Rhythmic complexity and predictive coding: A novel approach to modeling rhythm and meter perception in music

Frontiers in Psychology

Volumn 5, Issue SEP, 2014, Pages

  Vuust, Peter ^a,b   Witek, Maria A G ^a,b  

^a AARHUS UNIVERSITY HOSPITAL   (Denmark)

^b ROYAL ACADEMY OF MUSIC   (Denmark)

Author keywords

Meter; Pleasure; Predictive coding; Rhythm; Rhythmic complexity

Indexed keywords

EID: 84907192551     PISSN: None     EISSN: 16641078     Source Type: Journal    
DOI: 10.3389/fpsyg.2014.01111     Document Type: Review

References (163)

1. Agawu, K. (2003). Representing African Music: Postcolonial Notes, Queries, Positions. Taylor & Francis.
2. Altenmuller, E. (2001). How many music centers are in the brain? Annals of the New York Academy of Sciences 930, 273-280.
3. Barnes, R., and Jones, M.R. (2000). Expectancy, attention and time. Cognitive Psychology 41, 254- 311.
4. Bastos, A.M., Usrey, W.M., Adams, R.A., Mangun, G.R., Fries, P., and Friston, K.J. (2012). Canonical microcircuits for predictive coding. Neuron 76, 695-711.
5. Bengtsson, S.L., Ulle´n, F., Henrik Ehrsson, H., Hashimoto, T., Kito, T., Naito, E., Forssberg, H., and Sadato, N. (2009). Listening to rhythms activates motor and premotor cortices. Cortex 45, 62-71. doi: 10.1016/j.cortex.2008.07.002.
6. Berlyne, D.E. (1971). Aesthetics and psychobiology. East Norwalk, CT: Appleton-Century-Crofts.
7. Berniker, M., and Ko¨rding, K. (2008). Estimating the sources of motor errors for adaptation and generalization. Nature Neuroscience 11, 1454-1461.
8. Born, R.T., Tsui, J.M., and Pack, C.C. (2010). "Temporal dynamics of motion integration," in Dynamics of visual motion processing, eds. G. Masson & U.J. Ilg. (New York: Springer), 37-54.
9. Brochard, R., Abecasis, D., Potter, D., Ragot, R., and Drake, C. (2003). The 'tick-tock' of our internal clock: Direct brain evidence of subjective accents in isochronous sequences. Psychological Science 14, 362-366.
10. Brown, H., Friston, K.J., and Bestmann, S. (2011). Active inference, attention, and motor preparation. Frontiers in psychology 2. doi: 10.3389/fpsyg.2011.00218.
11. Burr, D., Tozzi, A., and Morrone, M.C. (2007). Neural mechanisms for timing visual events are spatially selective in real-world coordinates. Nature Neuroscience 10, 423-425.
12. Butler, M.J. (2006). Unlocking the groove: Rhythm, meter, and musical design in electronic dance music. Bloomington: Indiana University Press.
13. Cabeza, R., and Nyberg, L. (2000). Imaging cognition II: An empirical review of 275 PET and fMRI studies. Journal of Cognitive Neuroscience 12, 1-47.
14. Chapin, H.L., Zanto, T., Jantzen, K.J., Kelso, S.J.A., Steinberg, F., and Large, E.W. (2010). Neural responses to complex auditory rhythms: The role of attending. Frontiers in Psychology 1, 1-18.
15. Chen, J.L., Penhune, V.B., and Zatorre, R.J. (2008a). Listening to musical rhythms recruits motor regions of the brain Cerebral Cortex 18, 2844-2854.
16. Chen, J.L., Zatorre, R.J., and Penhune, V.B. (2008b). Moving on time: brain network for auditory motor synchronization is modulated by rhythm complexity and musical training. Journal of Cognitive Neuroscience 20.
