The fractal dimension of resting state EEG increases over age in children
Bibliographic record
Abstract
Resting-state electroencephalography (rs-EEG) represents spontaneous neural activity and is increasingly analyzed using nonlinear measures to assess brain complexity. The Higuchi Fractal Dimension (HFD) is a widely used metric for quantifying the fractal properties of EEG signals, yet its developmental trajectory remains largely unexplored. In this study, we examined age-related changes in HFD across childhood, adolescence, and early adulthood. We analyzed eyes-closed rs-EEG from 128 channels in 83 neurotypical participants (8 to 30 yr) from the MIPDB database. To assess developmental patterns, we applied a Gaussian Linear Mixed Model with age, electrode location, and their interaction as predictors, alongside non-parametric cluster-based permutation analysis to evaluate topographical differences. We observed a significant increase in HFD with age (P = 0.001), most pronounced between childhood and adolescence, followed by stabilization in early adulthood. HFD also varied across electrode locations, with higher values in frontal, central, and temporal regions and lower values in parietal and occipital areas. These findings provide new insights into the maturation of neural complexity in rs-EEG, aligning with known structural and functional changes in brain development. This study contributes to the growing body of research on nonlinear EEG dynamics and their relevance to neurodevelopment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".