Similar Spectral Power Densities Within the Schumann Resonance and a Large Population of Quantitative Electroencephalographic Profiles: Supportive Evidence for Koenig and Pobachenko
Bibliographic record
Abstract
In 1954 and 1960 Koenig and his colleagues described the remarkable similarities of spectral power density profiles and patterns between the earth-ionosphere resonance and human brain activity which also share magnitudes for both electric field (mV/m) and magnetic field (pT) components. In 2006 Pobachenko and colleagues reported real time coherence between variations in the Schumann and brain activity spectra within the 6-16 Hz band for a small sample. We examined the ratios of the average potential differences (~3 μV) obtained by whole brain quantitative electroencephalography (QEEG) between rostral-caudal and left-right (hemispheric) comparisons of 238 measurements from 184 individuals over a 3.5 year period. Spectral densities for the rostral-caudal axis revealed a powerful peak at 10.25 Hz while the left-right peak was 1.95 Hz with beat-differences of ~7.5 to 8 Hz. When global cerebral measures were employed, the first (7-8 Hz), second (13-14 Hz) and third (19-20 Hz) harmonics of the Schumann resonances were discernable in averaged QEEG profiles in some but not all participants. The intensity of the endogenous Schumann resonance was related to the 'best-of-fitness' of the traditional 4-class microstate model. Additional measurements demonstrated real-time coherence for durations approximating microstates in spectral power density variations between Schumann frequencies measured in Sudbury, Canada and Cumiana, Italy with the QEEGs of local subjects. Our results confirm the measurements reported by earlier researchers that demonstrated unexpected similarities in the spectral patterns and strengths of electromagnetic fields generated by the human brain and the earth-ionospheric cavity.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".