Spontaneous blinking and brain health: Can blink‐related oscillations capture brain changes in aging?
Bibliographic record
Abstract
Abstract Background Blink‐related oscillations (BROs) are recently discovered neurophysiological responses that follow spontaneous blinking, and represent environmental monitoring and awareness processes as the brain evaluates new visual information after eye reopening. BROs strongly activate the precuneus which is one of the earliest brain regions impacted by Alzheimer’s disease (AD) neuropathology, and as such may provide an important avenue for assessing and monitoring brain health in aging. In this study, we conducted the first investigation of BRO effects in normal aging to determine whether these responses can capture aging‐related brain changes. Method This research used data from the Cambridge Centre for Aging and Neuroscience (Cam‐CAN) repository, which comprises magnetocenphalography (MEG) and structural magnetic resonance imaging (MRI) from 700 healthy adults aged 18‐88. The MEG paradigm consists of a target detection task with simultaneous auditory and visual stimulation. MEG data were first denoised using independent component analysis, then BRO responses were derived by segmenting the cleaned data into 3s epochs time‐locked to spontaneous blinking. Participants were divided into 4 age groups comprising the youngest (18‐30), middle‐young (31‐50), middle‐old (51‐70), and oldest (71‐90), and analyses were performed using global field power (GFP) and minimum norm estimates to examine BRO effects at the sensor‐ and source‐levels, respectively. Result Results showed that BRO responses were present in all age groups. GFP amplitude increased with age during intervals spanning post‐blink BRO peaks, but not the pre‐blink baseline (p<0.05). BROs also activated brain regions spanning the occipital, temporal, and parietal cortices in all age groups (p<0.05 FWE), with the extent of activation increasing with age. Moreover, the activation extent of precuneus and hippocampus regions showed inverted U‐shape with age, increasing towards the middle‐old group but decreasing in the oldest. Conclusion These results demonstrate for the first time that BRO responses can capture brain changes in normal aging, with increased neural activation for processing blink‐related information as one ages. Results suggest that BROs may represent a simple yet powerful avenue for measuring aging‐related brain function changes, providing a potential tool for early detection of neurodegeneration – particularly with respect to the precuneus and hippocampus regions highly implicated in AD.
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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".