Spontaneous blinking and brain health in aging: Large-scale evaluation of blink-related oscillations across the lifespan
Bibliographic record
Abstract
Blink-related oscillations (BROs) are newly discovered neurophysiological brainwave responses associated with spontaneous blinking, and represent environmental monitoring and awareness processes as the brain evaluates new visual information appearing after eye re-opening. BRO responses have been demonstrated in healthy young adults across multiple task states and are modulated by both task and environmental factors, but little is known about this phenomenon in aging. To address this, we undertook the first large-scale evaluation of BRO responses in healthy aging using the Cambridge Centre for Aging and Neuroscience (Cam-CAN) repository, which contains magnetoencephalography (MEG) data from a large sample (N = 457) of healthy adults across a broad age range (18–88) during the performance of a simple target detection task. The results showed that BRO responses were present in all age groups, and the associated effects exhibited significant age-related modulations comprising an increase in sensor-level global field power (GFP) and source-level theta and alpha spectral power within the bilateral precuneus. Additionally, the extent of cortical activations also showed an inverted-U relationship with age, consistent with neurocompensation with aging. Crucially, these age-related differences were not observed in the behavioral measures of task performance such as reaction time and accuracy, suggesting that blink-related neural responses during the target detection task are more sensitive in capturing aging-related brain function changes compared to behavioral measures alone. Together, these results suggest that BRO responses are not only present throughout the adult lifespan, but the effects can also capture brain function changes in healthy aging—thus providing a simple yet powerful avenue for evaluating brain health in aging.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".