Presentation Information
[P1-33]Revealing rhythm categorization in human brain activity
*Tomas Lenc1,2, Francesca M. Barbero2, Nori Jacoby3,4, Rainer Polak5,6, Manuel Varlet7, Nicola Molinaro1,8, Sylvie Nozaradan2,9 (1. Basque Center on Cognition, Brain and Language (BCBL), Donostia-San Sebastian (Spain), 2. Institute of Neuroscience (IoNS), University of Louvain (UCLouvain), 1348 Louvain-la-Neuve (Belgium), 3. Computational Auditory Perception Group, Max Planck Institute for Empirical Aesthetics, Grüneburgweg 14, 60322 Frankfurt am Main (Germany), 4. Department of Psychology, Cornell University, Ithaca, NY 14853 (United States of America), 5. RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo (Norway), 6. Department of Musicology, University of Oslo (Norway), 7. The MARCS Institute for Brain, Behaviour & Development, Western Sydney University, Sydney (Australia), 8. Ikerbasque, Basque Foundation for Science, 48009 Bilbao (Spain), 9. International Laboratory for Brain, Music and Sound Research (BRAMS), Montreal (Canada))
Keywords:
Musical behavior,Representational similarity analysis,Perceptual categorization,Rhythm perception and production,Electroencephalography
Human experience of musical rhythm is fundamentally determined by the ability to map the infinite variety of possible rhythmic sensory inputs onto a finite set of internal rhythm categories. However, the underlying nature and neural mechanisms of rhythm categorization are still not well understood. Here, we present a novel approach allowing to reveal rhythm categories from brain activity using scalp electroencephalography (EEG) combined with frequency-domain and representational similarity analysis (fRSA).
Using this approach, we provide first direct evidence for neural categorization of rhythm in humans. We show that EEG activity elicited by a set of two-interval rhythms goes beyond mere tracking of acoustic temporal features and, instead, reflects two discrete categories that encompass small integer ratio rhythms reported in prior behavioral work. Importantly, we show that these neural categories are remarkably similar to the categorical structure captured in sensorimotor reproduction of the same stimuli, yet they can emerge automatically, without a related explicit task, thus independently from motor, instructional or decisional biases.
To go a step further, we investigated whether the automaticity of this phenomenon could be related to an early emergence of rhythm categories in the subcortical auditory regions based on lower-level physiological properties of neural assemblies. To test this, we used a functional localizer allowing to isolate EEG activity originating from higher-level cortical vs. subcortical auditory sources. Preliminary results indicate that while the categorical representations observed at the cortical level cannot be fully explained by subcortical responses, rudiments of rhythm categorization might already emerge in the early stages of the ascending auditory pathway.
Together, these results and methodological advances constitute a critical step towards elucidating the fundamental constituents and biological substrates of musical rhythm, particularly the interplay between universal neurobiological constraints shared across individuals and species, and the plasticity of categorization processes developing through life experience.
Using this approach, we provide first direct evidence for neural categorization of rhythm in humans. We show that EEG activity elicited by a set of two-interval rhythms goes beyond mere tracking of acoustic temporal features and, instead, reflects two discrete categories that encompass small integer ratio rhythms reported in prior behavioral work. Importantly, we show that these neural categories are remarkably similar to the categorical structure captured in sensorimotor reproduction of the same stimuli, yet they can emerge automatically, without a related explicit task, thus independently from motor, instructional or decisional biases.
To go a step further, we investigated whether the automaticity of this phenomenon could be related to an early emergence of rhythm categories in the subcortical auditory regions based on lower-level physiological properties of neural assemblies. To test this, we used a functional localizer allowing to isolate EEG activity originating from higher-level cortical vs. subcortical auditory sources. Preliminary results indicate that while the categorical representations observed at the cortical level cannot be fully explained by subcortical responses, rudiments of rhythm categorization might already emerge in the early stages of the ascending auditory pathway.
Together, these results and methodological advances constitute a critical step towards elucidating the fundamental constituents and biological substrates of musical rhythm, particularly the interplay between universal neurobiological constraints shared across individuals and species, and the plasticity of categorization processes developing through life experience.