17. Cicchini, G.M., Arrighi, R., Cecchetti, L., Giusti, M., and Burr, D.C. (2012). Optimal encoding of interval timing in expert percussionists. The Journal of Neuroscience 32, 1056-1060.
18. Clark, A. (2008). Supersizing the mind: Embodiment, action, and cognitive extension. Oxford University Press, USA.
19. Clark, A. (2013). Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral and Brain Sciences 36, 181-204.
20. Clark, A., and Chalmers, D. (1998). The extended mind. Analysis 58, 7-19.
21. Clarke, E.F. (1999). "Rhythm and timing in music," in The psychology of music, ed. D. Deutsch. 2nd ed (New York: Academic Press).
22. Clayton, M., Sager, R., and Will, U. (2004). In time with the music: The concept of entrainment and its significance for ethnomusicology. European Meetings in Ethnomusicology II (ESEM counterpoint 1), 3-75.
23. Danielsen, A. (2006). Presense and pleasure. The funk grooves of James Brown and Parliament. Middletown, Connecticut: Wesleyan University Press.
24. Danielsen, A. (2010). Musical rhythm in the age of digital reproduction. Farnham: Ashgate.
25. Demos, A.P., Chaffin, R., Begosh, K.T., Daniels, J.R., and Marsh, K.L. (2012). Rocking to the beat: Effects of music and partner's movements on spontaneous interpersonal coordination. Journal of Experimental Psychology: General 141, 49.
26. Desain, P., and Honing, H. (1999). Computational model of beat induction: The rule-based approach. Journal of New Music Research 28, 29-42.
27. Dixon, S. (2001). Automatic extraction of tempo and beat from expressive performances. Journal of New Music Research 30, 39-58.
28. Elliott, M.T., Wing, A.M., and Welchman, A.E. (2014). Moving in time: Bayesian causal inference explains movement coordination to auditory beats. Proceedings of the Royal Society B: Biological Sciences 281, 20140751.
29. Feldman, H., and Friston, K.J. (2010). Attention, uncertainty, and free-energy. Frontiers in human neuroscience 4.
30. Fiebach, C.J., and Schubotz, R.I. (2006). Dybamic anticipatory processing of hierarchical sequential events: A common role for Broca's area and ventral premotor cortex across domains? Cortex 42, 499-502.
31. Fiez, J.A. (1997). Phonology, semantics, and the role of the left inferior prefrontal cortex. Human Brain Mapping 5, 79-83.
32. Fitch, W.T., and Rosenfeld, A.J. (2007). Perception and production of syncopated rhythms. Music Perception 25, 43-58.
33. Fraisse, P. (1963). The psychology of time. New York: Harper & Row
34. Fraisse, P. (1982). "Rhythm and tempo," in The psychology of music, ed. D. Deutsch. 1st ed (New York: Academic Press).
35. Fraisse, P. (1984). Perception and estimation of time. Annual Review of Psychology 35, 1-37.
36. Friedman, D., Cycowicz, Y.M., and Gaeta, H. (2001). The novelty P3: an event-related brain potential (ERP) sign of the brain's evaluation of novelty. Neuroscience and biobehavioral reviews 25, 355-373.
37. Friston, K. (2002). Beyond phrenology: What can neuroimaging tell us about distributed circuitry? Annual Review of Neuroscience 25, 221-250.
38. Friston, K. (2003). Learning and inference in the brain. Neural Networks 16, 1325-1352.
39. Friston, K. (2005). A theory of cortical responses. Philosophical Transactions of the Royal Society B: Biological Sciences 360, 815-836.
40. Friston, K. (2008). Hierarchical models in the brain. PLoS Computational Biology 4, e1000211.
41. Friston, K. (2010). The free-energy principle: a unified brain theory? Nature Reviews Neuroscience 11, 127-138.
42. Friston, K., Daunizeau, J., Kilner, J., and Kiebel, S.J. (2010). Action and behavior: a free-energy formulation. Biological Cybernetics 102, 227-260.
