Predictive and tempo-flexible synchronization to a visual metronome in monkeys
Bibliographic record
Abstract
Predictive and tempo-flexible synchronization to an auditory beat is a fundamental component of human music. To date, only certain vocal learning species show this behaviour spontaneously. Prior research training macaques (vocal non-learners) to tap to an auditory or visual metronome found their movements to be largely reactive, not predictive. Does this reflect the lack of capacity for predictive synchronization in monkeys, or lack of motivation to exhibit this behaviour? To discriminate these possibilities, we trained monkeys to make synchronized eye movements to a visual metronome. We found that monkeys could generate predictive saccades synchronized to periodic visual stimuli when an immediate reward was given for every predictive movement. This behaviour generalized to novel tempi, and the monkeys could maintain the tempo internally. Furthermore, monkeys could flexibly switch from predictive to reactive saccades when a reward was given for each reactive response. In contrast, when humans were asked to make a sequence of reactive saccades to a visual metronome, they often unintentionally generated predictive movements. These results suggest that even vocal non-learners may have the capacity for predictive and tempo-flexible synchronization to a beat, but that only certain vocal learning species are intrinsically motivated to do it.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".