Abstract
A great deal of research in the neuroscience of music suggests that neural oscillations synchronize with musical stimuli. Although neural synchronization is a well-studied mechanism underpinning expectation, it has even more far-reaching implications for music. In this Perspective, we survey the literature on the neuroscience of music, including pitch, harmony, melody, tonality, rhythm, metre, groove and affect. We describe how fundamental dynamical principles based on known neural mechanisms can explain basic aspects of music perception and performance, as summarized in neural resonance theory. Building on principles such as resonance, stability, attunement and strong anticipation, we propose that people anticipate musical events not through predictive neural models, but because brain–body dynamics physically embody musical structure. The interaction of certain kinds of sounds with ongoing pattern-forming dynamics results in patterns of perception, action and coordination that we collectively experience as music. Statistically universal structures may have arisen in music because they correspond to stable states of complex, pattern-forming dynamical systems. This analysis of empirical findings from the perspective of neurodynamic principles sheds new light on the neuroscience of music and what makes music powerful.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$32.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout





Similar content being viewed by others
References
Zuckerkandl, V. The Sense of Music (Princeton Univ. Press, 1959).
Mehr, S. A. et al. Universality and diversity in human song. Science 366, eaax0868 (2019).
Savage, P. E., Brown, S., Sakai, E. & Currie, T. E. Statistical universals reveal the structures and functions of human music. Proc. Natl Acad. Sci. USA 112, 8987–8992 (2015).
Meyer, L. B. Emotion and Meaning in Music (Univ. Chicago Press, 1956).
Large, E. W. & Kim, J. C. in Foundations in Music Psychology: Theory and Research (eds Rentfrow, P. J. & Levitin, D. J.) 221–263 (MIT Press, 2019).
Huron, D. Sweet Anticipation: Music and the Psychology of Expectation (MIT Press, 2006).
Vuust, P., Heggli, O. A., Friston, K. J. & Kringelbach, M. L. Music in the brain. Nat. Rev. Neurosci. 23, 287–305 (2022).
Buzsáki, G. & Vöröslakos, M. Brain rhythms have come of age. Neuron 111, 922–926 (2023).
Lakatos, P., Gross, J. & Thut, G. A new unifying account of the roles of neuronal entrainment. Curr. Biol. 29, R890–R905 (2019).
Breakspear, M. Dynamic models of large-scale brain activity. Nat. Neurosci. 20, 340–352 (2017).
Hoppensteadt, F. C. & Izhikevich, E. M. Weakly Connected Neural Networks (Springer, 1997).
Kim, J. C. & Large, E. W. Signal processing in periodically forced gradient frequency neural networks. Front. Comput. Neurosci. 9, 152 (2015).
Large, E. W., Almonte, F. V. & Velasco, M. J. A canonical model for gradient frequency neural networks. Phys. Nonlinear Phenom. 239, 905–911 (2010).
Gibson, J. J. The Ecological Approach to Visual Perception: Classic Edition (Houghton Mifflin, 1979).
Haken, H., Kelso, J. A. S. & Bunz, H. A theoretical model of phase transitions in human hand movements. Biol. Cybern. 51, 347–356 (1985).
Large, E. W. & Jones, M. R. The dynamics of attending: how people track time-varying events. Psychol. Rev. 106, 119–159 (1999).
Thompson, E. & Varela, F. J. Radical embodiment: neural dynamics and consciousness. Trends Cogn. Sci. 5, 418–425 (2001).
Kim, J. C. & Large, E. W. Mode locking in periodically forced gradient frequency neural networks. Phys. Rev. E 99, 022421 (2019).
Kim, J. C. & Large, E. W. Multifrequency Hebbian plasticity in coupled neural oscillators. Biol. Cybern. 115, 43–57 (2021).
Pikovsky, A., Rosenblum, M. & Kurths, J. Synchronization: a Universal Concept in Nonlinear Sciences Vol. 2 (Cambridge Univ. Press, 2002).
Izhikevich, E. M. Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting (MIT Press, 2007).