43. Fujioka, T., Zendel, B.R., and Ross, B. (2010). Endogenous neuromagnetic activity for mental hierarchy of timing. The Journal of Neuroscience 30, 3458-3466.
44. Gebauer, L., Kringelbach, M.L., and Vuust, P. (2012). Ever-changing cycles of musical pleasure: The role of dopamine and anticipation. Psychomusicology 22, 152-167.
45. Gooch, C.M., Wiener, M., Hamilton, A.C., and Coslett, H.B. (2011). Temporal discrimination of sub-and suprasecond time intervals: A voxel-based lesion mapping analysis. Frontiers in integrative neuroscience 5.
46. Grahn, J.A., and Brett, M. (2007). Rhythm and beat perception in motor areas of the brain. Journal of Cognitive Neuroscience 19, 893-906. doi: 10.1162/jocn.2007.19.5.893.
47. Grahn, J.A., and Mcauley, J.D. (2009). Neural bases of individual differences in beat perception. Neuroimage 47, 1894-1903. doi: 10.1016/j.neuroimage.2009.04.039.
48. Grahn, J.A., and Rowe, J.B. (2009). Feeling the beat: premotor and striatal interactions in musicians and nonmusicians during beat perception. The Journal of Neuroscience 29, 7540-7548. doi: 10.1523/jneurosci.2018-08.2009.
49. Grahn, J.A., and Rowe, J.B. (2012). Finding and feeling the musical beat: Striatal dissociations between detection and prediction of regularity. Cerebral Cortex 23, 913-921. doi: 10.1093/cercor/bhs083.
50. Greenwald, J. (2002). Hip-hop drumming: The rhyme may define, but the groove makes you move. Black Music Research Journal 22, 259-271. doi: 10.2307/1519959.
51. Hohwy, J., Roepstorff, A., and Friston, K. (2008). Predictive coding explains binocular rivalry: an epistemological review. Cognition 108, 687-701.
52. Honing, H. (2012). Without it no music: beat induction as a fundamental musical trait. Annals of the New York Academy of Sciences 1252, 85-91. doi: 10.1111/j.1749-6632.2011.06402.x.
53. Honing, H. (2013). "Structure and interpretation of rhythm in music," in The psychology of music ed. D. Deutsch. 3rd ed (Amsterdam: Academic Press), 369-404.
54. Huron, D. (2006). Sweet anticipation: Music and the psychology of expectation. Cambridge, MA: The MIT Press.
55. Iyer, V. (2002). Embodied mind, situated cognition, and expressive microtiming in African-American music. Music Perception 19, 387-414.
56. Jahanshahi, M., Dirnberger, G., Fuller, R., and Frith, C. (2000). The role of the dorsolateral prefrontal cortex in random number generation: a study with positron emission tomography. Neuroimage 12, 713-725.
57. Janata, P., Tomic, S.T., and Haberman, J.M. (2012). Sensorimotor coupling in music and the psychology of the groove. Journal of Experimental Psychology: General 141, 54-75. doi: 10.1037/a0024208.
58. Johnston, A., Arnold, D.H., and Nishida, S. (2006). Spatially localized distortions of event time. Current Biology 16, 472-479.
59. Jones, M.R. (2004). "Attention and timing," in Ecological psychoacoustics, ed. J.G. Neuoff. (Amsterdam: Elsevier Academic Press), 49-85.
60. Jones, M.R. (2009). "Musical time," in The Oxford handbook of music psychology, eds. S. Hallam, I. Cross & M. Thaut. (New York: Oxford University Press), 81-92.
61. Kalender, B., Trehub, S.E., and Schellenberg, E.G. (2013). Cross-cultural differences in meter perception. Psychological Research 77, 196-203.
