Human Auditory–Motor Networks Show Frequency‐Specific Phase‐Based Coupling in Resting‐State <scp>MEG</scp>
Bibliographic record
Abstract
Perception and production of music and speech rely on auditory-motor coupling, a mechanism which has been linked to temporally precise oscillatory coupling between auditory and motor regions of the human brain, particularly in the beta frequency band. Recently, brain imaging studies using magnetoencephalography (MEG) have also shown that accurate auditory temporal predictions specifically depend on phase coherence between auditory and motor cortical regions. However, it is not yet clear whether this tight oscillatory phase coupling is an intrinsic feature of the auditory-motor loop, or whether it is only elicited by task demands. Further, we do not know if phase synchrony is uniquely enhanced in the auditory-motor system compared to other sensorimotor modalities, or to which degree it is amplified by musical training. In order to resolve these questions, we measured the degree of phase locking between motor regions and auditory or visual areas in musicians and non-musicians using resting-state MEG. We derived phase locking values (PLVs) and phase transfer entropy (PTE) values from 90 healthy young participants. We observed significantly higher PLVs across all auditory-motor pairings compared to all visuomotor pairings in all frequency bands. The pairing with the highest degree of phase synchrony was right primary auditory cortex with right ventral premotor cortex, a connection which has been highlighted in previous literature on auditory-motor coupling. Additionally, we observed that auditory-motor and visuomotor PLVs were significantly higher across all structures in the right hemisphere, and we found the highest differences between auditory and visual PLVs in the theta, alpha, and beta frequency bands. Last, we found that the theta and beta bands exhibited a preference for a motor-to-auditory PTE direction and that the alpha and gamma bands exhibited the opposite preference for an auditory-to-motor PTE direction. Taken together, these findings confirm our hypotheses that motor phase synchrony is significantly enhanced in auditory compared to visual cortical regions at rest, that these differences are highest across the theta-beta spectrum of frequencies, and that there exist alternating information flow loops across auditory-motor structures as a function of frequency. In our view, this supports the existence of an intrinsic, time-based coupling for low-latency integration of sounds and movements which involves synchronized phasic activity between primary auditory cortex with motor and premotor cortical areas.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".