Task-related oxygenation in the prefrontal cortex as a function of mask-wearing frequency: An empirical test using functional near-infrared spectroscopy
Bibliographic record
Abstract
Introduction of brain hypoxia by frequent mask-wearing is a concern voiced by some who resist masking mandates. Studies have examined acute effects of one-shot mask-wearing on peripheral and cerebral oxygenation in the laboratory, but not effects of everyday mask-wearing frequencies on task-related functional activation. The objective of the current study was to examine whether frequency of mask-wearing in daily life is associated with lower task-related brain oxygenation levels, and whether the magnitude of any such effects vary by age and sex. Participants were 78 community-dwelling adults between the ages of 18 and 84 years, all of whom were vaccinated at the time of participation; 65.4% (n = 51) were female. Frequency of mask-wearing was assessed using survey questions on mask-wearing practice during an active COVID-19 mask mandate. Recordings of task-related cerebral oxygenation were taken during the completion of a simple reaction time task using 16-channel functional near-infrared spectroscopy (fNIRS). The psychomotor vigilance task elicited reliable increases in cerebral oxygenation within the right mid-frontal gyrus (F(1,61.345) = 15.975, p < .001). However, there was no significant association between everyday masking frequency and performance on the psychomotor vigilance task (b = 0.059, SE = 0.092 (95% CI [-0.122, 0.241]), t = .646, p = .520), nor any association between everyday masking frequency and task-related brain oxygenation on any measurement channel (all ps < .05). Higher mask-wearing frequency in daily life is not associated with significantly lower levels of task-related brain oxygenation, or worse performance on a sustained attention task.
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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 | 0.003 |
| 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".