Eguíluz, V. M., Ospeck, M., Choe, Y., Hudspeth, A. J. & Magnasco, M. O. Essential nonlinearities in hearing. Phys. Rev. Lett. 84, 5232–5235 (2000).
Laudanski, J., Coombes, S., Palmer, A. R. & Sumner, C. J. Mode-locked spike trains in responses of ventral cochlear nucleus chopper and onset neurons to periodic stimuli. J. Neurophysiol. 103, 1226–1237 (2010).
Fujioka, T., Trainor, L. J., Large, E. W. & Ross, B. Internalized timing of isochronous sounds is represented in neuromagnetic beta oscillations. J. Neurosci. 32, 1791–1802 (2012).
Lakatos, P., Karmos, G., Mehta, A. D., Ulbert, I. & Schroeder, C. E. Entrainment of neuronal oscillations as a mechanism of attentional selection. Science 320, 110–113 (2008).
Strogatz, S. H. Nonlinear Dynamics and Chaos: with Applications to Physics, Biology, Chemistry, and Engineering (Westview Press, 2014).
Peper, C. L. E., Beek, P. J. & van Wieringen, P. C. W. Coupling strength in tapping a 2:3 polyrhythm. Hum. Mov. Sci. 14, 217–245 (1995).
Tichko, P., Kim, J. C. & Large, E. W. Bouncing the network: a dynamical systems model of auditory–vestibular interactions underlying infants’ perception of musical rhythm. Dev. Sci. 24, e13103 (2021).
Roman, I. R., Roman, A. S., Kim, J. C. & Large, E. W. Hebbian learning with elasticity explains how the spontaneous motor tempo affects music performance synchronization. PLoS Comput. Biol. 19, e1011154 (2023).
Tichko, P. & Large, E. W. Modeling infants’ perceptual narrowing to musical rhythms: neural oscillation and Hebbian plasticity. Ann. N. Y. Acad. Sci. https://doi.org/10.1111/nyas.14050 (2019).
Stepp, N. & Turvey, M. T. On strong anticipation. Cogn. Syst. Res. 11, 148–164 (2010).
Stepp, N. & Turvey, M. T. The muddle of anticipation. Ecol. Psychol. 27, 103–126 (2015).
Voss, H. U. Anticipating chaotic synchronization. Phys. Rev. E 61, 5115–5119 (2000).
Schuster, H. G. & Wagner, P. Mutual entrainment of two limit cycle oscillators with time delayed coupling. Prog. Theor. Phys. 81, 939–945 (1989).
Demos, A. P., Layeghi, H., Wanderley, M. M. & Palmer, C. Staying together: a bidirectional delay-coupled approach to joint action. Cogn. Sci. 43, e12766 (2019).
Patel, A. D. & Iversen, J. R. The evolutionary neuroscience of musical beat perception: the Action Simulation for Auditory Prediction (ASAP) hypothesis. Front. Syst. Neurosci. 8, 57 (2014).
Dubois, D. M. Incursive and hyperincursive systems, fractal machine and anticipatory logic. In AIP Conference Proceedings Vol. 573 (ed. Dubois, D. M.) 437–451 (AIP, 2001).
Roman, I. R., Washburn, A., Large, E. W., Chafe, C. & Fujioka, T. Delayed feedback embedded in perception-action coordination cycles results in anticipation behavior during synchronized rhythmic action: a dynamical systems approach. PLoS Comput. Biol. 15, e1007371 (2019).
Repp, B. H. Sensorimotor synchronization: a review of the tapping literature. Psychon. Bull. Rev. 12, 969–992 (2005).
Jones, M. R. Time, our lost dimension: toward a new theory of perception, attention, and memory. Psychol. Rev. 83, 323–355 (1976).
Correa, Á. & Nobre, A. C. Neural modulation by regularity and passage of time. J. Neurophysiol. 100, 1649–1655 (2008).
Henry, M. J. & Herrmann, B. Low-frequency neural oscillations support dynamic attending in temporal context. Timing Time Percept. 2, 62–86 (2014).
