Sensory contribution to vocal emotion deficit in patients with cerebellar stroke
Bibliographic record
Abstract
In recent years, there has been increasing evidence of cerebellar involvement in emotion processing. Difficulties in the recognition of emotion from voices (i.e., emotional prosody) have been observed following cerebellar stroke. However, the interplay between sensory and higher-order cognitive dysfunction in these deficits, as well as possible hemispheric specialization for emotional prosody processing, has yet to be elucidated. We investigated the emotional prosody recognition performances of patients with right versus left cerebellar lesions, as well as of matched controls, entering the acoustic features of the stimuli in our statistical model. We also explored the cerebellar lesion-behavior relationship, using voxel-based lesion-symptom mapping. Results revealed impairment of vocal emotion recognition in both patient subgroups, particularly for neutral or negative prosody, with a higher number of misattributions in patients with right-hemispheric stroke. Voxel-based lesion-symptom mapping showed that some emotional misattributions correlated with lesions in the right Lobules VIIb and VIII and right Crus I and II. Furthermore, a significant proportion of the variance in this misattribution was explained by acoustic features such as pitch, loudness, and spectral aspects. These results point to bilateral posterior cerebellar involvement in both the sensory and cognitive processing of emotions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.005 |
| 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) | 0.000 | 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 teacher head, 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".