In expressive music performance, tempo is known to be a fundamental parameter. In this article, we explored effects of changes in musical tempo on performers’ movement articulations. Eight duos (piano – violin) played two pieces at a predefined tempo, after which this start tempo was gradually increased and decreased. Throughout the different performances, we measured acceleration of the violinists’ head and right wrist, together with the downward force applied by their body to the ground surface. We calculated periodicities in downward force using fast Fourier transform (FFT) analyses and tested whether differences occurred across different tempi. Also, we clustered acceleration and force patterns across different tempi using self-organizing maps (SOMs) and k-means clustering. The results show that a continuous change in performance tempo leads to distinct “performance states” with characteristic bodily behavior in terms of periodic body movement and co-articulated gestures, which supports theories of tempo-variant motor control.
BoersmaP.WeeninkD. (2015). Praat: Doing phonetics by computer [Computer Software]. Retrieved from http://www.praat.org/
3.
BurgerB.ThompsonM. R.LuckG.SaarikallioS. H.ToiviainenP. (2014). Hunting for the beat in the body: On period and phase locking in music-induced movement. Frontiers in Human Neuroscience, 8(903). doi:10.3389/fnhum.2014.00903
4.
BurgerB.ToiviainenP. (2013). MoCap Toolbox: A Matlab toolbox for computational analysis of movement data. In BresinR. (Ed.), Proceedings of the 10th Sound and Music Computing Conference (SMC) (pp. 172–178). Stockholm, Sweden: KTH Royal Institute of Technology.
5.
CappelliniG.IvanenkoY. P.PoppeleR. E.LacquanitiF. (2006). Motor patterns in human walking and running. Journal of Neurophysiology, 95(6), 3426–3437.
6.
ClarkeE. (2001). Meaning and the specification of motion in music. Musicae Scientiae, 5(2), 213–234.
7.
ClarkeE. (2005). Ways of listening: An ecological approach to the perception of musical meaning. Oxford, UK: Oxford University Press.
8.
CoorevitsE.MoelantsD. (2016). Tempo in baroque music and dance. Music Perception, 33(5), 523–545.
9.
CyrM.PaulyR. G. (1998). Performing baroque music. Portland, OR: Amadeus Press.
10.
DahlS. (2005). On the beat: Human movement and timing in the production and perception of music (Doctoral Dissertation). KTH School of Computer Science and Communication, Stockholm, Sweden. Retrieved from http://www.sofiadahl.net/pdf/Dahlthesis.pdf
11.
Delevoye-TurrellY.DioneM.AgnerayG. (2014). Spontaneous motor tempo is the easiest pace to act upon for both the emergent and the predictive timing modes. Procedia – Social and Behavioral Sciences, 126, 121–122.
12.
DesainP.HoningH. (1994). Does expressive timing in music performance scale proportionally with tempo?Psychological Research, 56(4), 285–292.
13.
DukeR. A. (1994). When tempo changes rhythm: the effect of tempo on nonmusicians’ perception of rhythm. Journal of Research in Music Education, 42(1), 27–35.
14.
FraisseP. (1982). Rhythm and tempo. In DeutschD. (Ed.), The psychology of music (pp. 149–180). New York: Academic Press.
15.
FuruyaS.AltenmüllerE. (2013). Flexibility of movement organization in piano performance. Frontiers in Human Neuroscience, 7(173). doi:10.3389/fnhum.2013.00173
16.
FuruyaS.AokiT.NakaharaH.KinoshitaH. (2012). Individual differences in the biomechanical effect of loudness and tempo on upper-limb movements during repetitive piano keystrokes. Human Movement Science, 31(1), 26–39.
17.
FuruyaS.KinoshitaH. (2008). Expertise-dependent modulation of muscular and non-muscular torques in multi-joint arm movements during piano keystroke. Neuroscience, 156(2), 390–402.
18.
FuruyaS.SoechtingJ. F. (2012). Speed invariance of independent control of finger movements in pianists. Journal of Neurophysiology, 108(7), 2060–2068.
19.
GabrielssonA. (2001). Timing in music performance and its relations to music experience. In SlobodaJ. (Ed.), Generative processes in music: The psychology of performance, improvisation, and composition (pp.27–51). Oxford, UK: Oxford University Press.
20.
