Functional Connectivity States of Alpha Rhythm Sources in the Human Cortex at Rest: Implications for Real-Time Brain State Dependent EEG-TMS
Bibliographic record
Abstract
Alpha is the predominant rhythm of the human electroencephalogram, but its function, multiple generators and functional coupling patterns are still relatively unknown. In this regard, alpha connectivity patterns can change between different cortical generators depending on the status of the brain. Therefore, in the light of the communication through coherence framework, an alpha functional network depends on the functional coupling patterns in a determined state. This notion has a relevance for brain-state dependent EEG-TMS because, beyond the local state, a network connectivity overview at rest could provide further and more comprehensive information for the definition of 'instantaneous state' at the stimulation moment, rather than just the local state around the stimulation site. For this reason, we studied functional coupling at rest in 203 healthy subjects with MEG data. Sensor signals were source localized and connectivity was studied at the Individual Alpha Frequency (IAF) between three different cortical areas (occipital, parietal and prefrontal). Two different and complementary phase-coherence metrices were used. Our results show a consistent connectivity between parietal and prefrontal regions whereas occipito-prefrontal connectivity is less marked and occipito-parietal connectivity is extremely low, despite physical closeness. We consider our results a relevant add-on for informed, individualized real-time brain state dependent stimulation, with possible contributions to novel, personalized non-invasive therapeutic approaches.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".