Speech pauses in production of action language in Parkinson’s disease: A potential marker of mild cognitive impairment (S51.006)
Bibliographic record
Abstract
Objective: To evaluate pauses before action utterances in Parkinson’s disease (PD) as a marker of cognitive function. Background: Speech is frequently impaired in PD, with longer pauses within and between utterances compared to controls. Action verb use is also impaired, but it is unclear if motor or cognitive dysfunction underlies this deficit. We hypothesized that production of utterances containing action verbs is more associated with cognitive than motor function, and may serve as a marker of mild cognitive impairment (MCI) in PD. Design/Methods: 93 participants with PD and 8 older controls were asked to describe the cookie theft picture. We identified action utterances (AU, utterances containing an action verb) and non-action utterances (nonAU). Pauses > 2 sec. were measured using Praat(v5.3.72). To control for the amount of speech produced, the total duration of pauses was divided by number of utterances. Wilcoxon rank-sum test was used to compare linguistic variables between PD and controls. In the PD group, Spearman’s correlations between linguistic variables, motor severity (MDS-UPDRS Part-III) and global cognitive function (MoCA) were calculated. We ran a logistic regression model with the dependent variable cognitive status (MCI or normal cognition), and predictors linguistic markers, controlled for age, sex, words per minute and UPRDS. Results: Compared to controls, PD participants had significantly longer pauses before AU (p<0.04) but not nonAU. UPRDS was not correlated with linguistic markers but MoCA was inversely correlated with pauses before AU (rho= −0.34, p=0.0004) and before nonAU (rho=−0.38, p=0.0001). Pauses before AU (OR 30.6 (95% CI=1.81–519.50), p=0.018) but not before nonAU were predictive of PD-MCI. Conclusions: In PD, pausing before AU in spontaneous speech is associated with cognitive function independent of motor severity. This linguistic variable was sensitive to PD-MCI and could be a useful marker of early cognitive decline in PD. Future investigation should explore the cognitive basis of this action related language deficit. Disclosure: Dr. Nascimento Andrade has nothing to disclose. Dr. Smith has received personal compensation in the range of $0-$499 for serving as a Consultant for PureTech. The institution of Dr. Smith has received research support from NIH. Dr. Smith has received personal compensation in the range of $0-$499 for serving as a single time expert panel discussion contributor with Acadia. Ms. Manxhari has nothing to disclose.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".