EMBODIED METER: HIERARCHICAL EIGENMODES IN MUSIC-INDUCED MOVEMENT

被引:157
作者
Toiviainen, Petri [1 ]
Luck, Geoff [1 ]
Thompson, Marc R. [1 ]
机构
[1] Univ Jyvaskyla, Dept Mus, Jyvaskyla 40014, Finland
来源
MUSIC PERCEPTION | 2010年 / 28卷 / 01期
关键词
music; movement; synchronization; meter; embodiment; SIMPLE AUDITORY RHYTHMS; MOTOR THEORY; RATE LIMITS; ON-BEAT; PERCEPTION; TIME; RESONANCE;
D O I
10.1525/MP.2010.28.1.59
中图分类号
J6 [音乐];
学科分类号
摘要
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.
引用
收藏
页码:59 / 70
页数:12
相关论文
共 39 条
[1]  
[Anonymous], 1976, Linear Algebra and Its Applications
[2]  
Arom Simha., 1991, AFRICAN POLYPHONY PO, DOI [10.1017/cbo9780511518317, DOI 10.1017/CBO9780511518317, 10.1017/CBO9780511518317]
[3]  
Brown S, 2000, ORIGINS OF MUSIC, P3
[4]  
Cross I., 2003, The cognitive neuroscience of music, P42, DOI DOI 10.1093/ACPROF:OSO/9780198525202.003.0004
[5]   THE ANTHROPOMETRY OF THE MANUAL WORK SPACE FOR THE SEATED SUBJECT [J].
DEMPSTER, WT ;
GABEL, WC ;
FELTS, WJL .
AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY, 1959, 17 (04) :289-317
[6]  
Drake C, 2000, MUSIC PERCEPT, V18, P1
[7]  
Eerola T., 2006, 9 INT C MUS PERC COG
[8]  
Fraisse P., 1982, The psychology of music, P148
[9]   The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis [J].
Huang, NE ;
Shen, Z ;
Long, SR ;
Wu, MLC ;
Shih, HH ;
Zheng, QN ;
Yen, NC ;
Tung, CC ;
Liu, HH .
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 1998, 454 (1971) :903-995
[10]  
Hyvärinen A, 2001, INDEPENDENT COMPONENT ANALYSIS: PRINCIPLES AND PRACTICE, P71