Neural oscillatory dynamics in joint action: distinct contributions of entrainment and beta modulation to self–other integration
Bibliographic record
Abstract
Abstract Temporal coordination plays a pivotal role in human activities, enabling effective communication and collaboration. Yet, the neural mechanisms supporting this ability remain poorly understood. Recent research suggests that synchronized beta modulation across individual brains, as measured via EEG hyperscanning, may reflect a shared sensorimotor framework underpinning interpersonal synchronization. Building on the idea that self–other integration is a key mechanism in this process, behavioral studies have shown that adopting a partner’s first-person visual perspective (1P) enhances interpersonal coordination, as opposed to the natural second-person perspective (2P). Here, we used the body-swap illusion in immersive virtual reality to directly manipulate embodied perspective and investigate its neural consequences. Specifically, we examined how this illusion modulates beta activity and neural entrainment during joint rhythmic action. Forty participants (N=40), randomly paired into twenty dyads, performed a joint finger-tapping task while wearing head-mounted displays for immersive virtual environments. In coupled conditions, the visual scene was manipulated so that participants viewed their partner’s hand from a 1P perspective, as if it belonged to their own body, or from a natural 2P perspective. In uncoupled control conditions, participants saw their own hand in 1P and 2P, without perceiving any information about their partner’s tapping. EEG hyperscanning revealed that both neural entrainment (measured as the convergence of low-frequency oscillations) and beta modulation (changes in ∼20 Hz power linked to partner- generated movements) occurred in 1P and 2P visually coupled conditions. However, only beta modulation was selectively enhanced when participants experienced their partner’s hand from a 1P perspective. These findings suggest that while neural entrainment reflects a general mechanism for tracking a partner’s rhythmic behavior, beta modulation specifically supports the integration of the other’s effector into one’s bodily representation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".