62. Keller, P.E. (2008). "Joint action in music performance," in Enacting intersubjectivity: A cognitive and social perspective to the study of interactions, eds. F. Morganti, A. Carassa & G. Riva. (Amterdam: IOS Press), 205-221.
63. Kleinschmidt, A., Buchel, C., Zeki, S., and Frackowiak, R.S. (1998). Human brain activity during spontaneous reversing perception of ambiguous figures. Proceedings of the Royal Society of London B: Biological Sciences 265, 2427-2433.
64. Koelsch, S., Schro¨ger, E., and Tervaniemi, M. (1999). Superior pre-attentive auditory processing in musicians. Neuroreport 10, 1309-1313.
65. Konvalinka, I., Vuust, P., Roepstorff, A., and Frith, C.D. (2010). Follow you, follow me: continuous mutual prediction and adaptation in joint tapping. The Quarterly Journal of Experimental Psychology 63, 2220-2230.
66. Ko¨rding, K.P., Beierholm, U., Ma, W.J., Quartz, S., Tenenbaum, J.B., and Shams, L. (2007). Causal inference in multisensory perception. PloS one 2, e943.
67. Kung, S.-J., Chen, J.L., Zatorre, R.J., and Penhune, V.B. (2013). Interacting cortical and basal ganglia networks underlying finding and tapping to the musical beat. Journal of Cognitive Neuroscience 25, 401-420.
68. Ladinig, O., Honing, H., Haden, G., and Winkler, I. (2009). Probing attentive and preattentive emergent meter in adult listeners without extensive musical training. Music Perception 26, 377-386.
69. Large, E.W. (2000). On synchronizing movements to music. Human Movement Science 19, 527-566. doi: http://dx.doi.org/10.1016/S0167-9457%2800%2900026-9.
70. Large, E.W., and Jones, M.R. (1999). The dynamics of attending: How people track time-varying events. Psychological Review 106, 119-159. doi: http://dx.doi.org/10.1037/0033-295X.106.1.119.
71. Large, E.W., and Kolen, J.F. (1994). Resonance and the perception of musical meter. Connection Science 6, 177-208.
72. Lee, D.N. (1998). Guiding movement by coupling taus. Ecological Psychology 10, 221-250.
73. Lee, S.-H., Blake, R., and Heeger, D.J. (2005). Travelling waves of activity in primary visual cortex during binocular rivalry. Nature Neuroscience 8, 22.
74. Leman, M. (2007). Embodied music cognition and mediation technology. Cambridge, MA: MIT Press.
75. Leopold, D.A., and Logothetis, N.K. (1999). Multistable phenomena: changing views in perception. Trends in cognitive sciences 3, 254-264.
76. Lerdahl, F., and Jackendoff, R. (1983). A generative theory of tonal music. Cambridge, Mass; London: MIT Press.
77. Lewis, P., and Miall, R. (2003). Brain activation patterns during measurement of sub-and supra second intervals. Neuropsychologia 41, 1583-1592.
78. Lewis, P., and Miall, R. (2006). A right hemispheric prefrontal system for cognitive time measurement. Behavioural Processes 71, 226-234.
79. London, J. (2012). Hearing in time. New York: Oxford University Press.
80. Longuet-Higgins, H.C., and Lee, C. (1984). The rhythmic interpretation of monophonic music. Music Perception 1, 424-440.
81. Lumer, E.D., Friston, K.J., and Rees, G. (1998). Neural correlates of perceptual rivalry in the human brain. Science 280, 1930-1934.
82. Madison, G. (2001). Variability in isochronous tapping: higher order dependencies as a function of intertap interval. Journal of Experimental Psychology: Human Perception and Performance 27, 411.
83. Madison, G. (2006). Experiencing groove induced by music: Consistency and phenomenology. Music Perception 24, 201-208.
84. Madison, G., Gouyon, F., Ulle´n, F., and Ho¨rnstro¨m, K. (2011). Modeling the tendency for music to induce movement in humans: First correlations with low-level audio descriptors across music genres. Journal of Experimental Psychology: Human Perception and Performance 37, 1578-1594. doi: 10.1037/a0024323.
