Variations in the frequency and amplitude of resting-state EEG and fMRI signals in normal adults: The effects of age and sex
Bibliographic record
Abstract
Abstract Frequency and amplitude features of both resting-state electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are crucial metrics that reveal patterns of brain health in aging. However, the association between these two modalities is still unclear. In this study, we examined the peak frequency and standard deviation of both modalities in a dataset comprising healthy young (35.5±3.4 years, N=134) and healthy old (66.9±4.8 years, N=51) adults. Both age and sex effects were examined using non-parametric analyses of variance (ANOVA) and Tukey’s Honest Significant Difference (HSD) post-hoc comparisons in the cortical and subcortical regions. We found that, with age, EEG power decreases in the low frequency band (1-12 Hz) but increases in the high frequency band (12-30 Hz). Moreover, EEG frequency generally shifts up with aging. For fMRI, fluctuation amplitude is lower but fluctuation frequency is higher in older adults, but in a manner that depends on the fMRI frequency range. Furthermore, there are significant sex effects in EEG power (female > male), but the sex effect is negligible for EEG frequency as well as fMRI power and frequency. We also found that the fMRI-EEG power ratio is higher in young adults than old adults. However, the mediation analysis shows the association between EEG and fMRI parameters in aging is negligible. This is the first study that examines both power and frequency of both resting EEG and fMRI signals in the same cohort. In conclusion, both fMRI and EEG signals reflect age-related and sex-related brain differences, but they likely associate with different origins.
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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 | 0.003 |
| 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".