[O9] Oral 9: Timing & Time Perception

11:15 AM - 11:30 AM JST(2:15 AM - 2:30 AM UTC)

[O9-03] Intra- and inter-individual variability in body-brain-behavioral rhythms: a multimodal study with smart wearables

*Antonio Criscuolo¹, Michael Schwartze¹, Sonja Kotz^1,2 (1. Maastricht University (Netherlands), 2. Max Planck Institute for Human Cognitive and Brain Sciences (Germany))

Keywords:

rhythm,body-brain interactions,smart wearable,perception,action

Our sensory environment features a multitude of temporal regularities: there are temporally regular patterns in speech and music, as well as in bodily physiological activity.Is there a precise relationship between individual bodily (e.g., cardiac) and behavioral (e.g., walking) rhythms? Some authors suggested the existence of a cross-frequency architecture characterized by harmonic relations ¹: if your heart beats at 1.25Hz, your breathing rate may be a subharmonic (~.25Hz), while the speaking rate an harmonic (syllable rate: ~2.5Hz). The same may hold for perception and synchronization: sensory processing may prefer input at harmonic relations with your heartbeat, and you may synchronize more easily to music in close proximity to your preferred tempo.In an ongoing study, we are using a combination of smart wearable technology (fitness tracker, mobile EEG, smart glasses), to assess individual breathing, cardiac and brain signals, along with eye movements, pupil dilation and motion tracking. Participants engage in a series of tasks ranging from resting state and listening tasks, to spontaneous tapping, speaking and walking. Within a dynamic system framework ², our goals are to: (i) characterize intra- and inter-individual variability in body-brain-behavioral rhythms; (ii) test the hypothesis of individual cross-frequency architectures in body-behavioral rhythms; (iii) describing if and how dynamic body-brain interactions shape perception and action.Findings promise to advance our understanding of how complex body-brain interactions shape information processing, behavior and adaptation. Promoting individualized and integrative research approaches, our results may further support translational research in clinical populations characterized by altered rhythms (e.g., Parkinson’s).

References
Klimesch, W. The frequency architecture of brain and brain body oscillations: an analysis. European Journal of Neuroscience 48, 2431–2453 (2018).
Criscuolo, A., Schwartze, M. & Kotz, S. A. Cognition through the lens of a body–brain dynamic system. Trends Neurosci (2022) doi:10.1016/J.TINS.2022.06.004.