85. Maloney, L.T., and Mamassian, P. (2009). Bayesian decision theory as a model of human visual perception: testing Bayesian transfer. Visual Neuroscience 26, 147-155.
86. Margulis, E.H., and Beatty, A.P. (2008). Musical style, psychoaesthetics, and prospects for entropy as an analytical tool. Computer Music Journal 32, 64-78.
87. Mayville, J.M., Fuchs, A., Ding, M., Cheyne, D., Deecke, L., and Kelso, J.a.S. (2001). Event-related changes in neuromagnetic activity associated with syncopation and synchronization timing tasks. Human Brain Mapping 14, 65-80.
88. Mcauley, J.D., and Jones, M.R. (2003). Modeling effects of rhythmic context on perceived duration: a comparison of interval and entrainment approaches to short-interval timing. Journal of Experimental Psychology: Human Perception and Performance 29, 1102.
89. Meyer, L.B. (1956). Emotion and meaning in music. Chicago and London: University of Chicago Press.
90. Molnar-Szakacz, I., and Overy, K. (2006). Music and mirror neurons: From motion to 'e'motion. Social Cognitive and Affective Neuroscience 1, 235-241.
91. Morrone, M.C., Ross, J., and Burr, D. (2005). Saccadic eye movements cause compression of time as well as space. Nature Neuroscience 8, 950-954.
92. Mumford, D. (1992). On the computational architecture of the neocortex. Biological Cybernetics 66, 241-251.
93. Mumford, D. (1994). Neuronal architectures for pattern-theoretic problems. Large-Scale Theories of the Cortex. Cambridge, MA: MIT Press.
94. Mu¨nte, T.F., Kohlmetz, C., Nager, W., and Altenmu¨ller, E. (2001). Superior auditory spatial tuning in conductors. Nature 409, 580.
95. Na¨a¨ta¨nen, R. (1992). Attention and brain function. Hillsdale, N.J.: Erlbaum.
96. Na¨a¨ta¨nen, R., Paaviliainen, P., Alho, K., Reinikainen, K., and Sams, M. (1987). The mismatch negativity to intensity changes in an auditory stimulus sequence. Electroencephalography and Clinical Neurophysiology 40, 125-131.
97. Na¨a¨ta¨nen, R., Tervaniemi, M., Sussman, E.S., Paavilainen, P., and Winkler, I. (2001). 'Primitive intelligence' in the auditory cortex. Trends in Neurosciences 24, 283-288.
98. Nagarajan, S.S., Blake, D.T., Wright, B.A., Byl, N., and Merzenich, M.M. (1998). Practice-related improvements in somatosensory interval discrimination are temporally specific but generalize across skin location, hemisphere, and modality. The Journal of Neuroscience 18, 1559-1570.
99. Nikjeh, D.A., Lister, J.J., and Frisch, S.A. (2008). Hearing of note: an electrophysiologic and psychoacoustic comparison of pitch discrimination between vocal and instrumental musicians. Psychophysiology 45, 994-1007.
100. North, A.C., and Hargreaves, D.J. (1995). Subjective complexity, familiarity, and liking for popular music. Psychomusicology 14, 77-93.
101. North, A.C., and Hargreaves, D.J. (1997). "Experimental aesthetics and everyday music listening," in The social psychology of music, eds. D.J. Hargreaves & A.C. North. (Oxford: Oxford University Press).
102. Nozaradan, S., Peretz, I., Missal, M., and Mouraux, A. (2011). Tagging the neuronal entrainment to beat and meter. Journal of Neuroscience 31, 10234 -10240.
103. Orr, M.G., and Ohlsson, S. (2005). Relationship between complexity and liking as a function of expertise. Music Perception 22, 583-611.
