Two organizing principles of vocal production: Implications for nonhuman and human primates
Bibliographic record
Abstract
Vocal communication in nonhuman primates receives considerable research attention, with many investigators arguing for similarities between this calling and speech in humans. Data from development and neural organization show a central role of affect in monkey and ape sounds, however, suggesting that their calls are homologous to spontaneous human emotional vocalizations while having little relation to spoken language. Based on this evidence, we propose two principles that can be useful in evaluating the many and disparate empirical findings that bear on the nature of vocal production in nonhuman and human primates. One principle distinguishes production-first from reception-first vocal development, referring to the markedly different role of auditory-motor experience in each case. The second highlights a phenomenon dubbed dual neural pathways, specifically that when a species with an existing vocal system evolves a new functionally distinct vocalization capability, it occurs through emergence of a second parallel neural pathway rather than through expansion of the extant circuitry. With these principles as a backdrop, we review evidence of acoustic modification of calling associated with background noise, conditioning effects, audience composition, and vocal convergence and divergence in nonhuman primates. Although each kind of evidence has been interpreted to show flexible cognitively mediated control over vocal production, we suggest that most are more consistent with affectively grounded mechanisms. The lone exception is production of simple, novel sounds in great apes, which is argued to reveal at least some degree of volitional vocal control. If also present in early hominins, the cortically based circuitry surmised to be associated with these rudimentary capabilities likely also provided the substrate for later emergence of the neural pathway allowing volitional production in modern humans.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".