Investigating cognitive performance of healthy older adults using phase synchrony analyses of EEG signals
Bibliographic record
Abstract
Abstract Background Aging is a physiological process considered as a major risk factor for most irreversible neurodegenerative diseases, including Alzheimer’s disease and Parkinson’s disease. Moreover, it is highly associated with decline in attention, memory, communication skills and many other cognitive functions as well as an overall delay in cognitive information processing in aging individuals free of any neurodegenerative diseases. Although much research has been done on the human brain in clinical cohorts, fewer studies have investigated the impact of age in healthy aging individuals. However, results of neuroimaging studies indicate that healthy aging is accompanied by significant structural and functional changes in the brain. This study uses EEG coherence and phase synchrony measures to investigate the relationship between the neural connectivity in the human brain and cognitive scores from the Montreal Cognitive Assessment (MoCA) in healthy older adults. Method 75 participants aged between 60‐80 (M = 66.78, SD = 6.98) were recruited as part of the Aging Brain Cohort dataset at the University of South Carolina (ABC@UofSC). Resting‐state EEG signals were recorded from 128 electrodes using the Brain Vision actiCAP slim electrode layout with 500 Hz sampling frequency rate while participants were sitting quietly in a room using the Acti‐CHAMP EEG plus system. After preprocessing and denoising EEG signals, phase synchrony measure between each pair of electrodes was calculated for all frequency bands (delta, theta, alpha, gamma). Finally, a univariate general linear model (GLM) analysis was used to identify significant relationships between resting‐state functional connectivity indexed by phase synchrony and cognitive scores assessed by MoCA test while controlling for participants’ chronological age and gender. Results Our preliminary results revealed a significant association between cognitive scores and resting‐state functional connectivity of several brain electrodes in frontal, temporal, and parietal areas in high frequency alpha and beta bands. Conclusion Our results provide evidence that phase synchrony, a statistical measure of correlation between signals from electrodes spatially separated on the human scalp, could provide reliable biomarkers of cognitive performance of individuals in pre‐clinical disease states. This could enhance the clinicians’ ability to make early diagnosis of cognitive decline in older adults.
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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 | 0.001 | 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) | 0.002 | 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".