Autophonic loudness perception in Parkinson's disease
Bibliographic record
Abstract
The relationship between the intensity and loudness of self-generated (autophonic) speech remains invariant despite changes in auditory feedback, indicating that non-auditory processes contribute to this form of perception. The aim of the current study was to determine if the speech perception deficit associated with Parkinson's disease may be linked to deficits in such processes. Loudness magnitude estimates were obtained from parkinsonian and non-parkinsonian subjects across four separate conditions: self-produced speech under normal, perturbed, and masked auditory feedback, as well as auditory presentation of pre-recorded speech (passive listening). Slopes and intercepts of loudness curves were compared across groups and conditions. A significant difference in slope was found between autophonic and passive-listening conditions for both groups. Unlike control subjects, parkinsonian subjects' magnitude estimates under auditory masking increased in variability and did not show as strong a shift in intercept values. These results suggest that individuals with Parkinson's disease rely on auditory feedback to compensate for underlying deficits in sensorimotor integration important in establishing and regulating autophonic loudness.
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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".