104. Overy, K., and Molnar-Szakacs, I. (2009). Being together in time: Musical experience and the mirror neuron system. Music Perception 26, 489-504.
105. Owen, A.M., Mcmillan, K.M., Laird, A.R., and Bullmore, E. (2005). N-back working memory paradigm: A meta-analysis of normative functional neuroimaging studies. Human Brain Mapping 25, 46-59.
106. Paavilainen, P., Karlsson, M.-L., Reinikainen, K., and Na¨a¨ta¨nen, R. (1989). Mismatch negativity to change in spatial location of an auditory stimulus. Electroencephalography and Clinical Neurophysiology 73, 129-141.
107. Paavilainen, P., Simola, J., Jaramillo, M., Na¨a¨ta¨nen, R., and Winkler, I. (2001). Preattentive extraction of abstract feature conjunctions from auditory stimulation as reflected by the mismatch negativity (MMN). Psychophysiology 38, 359-365.
108. Pack, C.C., and Born, R.T. (2001). Temporal dynamics of a neural solution to the aperture problem in visual area MT of macaque brain. Nature 409, 1040-1042.
109. Palmer, C., and Krumhansl, C.L. (1990). Mental representation for musical meter. Journal of Experimental Psychology: Human Perception and Performance 16, 728-741.
110. Parncutt, R. (1994). A perceptual model of pulse salience and metrical accent in musical rhythms. Music Perception 11, 409-464.
111. Pearce, M.T., Ruiz, M.H., Kapasi, S., Wiggins, G.A., and Bhattacharya, J. (2010). Unsupervised statistical learning underpins computational, behavioural and neural manifestations of musical expectation. Neuroimage 50, 302-313.
112. Pearce, M.T., and Wiggins, G.A. (2006). Expectation in melody: The influence of context and learning. Music Perception 23, 377-405.
113. Pecenka, N., and Keller, P.E. (2011). The role of temporal prediction abilities in interpersonal sensorimotor synchronization. Experimental Brain Research 211, 505-515.
114. Phillips-Silver, J., Aktipis, A.C., and Bryant, G. (2010). The ecology of entrainment: Foundations of coordinated rhythmic movement. Music Perception 28, 3-14.
115. Phillips-Silver, J., and Trainor, L.J. (2005). Feeling the beat: Movement influences infant rhythm perception. Science 308, 1430-1430.
116. Phillips-Silver, J., and Trainor, L.J. (2007). Hearing what the body feels: Auditory encoding of rhythmic movement. Cognition 105, 533-546.
117. Phillips-Silver, J., and Trainor, L.J. (2008). Vestibular influence on auditory metrical interpretation. Brain and Cognition 67, 94-102. doi: 10.1016/j.bandc.2007.11.007.
118. Pressing, J. (2002). Black Atlantic rhythm: Its computational and transcultural foundations. Music Perception 19, 285-310.
119. Raij, T., Mcevoy, L., Ma¨kela¨, J.P., and Hari, R. (1997). Human auditory cortex is activated by omissions of auditory stimuli. Brain Research 745, 134-143.
120. Rao, R.P., and Ballard, D.H. (1999). Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects. Nature Neuroscience 2, 79-87.
121. Repp, B. (2005). Sensorimotor synchronization: A review of the tapping literature. Psychonomic Bulletin & Review 12, 969-992. doi: 10.3758/bf03206433.
122. Repp, B., and Keller, P.E. (2008). Sensorimotor synchronisation with adaptively timed sequences. Human Movement Science 27, 423-456.
123. Robbins, H. (Year). "An empirical Bayes approach to statistics", in: Third Berkeley Symposium on Mathematical Statistics and Probability: Contributions to the theory of Statistics: University of California Press), 157-163.
124. Roepstorff, A., Niewohner, J., and Beck, S. (2010). Enculturing brains through patterned practices. Neural Networks 23, 1051-1059.
