in GCH1 mutation carriers both OFF and ON DRT compared to controls. Furthermore, longitudinal changes of SAI were examined in a subset of the same individuals that were measured ∼five years earlier. RESULTS: Neither SAI nor ds-TMS were significantly different in GCH1 mutation carriers relative to controls. No effects of DRT on SAI or ds-TMS were seen but SAI decreased over time in mutation carriers OFF DRT. CONCLUSION: Our longitudinal results suggest changes in SAI that could be associated with plasticity changes in sensorimotor networks.
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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".