Estimation of Spatial Distribution of the Main Rhythms of Human Brain Activity Using the Method of Functional Tomography Based on Magnetic Encephalography Data
Bibliographic record
Abstract
Three-dimensional structures of distribution of sources generating the main rhythms of electrical activity of the brain are found. The frequency bands of the following rhythms are considered: delta (1–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), beta (13–35 Hz), and gamma (35–49 Hz). Experimental data obtained on 275-channel magnetic encephalographs at McGill University and the University of Montreal were considered. Magnetic encephalograms of spontaneous brain activity were recorded for 5 minutes in a magnetically insulated room. The spatial position of all elementary sources of brain activity was calculated by the method of functional tomography based on a detailed spectral analysis of multichannel magnetic encephalography data and on the solution of the inverse problem for localization of elementary oscillations at each frequency. Combining the data on the location and power of sources of all frequencies included in the considered rhythm generates a cloud of points, which is the source of this rhythm. For each rhythm, a cloud of points in the experimental space is shown, statistical characteristics of the distribution of sources are calculated. The proposed method can be used for a detailed quantitative study of brain activity.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".