The impact of parkinson's disease on the cortical mechanisms that support auditory–motor integration for voice control
Bibliographic record
Abstract
Several studies have shown sensorimotor deficits in speech processing in individuals with idiopathic Parkinson's disease (PD). The underlying neural mechanisms, however, remain poorly understood. In the present event-related potential (ERP) study, 18 individuals with PD and 18 healthy controls were exposed to frequency-altered feedback (FAF) while producing a sustained vowel and listening to the playback of their own voice. Behavioral results revealed that individuals with PD produced significantly larger vocal compensation for pitch feedback errors than healthy controls, and exhibited a significant positive correlation between the magnitude of their vocal responses and the variability of their unaltered vocal pitch. At the cortical level, larger P2 responses were observed for individuals with PD compared with healthy controls during active vocalization due to left-lateralized enhanced activity in the superior and inferior frontal gyrus, premotor cortex, inferior parietal lobule, and superior temporal gyrus. These two groups did not differ, however, when they passively listened to the playback of their own voice. Individuals with PD also exhibited larger P2 responses during active vocalization when compared with passive listening due to enhanced activity in the inferior frontal gyrus, precental gyrus, postcentral gyrus, and middle temporal gyrus. This enhancement effect, however, was not observed for healthy controls. These findings provide neural evidence for the abnormal auditory-vocal integration for voice control in individuals with PD, which may be caused by their deficits in the detection and correction of errors in voice auditory feedback. Hum Brain Mapp 37:4248-4261, 2016. © 2016 Wiley Periodicals, Inc.
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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) | 0.001 | 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".