Embodied Meter: Hierarchical Eigenmodes in Music-Induced Movement

Listening to music often is associated with spontaneous body movements frequently synchronized with its periodic structure. The notion of embodied cognition assumes that intelligent behavior does not emerge from mere passive perception, but requires goal-directed interactions between the organism and its environment. According to this view, one could postulate that we may use our bodily movements to help parse the metric structure of music. The aim of this study was to investigate how pulsations on different metrical levels manifest in music-induced movement. Musicians were presented with a piece of instrumental music in 4/4 time, played at four different tempi ranging from 92 to 138 bpm. Participants were instructed to move to the music, and their movements were recorded with a high quality optical motion capture system. Subsequently, signal processing methods and principal components analysis were applied to extract movement primitives synchronized with different metrical levels. We found differences between metric levels in terms of the prevalence of synchronized eigenmovements. For instance, mediolateral movements of arms were found to be frequently synchronized with the tactus level pulse, while rotation and lateral flexion of the upper torso were commonly found to exhibit periods of two and four beats, respectively. The results imply that periodicities on several metric levels are simultaneously present in music-induced movement. This could suggest that the metric structure of music is encoded in these movements.

[1]  W. T. Dempster,et al.  The anthropometry of the manual work space for the seated subject. , 1959, American journal of physical anthropology.

[2]  A. Savitzky,et al.  Smoothing and Differentiation of Data by Simplified Least Squares Procedures. , 1964 .

[3]  Ronald W. Schafer,et al.  Digital Processing of Speech Signals , 1978 .

[4]  M.G. Bellanger,et al.  Digital processing of speech signals , 1980, Proceedings of the IEEE.

[5]  P. Fraisse 6 – Rhythm and Tempo , 1982 .

[6]  R. Jackendoff,et al.  A Generative Theory of Tonal Music , 1985 .

[7]  A. Liberman,et al.  The motor theory of speech perception revised , 1985, Cognition.

[8]  P. J. Green,et al.  Density Estimation for Statistics and Data Analysis , 1987 .

[9]  C. Krumhansl,et al.  Mental representations for musical meter. , 1990, Journal of experimental psychology. Human perception and performance.

[10]  Audra E. Kosh,et al.  Linear Algebra and its Applications , 1992 .

[11]  R. Parncutt A Perceptual Model of Pulse Salience and Metrical Accent in Musical Rhythms , 1994 .

[12]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[13]  Neil P. McAngus Todd,et al.  A Sensory-Motor Theory of Rhythm, Time Perception and Beat Induction , 1999 .

[14]  L. V. Noorden,et al.  Resonance in the Perception of Musical Pulse , 1999 .

[15]  C. Drake,et al.  Tapping in Time with Mechanically and Expressively Performed Music , 2000 .

[16]  William A. Sethares,et al.  Meter and Periodicity in Musical Performance , 2001 .

[17]  Carol L. Krumhansl,et al.  Tapping to Ragtime: Cues to Pulse Finding , 2001 .

[18]  I. Cross Music, Cognition, Culture, and Evolution , 2001, Annals of the New York Academy of Sciences.

[19]  Edward W. Large,et al.  Tracking simple and complex sequences , 2002, Psychological research.

[20]  J. Snyder,et al.  Tapping to Bach: Resonance-Based Modeling of Pulse , 2003 .

[21]  D. Gordon E. Robertson,et al.  Research Methods in Biomechanics , 2004 .

[22]  B. Repp,et al.  Rhythmic movement is attracted more strongly to auditory than to visual rhythms , 2004, Psychological research.

[23]  Aniruddh D. Patel,et al.  The influence of metricality and modality on synchronization with a beat , 2005, Experimental Brain Research.

[24]  Bruno H. Repp,et al.  Rate Limits of On-Beat and Off-Beat Tapping With Simple Auditory Rhythms: 1. Qualitative Observations , 2005 .

[25]  L. Trainor,et al.  Feeling the Beat: Movement Influences Infant Rhythm Perception , 2005, Science.

[26]  Hamish G MacDougall,et al.  Marching to the beat of the same drummer: the spontaneous tempo of human locomotion. , 2005, Journal of applied physiology.

[27]  Harri Valpola,et al.  Denoising Source Separation , 2005, J. Mach. Learn. Res..

[28]  Bruno H. Repp,et al.  Rate Limits of On-Beat and Off-Beat Tapping With Simple Auditory Rhythms: : 2. The Roles of Different Kinds of Accent , 2005 .

[29]  Petri Toiviainen,et al.  An investigation of pre-schoolers' corporeal synchroniza- tion with music , 2006 .

[30]  L. Trainor,et al.  Hearing what the body feels: Auditory encoding of rhythmic movement , 2007, Cognition.

[31]  D. Moelants,et al.  Walking on music. , 2007, Human movement science.

[32]  Neil P. McAngus Todd,et al.  The Contribution of Anthropometric Factors to Individual Differences in the Perception of Rhythm , 2007 .

[33]  L. Trainor,et al.  Vestibular influence on auditory metrical interpretation , 2008, Brain and Cognition.

[34]  Marc Leman,et al.  How potential users of music search and retrieval systems describe the semantic quality of music , 2008 .

[35]  Laurence R. Harris,et al.  The primal role of the vestibular system in determining musical rhythm , 2009, Cortex.

[36]  M. Leman,et al.  The Spatiotemporal Representation of Dance and Music Gestures using Topological Gesture Analysis (TGA) , 2010 .

[37]  S. Baron,et al.  Origins of music , 2011 .

[38]  Seungjin Choi,et al.  Independent Component Analysis , 2009, Handbook of Natural Computing.