Human larynx motor cortices coordinate respiration for vocal-motor control
Bibliographic record
Abstract
Vocal flexibility is a hallmark of the human species, most particularly the capacity to speak and sing. This ability is supported in part by the evolution of a direct neural pathway linking the motor cortex to the brainstem nucleus that controls the larynx the primary sound source for communication. Early brain imaging studies demonstrated that larynx motor cortex at the dorsal end of the orofacial division of motor cortex (dLMC) integrated laryngeal and respiratory control, thereby coordinating two major muscular systems that are necessary for vocalization. Neurosurgical studies have since demonstrated the existence of a second larynx motor area at the ventral extent of the orofacial motor division (vLMC) of motor cortex. The vLMC has been presumed to be less relevant to speech motor control, but its functional role remains unknown. We employed a novel ultra-high field (7T) magnetic resonance imaging paradigm that combined singing and whistling simple melodies to localise the larynx motor cortices and test their involvement in respiratory motor control. Surprisingly, whistling activated both 'larynx areas' more strongly than singing despite the reduced involvement of the larynx during whistling. We provide further evidence for the existence of two larynx motor areas in the human brain, and the first evidence that laryngeal-respiratory integration is a shared property of both larynx motor areas. We outline explicit predictions about the descending motor pathways that give these cortical areas access to both the laryngeal and respiratory systems and discuss the implications for the evolution of speech.
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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 | 0.000 |
| 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) | 0.003 | 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".