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The role of the motor system in the processing of rhythmic complexity: a critical review

The role of the motor system in the processing of rhythmic complexity: a critical review

Name:Francisco, Cossavella

School/Affiliation:Laboratorio de Inteligencia Artificial Aplicada, Departamento de Computación, Universidad de Buenos Aires, Buenos Aires, Argentina, Instituto de Investigación en Ciencias de la Computación (ICC), CONICET-Universidad de Buenos Aires, Buenos Aires, Argentina

Co-Authors:Martín A., Miguel; Diego, Fernández Slezak

Virtual or In-person:Virtual


The desire to move to music appears to be a human universal. This behavioral response seems to be supported by a tight coupling of auditory and motor networks, even in the absence of overt movement. The prevailing theories explain this phenomenon either in terms of passive brain network entrainment to musical periodicity or motor system involvement in predictive processing. Both explanations recognize the role of rhythmic complexity in modulating motor activity. However, the precise nature of the relationship between rhythmic complexity and motor activity remains unclear. In this work, we conducted an fMRI literature review to evaluate this relationship. Out of 110 reviewed articles, 24 reported findings ranging from non-existent to linear or inverted-U-shaped relations. Underlying these findings, we encountered significant heterogeneity in the measurement and conceptualization of rhythmic complexity. We provide a summary of the associations found, the approaches to measuring rhythmic complexity and the different types of tasks and stimuli used. We conclude that, in order to move forward, more agreement is needed regarding measures and notions of complexity. Additionally, we note that the entirety of the research reviewed was conducted by teams from the global north, primarily on WEIRD populations, and only a small subset utilized ecologically valid stimuli. To this end, we are in the process of developing an ecological and perceptually validated natural music dataset. Our aim is to utilize this dataset not only for assessing the processing of rhythmic complexity across cultures but also for crafting a rhythmic complexity metric suitable for audio formats.

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