Cognitive decline limits compensatory resource allocation within the aged swallowing network
Bibliographic record
Abstract
Cognitive decline has been postulated to predispose to presbyphagia but the neurophysiological basis of this interaction is unclear. To investigate the role of cognition for compensatory resource allocation within the swallowing network and behavioral swallowing performance in dual-task cognitive and motor interference in ageing, volunteers ≥ 70 years of age without preexisting diseases causing dysphagia were investigated using Flexible Endoscopic Evaluation of Swallowing (FEES) including a cognitive and motor dual-task paradigm and a Montreal Cognitive Assessment. The neural correlates of swallowing during dual-task were characterized using magnetoencephalography. Results were related to cognitive function. Sixty-three participants (77.7 ± 6.1 years) underwent FEES, of which 40 additionally underwent MEG. Both cognitive and motor dual-tasks interfered with swallowing function resulting in an increase in pharyngeal residue and premature bolus spillage. The extent of swallowing deterioration ("dual-task cost") was associated with cognitive decline (cognitive dual-task: Spearman's rho = - 0.39, p = 0.002; motor dual-task: Spearman's rho = - 0.25, p = 0.046). When challenged with dual-tasking participants with regular cognition showed compensatory stronger and broader brain activation in cortical pre- and supplementary motor planning areas as well as in frontal executive regions within the cortical swallowing network (p = 0.004) compared to participants with cognitive deficits. They also performed better in the competing cognitive and motor dual-task and showed fewer incorrect responses (p = 0.028). Oropharyngeal swallowing involves cognitive cortical processing. Cognitive decline seems to limit the capacity for compensatory resource allocation within the swallowing network. This may lead to deterioration in both swallowing function and concurrent cognitive-motor performance in challenging dual-task situations.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".