ReviewPLoS computational biology2023
Hebbian learning with elasticity explains how the spontaneous motor tempo affects music performance synchronization.
Review in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Article
- Universal and Cross-Cultural Variations in Audio-Motor Synchronization Between French and Indian Participants.Annals of the New York Academy of Sciences · 2026Article
- Testing sensorimotor timing across age and music experience in a real-world environment.Scientific reports · 2026Article
- Article
- Computational modeling of rhythmic expectations: Perspectives, pitfalls, and prospects.PLoS computational biology · 2025Review
- Pitch biases sensorimotor synchronization to auditory rhythms.Scientific reports · 2025Article
- Musical neurodynamics.Nature reviews. Neuroscience · 2025Review
- Auditory-motor synchronization and perception suggest partially distinct time scales in speech and music.Communications psychology · 2024Article
- Adaptive oscillators support Bayesian prediction in temporal processing.PLoS computational biology · 2023Article
- Dynamic models for musical rhythm perception and coordination.Frontiers in computational neuroscience · 2023Review
- Reliable estimation of internal oscillator properties from a novel, fast-paced tapping paradigm.Scientific reports · 2022Article
- Behavioral and Neural Dynamics of Interpersonal Synchrony Between Performing Musicians: A Wireless EEG Hyperscanning Study.Frontiers in human neuroscience · 2021Article
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
A musician's spontaneous rate of movement, called spontaneous motor tempo (SMT), can be measured while spontaneously playing a simple melody. Data shows that the SMT influences the musician's tempo and synchronization. In this study we present a model that captures these phenomena. We review the results from three previously-published studies: solo musical performance with a pacing metronome tempo that is different from the SMT, solo musical performance without a metronome at a tempo that is faster or slower than the SMT, and duet musical performance between musicians with matching or mismatching SMTs. These studies showed, respectively, that the asynchrony between the pacing metronome and the musician's tempo grew as a function of the difference between the metronome tempo and the musician's SMT, musicians drifted away from the initial tempo toward the SMT, and the absolute asynchronies were smaller if musicians had matching SMTs. We hypothesize that the SMT constantly acts as a pulling force affecting musical actions at a tempo different from a musician's SMT. To test our hypothesis, we developed a model consisting of a non-linear oscillator with Hebbian tempo learning and a pulling force to the model's spontaneous frequency. While the model's spontaneous frequency emulates the SMT, elastic Hebbian learning allows for frequency learning to match a stimulus' frequency. To test our hypothesis, we first fit model parameters to match the data in the first of the three studies and asked whether this same model would explain the data the remaining two studies without further tuning. Results showed that the model's dynamics allowed it to explain all three experiments with the same set of parameters. Our theory offers a dynamical-systems explanation of how an individual's SMT affects synchronization in realistic music performance settings, and the model also enables predictions about performance settings not yet tested.
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