Cerebral Areas Processing Swallowing and Tongue Movement Are Overlapping but Distinct: A Functional Magnetic Resonance Imaging Study
Bibliographic record
Abstract
Although multiple regions of the cerebral cortex have been implicated in swallowing, the functional contributions of each brain area remain unclear. The present study sought to clarify the roles of these cortical foci in swallowing by comparing brain activation associated with voluntary saliva swallowing and voluntary tongue elevation. Fourteen healthy right-handed subjects were examined with single-event-related functional magnetic resonance imaging (fMRI) while laryngeal movements associated with swallowing and tongue movement were simultaneously recorded. Both swallowing and tongue elevation activated 1) the left lateral pericentral and anterior parietal cortex, and 2) the anterior cingulate cortex (ACC) and adjacent supplementary motor area (SMA), suggesting that these brain regions mediate processes shared by swallowing and tongue movement. Tongue elevation activated a larger total volume of cortex than swallowing, with significantly greater activation within the ACC, SMA, right precentral and postcentral gyri, premotor cortex, right putamen, and thalamus. Although a contrast analysis failed to identify activation foci specific to swallowing, superimposed activation maps suggested that the most lateral extent of the left pericentral and anterior parietal cortex, rostral ACC, precuneus, and right parietal operculum/insula were preferentially activated by swallowing. This finding suggests that these brain areas may mediate processes specific to swallowing. Approximately 60% of the subjects showed a strong functional lateralization of the postcentral gyrus toward the left hemisphere for swallowing, whereas 40% showed a similar activation bias for the tongue elevation task. This finding supports the view that the oral sensorimotor cortices within the left and right hemispheres are functionally nonequivalent.
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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 | 0.001 |
| 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".