Jones, M. R., Moynihan, H., MacKenzie, N. & Puente, J. Temporal aspects of stimulus-driven attending in dynamic arrays. Psychol. Sci. 13, 313–319 (2002).
Rohenkohl, G. & Nobre, A. C. Alpha oscillations related to anticipatory attention follow temporal expectations. J. Neurosci. 31, 14076–14084 (2011).
Fitzroy, A. B. & Sanders, L. D. Musical meter modulates the allocation of attention across time. J. Cogn. Neurosci. 27, 2339–2351 (2015).
Herbst, S. K., Stefanics, G. & Obleser, J. Endogenous modulation of delta phase by expectation — a replication of Stefanics et al., 2010. Cortex 149, 226–245 (2022).
Ding, N. et al. Temporal modulations in speech and music. Neurosci. Biobehav. Rev. 81, 181–187 (2017).
Harding, E. E., Sammler, D., Henry, M. J., Large, E. W. & Kotz, S. A. Cortical tracking of rhythm in music and speech. Neuroimage 185, 96–101 (2019).
Herrmann, B., Henry, M. J., Grigutsch, M. & Obleser, J. Oscillatory phase dynamics in neural entrainment underpin illusory percepts of time. J. Neurosci. 33, 15799–15809 (2013).
Nozaradan, S., Peretz, I. & Mouraux, A. Selective neuronal entrainment to the beat and meter embedded in a musical rhythm. J. Neurosci. 32, 17572–17581 (2012).
Tal, I. et al. Neural entrainment to the beat: the ‘missing-pulse’ phenomenon. J. Neurosci. 37, 6331–6341 (2017).
Nozaradan, S., Peretz, I., Missal, M. & Mouraux, A. Tagging the neuronal entrainment to beat and meter. J. Neurosci. 31, 10234–10240 (2011).
Snyder, J. S. & Large, E. W. Gamma-band activity reflects the metric structure of rhythmic tone sequences. Cogn. Brain Res. 24, 117–126 (2005).
Giehl, J., Noury, N. & Siegel, M. Dissociating harmonic and non-harmonic phase-amplitude coupling in the human brain. Neuroimage 227, 117648 (2021).
Beek, P. J., Peper, C. E. & Daffertshofer, A. Modeling rhythmic interlimb coordination: beyond the Haken–Kelso–Bunz model. Brain Cogn. 48, 149–165 (2002).
Large, E. W. et al. Dynamic models for musical rhythm perception and coordination. Front. Comput. Neurosci. 17, 1151895 (2023).
Chen, J. L., Penhune, V. B. & Zatorre, R. J. Listening to musical rhythms recruits motor regions of the brain. Cereb. Cortex 18, 2844–2854 (2008).
Grahn, J. A. & Brett, M. Rhythm and beat perception in motor areas of the brain. J. Cogn. Neurosci. 19, 893–906 (2007).
Zalta, A., Petkoski, S. & Morillon, B. Natural rhythms of periodic temporal attention. Nat. Commun. 11, 1051 (2020).
Morillon, B., Schroeder, C. E. & Wyart, V. Motor contributions to the temporal precision of auditory attention. Nat. Commun. 5, 5255 (2014).
Nozaradan, S., Peretz, I. & Keller, P. E. Individual differences in rhythmic cortical entrainment correlate with predictive behavior in sensorimotor synchronization. Sci. Rep. 6, 20612 (2016).
Repp, B. H. Rate limits of sensorimotor synchronization. Adv. Cogn. Psychol. 2, 163–181 (2006).
Treffner, P. J. & Turvey, M. T. Resonance constraints on rhythmic movement. J. Exp. Psychol. Hum. Percept. Perform. 19, 1221–1237 (1993).
Peper, C. L. E., Beek, P. J. & van Wieringen, P. C. W. Multifrequency coordination in bimanual tapping: asymmetrical coupling and signs of supercriticality. J. Exp. Psychol. Hum. Percept. Perform. 21, 1117–1138 (1995).
Aschersleben, G., Gehrke, J. & Prinz, W. Tapping with peripheral nerve block. Exp. Brain Res. 136, 331–339 (2001).
