Maturation of EEG power spectra in early adolescence: a longitudinal study
Bibliographic record
Abstract
This study investigated the fine-grained development of the EEG power spectra in early adolescence, and the extent to which it is reflected in changes in peak frequency. It also sought to determine whether sex differences in the EEG power spectra reflect differential patterns of maturation. A group of 56 adolescents were tested at age 10 years and then at two further time-points approximately 18 months apart. The EEG was recorded during both eyes-closed and eyes-open conditions and Fourier transformed to provide estimates of absolute and relative spectral power at 0.5 Hz intervals from 0.5 to 40 Hz. The peak alpha frequency for each individual at each time-point was also determined for relative spectral power. Partial Least Squares (PLS) analysis was used to determine the combination of electrodes and frequencies that showed developmental change, or differed between the sexes. As a function of age, absolute delta and theta frequencies power decreased, and relative alpha2 and beta frequencies increased, replicating the standard findings of a decrease in lower, and increase in higher, frequencies with age. A small but significant increase in peak alpha frequency with age was detected. Moreover PLS analysis performed with individual alpha frequencies aligned to 10 Hz suggested that the age-related increase seen in alpha2 relative power was driven by changes in the peak frequency. Although males demonstrated higher alpha power than females, there were no sex differences in peak frequency, suggesting that there may be more to sex differences in EEG power than simply different rates of maturation between the two sexes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".