125. Rohrmeier, M.A., and Koelsch, S. (2012). Predictive information processing in music cognition. A critical review. International Journal of Psychophysiology 83, 164-175.
126. Rubin, E. (1918). Synsoplevede Figurer. Studier i psykologisk analyse. Part 1. Copenhagen: Gyldendal.
127. Sadeghi, H., Allard, P., Prince, F., and Labelle, H. (2000). Symmetry and limb dominance in able bodied gait: a review. Gait and Posture 12, 34-45.
128. Sams, M., Paavilainen, P., Alho, K., and Na¨a¨ta¨nen, R. (1985). Auditory frequency discrimination and event-related potentials. Electroencephalography and Clinical Neurophysiology 62, 437-448.
129. Schaffrath, H. (1995). "The Essen Folksong Collection", (ed.) D. Huron. Stanford, CA: Center for Computer-Assisted Research in the Humanities.
130. Schmidt, R., Fitzpatrick, P., Caron, R., and Mergeche, J. (2011). Understanding social motor coordination. Human Movement Science 30, 834-845.
131. Schogler, B., Pepping, G.-J., and Lee, D.N. (2008). TauG-guidance of transients in expressive musical performance. Experimental Brain Research.
132. Schultz, W. (2007). Behavioral dopamine signals. Trends in Neurosciences 30, 203-210.
133. Schultz, W., Preuschoff, K., Camerer, C., Hsu, M., Fiorillo, C.D., Tobler, P.N., and Bossaerts, P. (2008). Explicit neural signals reflecting reward uncertainty. Philosophical Transactions of the Royal Society B: Biological Sciences 363, 3801-3811.
134. Simons, J.S., Scho¨lvinck, M.L., Gilbert, S.J., Frith, C.D., and Burgess, P.W. (2006). Differential components of prospective memory?: Evidence from fMRI. Neuropsychologia 44, 1388-1397.
135. Song, C., Simpson, A.J., Harte, C.A., Pearce, M.T., and Sandler, M.B. (2013). Syncopation and the Score. PloS one 8, e74692.
136. Stephan, K.E., Harrison, L.M., Kiebel, S.J., David, O., Penny, W.D., and Friston, K.J. (2007). Dynamic causal models of neural system dynamics: current state and future extensions. Journal of biosciences 32, 129-144.
137. Sterzer, P., Russ, M.O., Preibisch, C., and Kleinschmidt, A. (2002). Neural correlates of spontaneous direction reversals in ambiguous apparent visual motion. Neuroimage 15, 908-916.
138. Stupacher, J., Hove, M.J., Novembre, G., Schu¨tz-Bosbach, S., and Keller, P.E. (2013). Musical groove modulates motor cortex excitability: A TMS investigation. Brain and Cognition 82, 127-136.
139. Teki, S., Grube, M., and Griffiths, T.D. (2011a). A unified model of time perception accounts for duration-based and beat-based timing mechanisms. Frontiers in integrative neuroscience 5.
140. Teki, S., Grube, M., Kumar, S., and Griffiths, T.D. (2011b). Distinct neural substrates of duration based and beat-based auditory timing. The Journal of Neuroscience 31, 3805-3812.
141. Temperley, D. (2004). An Evalutation system for metrical models. Computer Music Journal 28.
142. Temperley, D. (2007). Music and probability. Cambridge, MA: MIT Press.
143. Temperley, D. (2009). A unified probabilistic model for polyphonic music analysis. Journal of New Music Research 38, 3-18.
144. Temperley, D. (2010). Modeling common-practice rhythm. Music Perception 27, 355-376.
145. Temperley, D., and Sleator, D. (1999). Modeling meter and harmony: A preference rule approach. Computer Music Journal 23, 10-27.
146. Trainor, L.J., Mcdonald, K.L., and Alain, C. (2002). Automatic and controlled processing of melodic contour and interval information measured by electrical brain activity. Journal of Cognitive Neuroscience 14, 430-442.