Lerdahl, F. & Jackendoff, R. S. A Generative Theory of Tonal Music (MIT Press, 1983).
Fraisse, P. in The Psychology of Music (ed. Deutsch, D.) 149–180 (Academic, 1982).
Povel, D.-J. & Essens, P. Perception of temporal patterns. Music Percept. 2, 411–440 (1985).
Jacoby, N. & McDermott, J. H. Integer ratio priors on musical rhythm revealed cross-culturally by iterated reproduction. Curr. Biol. 27, 359–370 (2017).
McAuley, J. D., Jones, M. R., Holub, S., Johnston, H. M. & Miller, N. S. The time of our lives: life span development of timing and event tracking. J. Exp. Psychol. Gen. 135, 348–367 (2006).
Palmer, C., Lidji, P. & Peretz, I. Losing the beat: deficits in temporal coordination. Philos. Trans. R. Soc. B 369, 20130405 (2014).
Naveda, L., Gouyon, F., Guedes, C. & Leman, M. Microtiming patterns and interactions with musical properties in Samba music. J. N. Music Res. 40, 225–238 (2011).
Large, E. W., Herrera, J. A. & Velasco, M. J. Neural networks for beat perception in musical rhythm. Front. Syst. Neurosci. 9, 1–14 (2015).
Janata, P., Tomic, S. T. & Haberman, J. M. Sensorimotor coupling in music and the psychology of the groove. J. Exp. Psychol. Gen. 141, 54–75 (2012).
Todd, N. P. & Lee, C. S. The sensory-motor theory of rhythm and beat induction 20 years on: a new synthesis and future perspectives. Front. Hum. Neurosci. 9, 444 (2015).
Haegens, S. & Zion Golumbic, E. Rhythmic facilitation of sensory processing: a critical review. Neurosci. Biobehav. Rev. 86, 150–165 (2018).
Ross, J. M., Iversen, J. R. & Balasubramaniam, R. The role of posterior parietal cortex in beat-based timing perception: a continuous theta burst stimulation study. J. Cogn. Neurosci. 30, 634–643 (2018).
Vuust, P., Dietz, M. J., Witek, M. & Kringelbach, M. L. Now you hear it: a predictive coding model for understanding rhythmic incongruity. Ann. N. Y. Acad. Sci. 1423, 19–29 (2018).
Witek, M. A. G., Clarke, E. F., Wallentin, M., Kringelbach, M. L. & Vuust, P. Syncopation, body-movement and pleasure in groove music. PLoS ONE 9, e94446 (2014).
Matthews, T. E., Stupacher, J. & Vuust, P. The pleasurable urge to move to music through the lens of learning progress. J. Cogn. 6, 55 (2023).
Zalta, A., Large, E. W., Schön, D. & Morillon, B. Neural dynamics of predictive timing and motor engagement in music listening. Sci. Adv. 10, eadi2525 (2024).
Spiech, C. et al. Sensorimotor synchronization increases groove. Preprint at PsyArXiv https://doi.org/10.31234/osf.io/fw7mh (2022).
Spiech, C., Danielsen, A., Laeng, B. & Endestad, T. Oscillatory attention in groove. Cortex 174, 137–148 (2024).
Matthews, T. E., Witek, M. A. G., Thibodeau, J. L. N., Vuust, P. & Penhune, V. B. Perceived motor synchrony with the beat is more strongly related to groove than measured synchrony. Music Percept. 39, 423–442 (2022).
Senn, O. et al. Null effect of perceived drum pattern complexity on the experience of groove. PLoS ONE 19, e0311877 (2024).
London, J., Polak, R. & Jacoby, N. Rhythm histograms and musical meter: a corpus study of Malian percussion music. Psychon. Bull. Rev. 24, 474–480 (2017).
London, J. Hearing in Time (Oxford Univ. Press, 2012).
Hannon, E. E. & Trehub, S. E. Metrical categories in infancy and adulthood. Psychol. Sci. 16, 48–55 (2005).
