Infant attention to rhythmic audiovisual synchrony is modulated by stimulus properties
Bibliographic record
Abstract
Musical interactions are a common and multimodal part of an infant's daily experiences. Infants hear their parents sing while watching their lips move and see their older siblings dance along to music playing over the radio. Here, we explore whether 8- to 12-month-old infants associate musical rhythms they hear with synchronous visual displays by tracking their dynamic visual attention to matched and mismatched displays. Visual attention was measured using eye-tracking while they attended to a screen displaying two videos of a finger tapping at different speeds. These videos were presented side by side while infants listened to an auditory rhythm (high or low pitch) synchronized with one of the two videos. Infants attended more to the low-pitch trials than to the high-pitch trials but did not display a preference for attending to the synchronous hand over the asynchronous hand within trials. Exploratory evidence, however, suggests that tempo, pitch, and rhythmic complexity interactively engage infants' visual attention to a tapping hand, especially when that hand is aligned with the auditory stimulus. For example, when the rhythm was complex and the auditory stimulus was low in pitch, infants attended to the fast hand more when it aligned with the auditory stream than to misaligned trials. These results suggest that the audiovisual integration in rhythmic non-speech contexts is influenced by stimulus properties.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".