Deficits in the Mimicry of Facial Expressions in Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: Humans spontaneously mimic the facial expressions of others, facilitating social interaction. This mimicking behavior may be impaired in individuals with Parkinson's disease, for whom the loss of facial movements is a clinical feature. OBJECTIVE: To assess the presence of facial mimicry in patients with Parkinson's disease. METHOD: Twenty-seven non-depressed patients with idiopathic Parkinson's disease and 28 age-matched controls had their facial muscles recorded with electromyography while they observed presentations of calm, happy, sad, angry, and fearful emotions. RESULTS: Patients exhibited reduced amplitude and delayed onset in the zygomaticus major muscle region (smiling response) following happy presentations (patients M = 0.02, 95% confidence interval [CI] -0.15 to 0.18, controls M = 0.26, CI 0.14 to 0.37, ANOVA, effect size [ES] = 0.18, p < 0.001). Although patients exhibited activation of the corrugator supercilii and medial frontalis (frowning response) following sad and fearful presentations, the frontalis response to sad presentations was attenuated relative to controls (patients M = 0.05, CI -0.08 to 0.18, controls M = 0.21, CI 0.09 to 0.34, ANOVA, ES = 0.07, p = 0.017). The amplitude of patients' zygomaticus activity in response to positive emotions was found to be negatively correlated with response times for ratings of emotional identification, suggesting a motor-behavioral link (r = -0.45, p = 0.02, two-tailed). CONCLUSIONS: Patients showed decreased mimicry overall, mimicking other peoples' frowns to some extent, but presenting with profoundly weakened and delayed smiles. These findings open a new avenue of inquiry into the "masked face" syndrome of PD.
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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".