Nave-Blodgett, J. E., Snyder, J. S. & Hannon, E. E. Hierarchical beat perception develops throughout childhood and adolescence and is enhanced in those with musical training. J. Exp. Psychol. Gen. 150, 314–339 (2021).
Goldberg, D. What’s the meter of Elenino Horo? Rhythm and timing in drumming for a Bulgarian folk dance. Anal. Approaches World Music 7, 69–107 (2020).
Tichko, P., Kim, J. C. & Large, E. W. A dynamical, radically embodied, and ecological theory of rhythm development. Front. Psychol. 13, 653696 (2022).
Ullal-Gupta, S., Vanden Bosch der Nederlanden, C. M., Tichko, P., Lahav, A. & Hannon, E. E. Linking prenatal experience to the emerging musical mind. Front. Syst. Neurosci. 7, 48 (2013).
Doelling, K. B. & Poeppel, D. Cortical entrainment to music and its modulation by expertise. Proc. Natl Acad. Sci. USA. 112, E6233–E6242 (2015).
Trainor, L. J., Gao, X., Lei, J., Lehtovaara, K. & Harris, L. R. The primal role of the vestibular system in determining musical rhythm. Cortex 45, 35–43 (2009).
Phillips-Silver, J. & Trainor, L. J. Psychology: feeling the beat: movement influences infant rhythm perception. Science 308, 1430 (2005).
Phillips-Silver, J. & Trainor, L. J. Vestibular influence on auditory metrical interpretation. Brain Cogn. 67, 94–102 (2008).
Zamm, A., Wellman, C. & Palmer, C. Endogenous rhythms influence interpersonal synchrony. J. Exp. Psychol. Hum. Percept. Perform. 42, 611–616 (2016).
Palmer, C., Spidle, F., Koopmans, E. & Schubert, P. Ears, heads, and eyes: when singers synchronise. Q. J. Exp. Psychol. 72, 2272–2287 (2019).
Scheurich, R., Zamm, A. & Palmer, C. Tapping into rate flexibility: musical training facilitates synchronization around spontaneous production rates. Front. Psychol. 9, 458 (2018).
Zamm, A., Wang, Y. & Palmer, C. Musicians’ natural frequencies of performance display optimal temporal stability. J. Biol. Rhythms 33, 432–440 (2018).
Zamm, A. et al. Synchronizing MIDI and wireless EEG measurements during natural piano performance. Brain Res. 1716, 27–38 (2019).
Zamm, A. et al. Behavioral and neural dynamics of interpersonal synchrony between performing musicians: a wireless EEG hyperscanning study. Front. Hum. Neurosci. 15, 717810 (2021).
Palmer, C. & Demos, A. P. Are we in time? How predictive coding and dynamical systems explain musical synchrony. Curr. Dir. Psychol. Sci. 31, 147–153 (2022).
Fredrickson-Hemsing, L., Ji, S., Bruinsma, R. & Bozovic, D. Mode-locking dynamics of hair cells of the inner ear. Phys. Rev. E 86, 021915 (2012).
Camalet, S., Duke, T., Jülicher, F. & Prost, J. Auditory sensitivity provided by self-tuned critical oscillations of hair cells. Proc. Natl Acad. Sci. USA 97, 3183–3188 (2000).
Jülicher, F., Andor, D. & Duke, T. Physical basis of two-tone interference in hearing. Proc. Natl Acad. Sci. USA 98, 9080–9085 (2001).
Lerud, K. D., Kim, J. C., Almonte, F. V., Carney, L. H. & Large, E. W. A canonical oscillator model of cochlear dynamics. Hear. Res. 380, 100–107 (2019).
Langner, G. Periodicity coding in the auditory system. Hear. Res. 60, 115–142 (1992).
Lerud, K. D., Almonte, F. V., Kim, J. C. & Large, E. W. Mode-locking neurodynamics predict human auditory brainstem responses to musical intervals. Hear. Res. 308, 41–49 (2014).
Shamma, S. A. Speech processing in the auditory system I: the representation of speech sounds in the responses of the auditory nerve. J. Acoust. Soc. Am. 78, 1612–1621 (1985).
