Functional abnormalities in the primary orofacial sensorimotor cortex during speech in Parkinson's disease
Bibliographic record
Abstract
Parkinson's disease (PD) affects speech, including respiration, phonation, and articulation. We measured the blood oxygen level-dependent (BOLD) response to overt sentence reading in: (1) 9 treated female patients with mild to moderate PD (age; mean 66.0 +/- 11.6 years, mean levodopa equivalent 583.3 +/- 397.9 mg) and (2) 8 age-matched healthy female controls (age; mean 62.2 years +/- 12.3). Speech was recorded in the scanner to assess which brain regions underlie variations in the initiation and paralinguistic aspects (e.g., pitch, loudness, and rate) of speech production in the two groups. There were no differences in paralinguistic aspects of speech except for speech loudness; it was lower in PD patients compared with that in controls, when age was used as a covariate. In both groups, we observed increases in the BOLD response (reading-baseline) in brain regions involved in speech production and perception. In PD patients, as compared with controls, we found significantly higher BOLD signal in the right primary orofacial sensorimotor cortex and more robust correlations between the measured speech parameters and the BOLD response to reading, particularly, in the left primary orofacial sensorimotor cortex. These results might reflect compensatory mechanisms and/or treatment effects that take place in mild to moderately ill PD patients with quality of speech yet comparable with that of age-matched controls.
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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 | 0.000 |
| 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) | 0.001 | 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".