Extracting the Beat: An Experience-dependent Complex Integration of Multisensory Information Involving Multiple Levels of the Nervous System
Bibliographic record
Abstract
In a series of studies we have shown that movement (or vestibular stimulation) that is synchronized to every second or every third beat of a metrically ambiguous rhythm pattern biases people to perceive the meter as a march or as a waltz, respectively.Riggle (this volume) claims that we postulate an "innate", "specialized brain unit" for beat perception that is "directly" influenced by vestibular input.In fact, to the contrary, we argue that experience likely plays a large role in the development of rhythmic auditory-movement interactions, and that rhythmic processing in the brain is widely distributed and includes subcortical and cortical areas involved in sound processing and movement.Further, we argue that vestibular and auditory information are integrated at various subcortical and cortical levels along with input from other sensory modalities, and it is not clear which levels are most important for rhythm processing or, indeed, what a "direct" influence of vestibular input would mean.Finally, we argue that vestibular input to sound location mechanisms may be involved, but likely cannot explain the influence of vestibular input on the perception of auditory rhythm.This remains an empirical question for future research.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".