147. Trost, W., and Vuilleumier, P. (2013). "Rhythmic entrainment as a mechanism for emotion induction by music: A neurophysiological perspective," in The emotional power of music: multidisciplinary perspectives on musical arousal, expression, and social control, eds. T. Cochrane, B. Fantini & K.R. Scherer. (New York: Oxford University Press), 213-225.
148. Van Zuijen, T.L., Sussman, E., Winkler, I., Na¨a¨ta¨nen, R., and Tervaniemi, M. (2004). Grouping of sequential sounds-an event-related potential study comparing musicians and nonmusicians. Journal of Cognitive Neuroscience 16, 331-338.
149. Verschure, P.F., Voegtlin, T., and Douglas, R.J. (2003). Environmentally mediated synergy between perception and behaviour in mobile robots. Nature 425, 620-624.
150. Volk, A. (2008). The study of syncopaiton using inner metric analysis: Linking theoretical and experimental analysis of metre in music. Journal of New Music Research 37, 259-273.
151. Vuust, P., Brattico, E., Seppa¨nen, M., Na¨a¨ta¨nen, R., and Tervaniemi, M. (2012a). Practiced musical style shapes auditory skills. Annals of the New York Academy of Sciences 1252, 139-146.
152. Vuust, P., Brattico, E., Seppa¨nen, M., Na¨a¨ta¨nen, R., and Tervaniemi, M. (2012b). The sound of music: Differentiating musicians using a fast, musical multi-feature mismatch negativity paradigm. Neuropsychologia 50, 1432-1443.
153. Vuust, P., and Frith, C.D. (2008). Anticipation is the key to understanding music and the effects of music on emotion. Behavioral and Brain Sciences 31, 599-600.
154. Vuust, P., Ostergaard, L., Pallesen, K.J., Bailey, C., and Roepstorff, A. (2009). Predictive coding of music-brain responses to rhythmic incongruity. Cortex 45, 80-92.
155. Vuust, P., Pallesen, K.J., Bailey, C., Van Zuijen, T.L., Gjedde, A., Roepstorff, A., and Østergaard, L. (2005). To musicians, the message is in the meter: pre-attentive neuronal responses to incongruent rhythm are left-lateralized in musicians. Neuroimage 24, 560-564.
156. Vuust, P., Roepstorff, A., Wallentin, M., Mouridsen, K., and Østergaard, L. (2006). It don't mean a thing...: Keeping the rhythm during polyrhythmic tension, activates language areas (BA47). Neuroimage 31, 832-841.
157. Vuust, P., Wallentin, M., Mouridsen, K., Østergaard, L., and Roepstorff, A. (2011). Tapping polyrhythms in music activates language areas. Neuroscience Letters 494, 211-216.
158. Waadeland, C.H. (2001). "It don't mean a thing if it ain't got that swing" - Simulating expressive timing by modulated movements. Journal of New Music Research 30, 23-37.
159. Winkler, I., Karmos, G., and Na¨a¨ta¨nen, R. (1996). Adaptive modeling of the unattended acoustic environment reflected in the mismatch negativity event-related potential. Brain Research 742, 239-252.
160. Witek, M.A.G., Clarke, E.F., Kringelbach, M.L., and Vuust, P. (in press). Effects of polyphonic context, instrumentation and metric location on syncopation in music. Music Perception.
161. Witek, M.A.G., Clarke, E.F., Wallentin, M., Kringelbach, M.L., and Vuust, P. (2014). Syncopation, body-movement and pleasure in groove music. PloS one 9, e94446. doi: 10.1371/journal.pone.0094446.
162. Wundt, W. (1874). Grundzuge der physiologischen psychologie. Leipzig: Englemann.
163. Yu, A.J. (2007). Adaptive behavior: Humans act as Bayesian learners. Current Biology 17, R977-R980.