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Musical interaction is influenced by underlying predictive models and musical expertise
Ole A Heggli1, Ivana Konvalinka2, Morten L Kringelbach3,4
1Center for Music in the Brain, Aarhus University & Royal Academy of Music, Aarhus, Denmark. ole.heggli@clin.au.dk.
Scientific Reports
|August 1, 2019
Summary
Musicians synchronize tapping better with shared rhythm context models (RCMs). Even with dissimilar predictive models, skilled musicians quickly recover synchronization, with drummers showing unique adaptation patterns.
Area of Science:
- Cognitive Neuroscience
- Music Psychology
- Human-Computer Interaction
Background:
- Musical interaction offers insights into human coordination and predictive modeling.
- Polyrhythms can create distinct rhythmic contexts while maintaining isochronous behavior.
Purpose of the Study:
- To investigate how shared versus non-shared rhythmic context models (RCMs) affect synchronization in joint finger tapping tasks.
- To explore the adaptability of musicians' synchronization strategies when predictive models differ.
Main Methods:
- Utilized polyrhythms to design joint finger tapping tasks with shared and non-shared RCMs.
- Recruited 22 highly skilled musicians performing in 11 dyads.
- Analyzed synchronization behavior and directionality patterns.
Main Results:
- Synchronization was significantly impaired at the start of trials with non-shared RCMs compared to shared RCMs.
- Musicians demonstrated rapid recovery of synchronization despite holding dissimilar predictive models.
- Drummer dyads exhibited distinct synchronization patterns, indicating expertise-influenced strategies.
Conclusions:
- Holding different predictive models negatively impacts initial synchronization in joint musical tasks.
- Musicians possess robust adaptive capabilities to regain synchronization with dissimilar RCMs.
- Instrument-specific expertise influences synchronization strategies during dyadic musical performance.
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