Pitch underlies activation of the vocal system during affective vocalization
Bibliographic record
Abstract
Affective prosody is that aspect of speech that conveys a speaker's emotional state through modulations in various vocal parameters, most prominently pitch. While a large body of research implicates the cingulate vocalization area in controlling affective vocalizations in monkeys, no systematic test of functional homology for this area has yet been reported in humans. In this study, we used functional magnetic resonance imaging to compare brain activations when subjects produced affective vocalizations in the form of exclamations vs non-affective vocalizations with similar pitch contours. We also examined the perception of affective vocalizations by having participants make judgments about either the emotions being conveyed by recorded affective vocalizations or the pitch contours of the same vocalizations. Production of affective vocalizations and matched pitch contours activated a highly overlapping set of brain areas, including the larynx-phonation area of the primary motor cortex and a region of the anterior cingulate cortex that is consistent with the macro-anatomical position of the cingulate vocalization area. This overlap contradicts the dominant view that these areas form two distinct vocal pathways with dissociable functions. Instead, we propose that these brain areas are nodes in a single vocal network, with an emphasis on pitch modulation as a vehicle for affective expression.
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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".