Feeling the beat: an investigation into the neural correlates of vibrotactile beat perception
Bibliographic record
Abstract
The current study investigates our ability to perceive and synchronize movements to the beat of rhythms presented through vibrations to the skin. I compared EEG recordings and tapping accuracy to rhythms that varied in modality: auditory-only, vibrotactile, multimodal (vibrotactile and auditory) and complexity: metronome and simple rhythms. The neural data showed that signals localized to the primary auditory cortex showed a larger spike in power at beat frequencies presentation of auditory compared to vibrotactile rhythms. Tapping ability was found to be lowest in vibrotactile compared to auditory and multimodal rhythms. Auditory only and multimodal rhythms did not show a statistical difference in the neural or tapping data. Tapping variability predicted neural entrainment, such that more variable tapping elicited a more entrained neural signal in primary auditory cortex, and less in pre-motor regions. In conclusion, these results show how the temporal processing of rhythm is superior in auditory modalities.
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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) | 0.002 | 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".