Motor cortex excitability is reduced during freezing of upper limb movement in Parkinson’s disease
Bibliographic record
Abstract
Whilst involvement of the motor cortex in the phenomenon of freezing in Parkinson's disease has been previously suggested, few empiric studies have been conducted to date. We investigated motor cortex (M1) excitability in eleven right-handed Parkinson's disease patients (aged 69.7 ± 9.6 years, disease duration 11.2 ± 3.9 years, akinesia-rigidity type) with verified gait freezing using a single-pulse transcranial magnetic stimulation (TMS) repetitive finger tapping paradigm. We delivered single TMS pulses at 120% of the active motor threshold at the 'ascending (contraction)' and 'descending (relaxation)' slope of the tap cycle during i) regular tapping, ii) the transition period of the three taps prior to a freeze and iii) during freezing of upper limb movement. M1 excitability was modulated along the tap cycle with greater motor evoked potentials (MEPs) during 'ascending' than 'descending'. Furthermore, MEPs during the 'ascending' phase of regular tapping, but not during the transition period, were greater compared to the MEPs recorded throughout a freeze. Neither force nor EMG activity 10-110 s before the stimulus predicted MEP size. This piloting study suggests that M1 excitability is reduced during freezing and the transition period preceding a freeze. This supports that M1 excitability is critical to freezing in Parkinson's 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) | 0.000 | 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".