Time-resolved phase-amplitude coupling in neural oscillations
Bibliographic record
Abstract
Cross-frequency coupling between neural oscillations is a phenomenon observed across spatial scales in a wide range of preparations, including human non-invasive electrophysiology. Although the functional role and mechanisms involved are not entirely understood, the concept of interdependent neural oscillations drives an active field of research to comprehend the ubiquitous polyrhythmic activity of the brain, beyond empirical observations. Phase-amplitude coupling, a particular form of cross-frequency coupling between bursts of high-frequency oscillations and the phase of lower frequency rhythms, has recently received considerable attention. However, the measurement methods have relatively poor sensitivity and require long segments of experimental data. This obliterates the resolution of fast changes in coupling related to behavior, and more generally, to the non-stationary dynamics of brain electrophysiology. We propose a new measure of phase-amplitude coupling that can resolve up to one, optimally two, cycles of the underlying slow frequency component. The method also provides a measure of the coupling strength, for augmented insight into the mechanisms involved. We demonstrate the technique with synthesized data and compare its performances with existing methods. We also show that the method reveals rapid changes in coupling parameters in data from the entorhinal cortex of a free-behaving rat. The time-resolved changes revealed are compatible with behavior and complement observed modulations of oscillatory power. We anticipate that this new measure of dynamic phase-amplitude coupling will contribute to accelerate research into the dynamics of inter-dependent oscillatory components related to brain functions and dysfunctions.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 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".