GodøyR. I. (2014). Understanding coarticulation in musical experience. In AramakiM.DerrienO.Kronland-MartinetR.YstadS. (Eds.), Sound, music, and motion. CMMR 2013. Lecture notes in computer science (Vol. 8905, pp. 535–547). Cham, Switzerland: Springer International.
21.
GodøyR. I.JenseniusA. R.NymoenK. (2010). Chunking in music by coarticulation. Acta Acustica united with Acustica, 96(4), 690–700.
22.
GoeblW.PalmerC. (2008). Tactile feedback and timing accuracy in piano performance. Experimental Brain Research, 186(3), 471–479.
23.
GoeblW.PalmerC. (2009, December). Finger motion in piano performance: Touch and tempo. In WilliamonA.PrettyS.BuckR. (Eds.), Proceedings of the International Symposium on Performance Science (pp. 65–70). Retrieved from http://www.performancescience.org/ISPS2009/Proceedings/
24.
GoeblW.PalmerC. (2013). Temporal control and hand movement efficiency in skilled music performance. PLOS One, 8(1), e50901. doi:10.1371/journal.pone.0050901
25.
HardcastleW. J.HewlettN. (1999). Coarticulation: Theory, data and techniques. Cambridge, UK: Cambridge University Press.
26.
HandelS.LawsonG. R. (1983). The contextual nature of rhythmic interpretation. Perception & Psychophysics, 34, 103–210.
27.
HoningH. (2007). Is expressive timing relational invariant under tempo transformation?Psychology of Music, 35(2), 276–285.
28.
IjspeertA. J.NakanishiJ.HoffmannH.PastorP.SchaalS. (2013). Dynamical movement primitives: Learning attractor models for motor behaviors. Neural Computation, 25(2), 328–373.
29.
JonesM. R.BoltzM. (1989). Dynamic attending and responses to time. Psychological Review, 96(3), 459–491.
30.
KelsoJ. A. S. (1995). Dynamic patterns: The self-organization of brain and behavior. Cambridge, MA: MIT Press.
31.
KetchenD. J.ShookC. L. (1996). The application of cluster analysis in strategic management research: An analysis and critique. Strategic Management Journal, 17(6), 441–458.
32.
KohonenT. (1998). The self-organizing map. Neurocomputing, 21(1–3), 1–6.
l’AffilardM. (1702). Principes très faciles pour bien apprendre la musique. Paris, France: Christophe Ballard.
35.
LemanM. (2007). Embodied music cognition and mediation technology. Cambridge, MA: MIT Press.
36.
LemanM. (2016). The expressive moment: How interaction (with music) shapes human empowerment. Cambridge, MA: MIT Press.
37.
LondonJ. (2004). Hearing in time: Psychological aspects of musical meter. New York: Oxford University Press.
38.
LondonJ.BurgerB.ThompsonM.ToiviainenP. (2016). Speed on the dance floor: Auditory and visual cues for musical tempo. Acta Psychologica, 164, 70–80.
39.
MacDougallH. G.MooreS. T. (2005). Marching to the beat of the same drummer: The spontaneous tempo of human locomotion. Journal of Applied Physiology, 99(3), 1164–1173.
40.
MacKenzieC. L.Van EerdD. L. (1990). Rhythmic precision in the performance of piano scales: Motor psychophysics and motor programming. In JeannerodM. (Ed.), Attention and performance: Motor representation and control (pp. 375–408). Hillsdale, NJ: Lawrence Erlbaum.
41.
MoelantsD. (2002). Preferred tempo reconsidered. In StevensC.BurnhamD.McPhersonG.SchubertE.RenwickJ. (Eds.), Proceedings of the 7th International Conference on Music Perception and Cognition (pp. 580–583). Sydney, Australia: Causal Productions.
42.
MoelantsD. (2011). The performance of notes inégales: The influence of tempo, musical structure, and individual performance style on expressive timing. Music Perception, 28(5), 449–460.
43.
Mussa-IvaldiF. A.GiszterS. F.BizziE. (1994). Linear combinations of primitives in vertebrate motor control. Proceedings of the National Academy of Sciences of the United States of America, 91(16), 7534–7538.
44.
NozaradanS.PeretzI.MourauxA. (2012). Selective neuronal entrainment to the beat and meter embedded in a musical rhythm. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 32(49), 17572–17581.
RamsayJ.HookerG.GravesS. (2009). Functional data analysis with R and MATLAB. New York: Springer.
50.
RasamimananaN.BernardinD.WanderleyM.BevilacquaF. (2009). String bowing gestures at varying bow stroke frequencies: A case study. In Sales DiasM.GibetS.WanderleyM. M.BastosR. (Eds.), Gesture-based human-computer interaction and simulation. GW 2007. Lecture notes in computer science (Vol. 5085, pp. 216–226). Berlin, Germany: Springer-Verlag.
51.
ReppB. H. (1994). Relational invariance of expressive microstructure across global tempo changes in music performance: An exploratory study. Psychological Research, 56(4), 269–284.
52.
ReppB. H.DoggettR. (2007). Tapping to a very slow beat: A comparison of musicians and nonmusicians. Music Perception, 24(4), 367–376.
53.
ReppB. H.WindsorW. L.DesainP. (2002). Effects of tempo on the timing of simple musical rhythms. Music Perception, 19(4), 565–593.
54.
SachsC. (1953). Rhythm and tempo: A study in music history. New York: Norton.
55.
SchmidtR. A.LeeT. D. (2011). Central contributions to motor control. In SchmidtR.A.LeeT. D. (Eds.), Motor control and learning: A behavioral emphasis (pp. 131–170). Champaign, IL: Human Kinetics.
56.
ShadmehrR.ThoroughmanK. A. (2000). Learning of action through adaptive combination of motor primitives. Nature, 407(6805), 742–747.
57.
ShafferL. (1984). Timing in solo and duet piano performances. The Quarterly Journal of Experimental Psychology Section A: Human Experimental Psychology, 36(4), 577–595.
58.
ShapiroD. C.ZernickeR. F.GregorR. J.DiestelJ. D. (1981). Evidence for generalized motor programs using gait pattern analysis. Journal of Motor Behavior, 13(1), 33–47.
59.
ShoveP.ReppB. (1995). Musical motion and performance: Theoretical and empirical perspectives. In RinkJ. (Ed.), The practice of performance (pp. 55–83). Cambridge, UK: Cambridge University Press.
60.
ThelenE.SmithL. B. (1998). Dynamic systems theories. In LernerR. M. (Ed.), Theoretical models of human development (5th ed., pp. 563–634). New York: John Wiley & Sons.
61.
ThompsonM.DiapoulisG.JohnsonS.KwanP. Y.HimbergT. (2015, June). Effect of tempo and vision on interpersonal coordination of timing in dyadic performance. In AramakiM.Kronland-MartinetR.YstadS. (Eds.), Proceedings of the 11th International Symposium on CMMR (pp. 16–23). Plymouth, UK: Laboratory of Mechanics and Acoustics.
62.
ToddN. (1992). The dynamics of dynamics: A model of musical expression. The Journal of the Acoustical Society of America, 91(6), 3540–3550.
63.
ToddN. (1995). The kinematics of musical expression. The Journal of the Acoustical Society of America, 97(3), 1940–1949.
64.
ToddN. (1999). Motion in music: A neurobiological perspective. Music Perception, 17(1), 115–126.
65.
ToiviainenP.LuckG.ThompsonM. R. (2010). Embodied meter: Hierarchical eigenmodes in music-induced movement. Music Perception, 28(1), 59–70.
66.
TurveyM. T. (1990). Coordination. The American Psychologist, 45(8), 938–953.
67.
Van DyckE.MoensB.BuhmannJ.DemeyM.CoorevitsE.Dalla BellaS.LemanM. (2015). Spontaneous entrainment of running cadence to music tempo. Sports Medicine - Open, 1(1), 15.
68.
van NoordenL. (1975). Temporal coherence in the perception of tone sequences (Doctoral dissertation). Technische Hogeschool Eindhoven, Eindhoven, the Netherlands. Retrieved from http://alexandria.tue.nl/extra1/PRF2A/7707058.pdf
69.
van NoordenL.MoelantsD. (1999). Resonance in the perception of musical pulse. Journal of New Music Research, 28(1), 43–66.
70.
van VugtF. T.FuruyaS.VathH.JabuschH.-C.AltenmüllerE. (2014). Playing beautifully when you have to be fast: Spatial and temporal symmetries of movement patterns in skilled piano performance at different tempi. Experimental Brain Research, 232(11), 3555–3567.
71.
WarrenW. H. (2006). The dynamics of perception and action. Psychological Review, 113(2), 358–389.