Licklider, J. C. R. A duplex theory of pitch perception. Experientia 7, 128–134 (1951).
de Cheveigné, A. & Pressnitzer, D. The case of the missing delay lines: synthetic delays obtained by cross-channel phase interaction. J. Acoust. Soc. Am. 119, 3908–3918 (2006).
Cartwright, J. H. E., González, D. L. & Piro, O. Nonlinear dynamics of the perceived pitch of complex sounds. Phys. Rev. Lett. 82, 5389–5392 (1999).
Schouten, J. F., Ritsma, R. J. & Cardozo, B. L. Pitch of the residue. J. Acoust. Soc. Am. 34, 1418–1424 (1962).
Huang, C. & Rinzel, J. A neuronal network model for pitch selectivity and representation. Front. Comput. Neurosci. 10, 57 (2016).
Meddis, R. & O’Mard, L. P. Virtual pitch in a computational physiological model. J. Acoust. Soc. Am. 120, 3861–3869 (2006).
Bigand, E., Parncutt, R. & Lerdahl, F. Perception of musical tension in short chord sequences: the influence of harmonic function, sensory dissonance, horizontal motion, and musical training. Percept. Psychophys. 58, 125–141 (1996).
von Helmholtz, H. L. F. On the Sensations of Tone as a Physiological Basis for the Theory of Music (Dover, 1954).
McDermott, J. H., Lehr, A. J. & Oxenham, A. J. Individual differences reveal the basis of consonance. Curr. Biol. 20, 1035–1041 (2010).
Tramo, M. J., Cariani, P. A., Delgutte, B. & Braida, L. D. Neurobiological foundations for the theory of harmony in Western tonal music. Ann. N. Y. Acad. Sci. 930, 92–116 (2001).
Shapira Lots, I. & Stone, L. Perception of musical consonance and dissonance: an outcome of neural synchronization. J. R. Soc. Interface 5, 1429–1434 (2008).
Lee, K. M., Skoe, E., Kraus, N. & Ashley, R. Selective subcortical enhancement of musical intervals in musicians. J. Neurosci. 29, 5832–5840 (2009).
Ronconi, L., Oosterhof, N. N., Bonmassar, C. & Melcher, D. Multiple oscillatory rhythms determine the temporal organization of perception. Proc. Natl Acad. Sci. USA 114, 13435–13440 (2017).
Singer, W. & Gray, C. M. Visual feature integration and the temporal correlation hypothesis. Annu. Rev. Neurosci. 18, 555–586 (1995).
McDermott, J. H., Schultz, A. F., Undurraga, E. A. & Godoy, R. A. Indifference to dissonance in native Amazonians reveals cultural variation in music perception. Nature 535, 547–550 (2016).
Lahdelma, I. & Eerola, T. Cultural familiarity and musical expertise impact the pleasantness of consonance/dissonance but not its perceived tension. Sci. Rep. 10, 8693 (2020).
Burns, E. M. in The Psychology of Music 2nd edn (ed. Deutsch, D.) 215–264 (Academic, 1999).
Kathios, N., Sachs, M. E., Zhang, E., Ou, Y. & Loui, P. Generating new musical preferences from multilevel mapping of predictions to reward. Psychol. Sci. 35, 34–54 (2024).
McPherson, M. J. et al. Perceptual fusion of musical notes by native Amazonians suggests universal representations of musical intervals. Nat. Commun. 11, 2786 (2020).
Burns, E. M. & Ward, W. D. Categorical perception — phenomenon or epiphenomenon: evidence from experiments in the perception of melodic musical intervals. J. Acoust. Soc. Am. 63, 456–468 (1978).
Rakowski, A. Intonation variants of musical intervals in isolation and in musical contexts. Psychol. Music 18, 60–72 (1990).
Siegel, J. A. & Siegel, W. Categorical perception of tonal intervais: musicians can’t tellsharp fromflat. Percept. Psychophys. 21, 399–407 (1977).
Schellenberg, E. G. & Trehub, S. E. Children’s discrimination of melodic intervals. Dev. Psychol. 32, 1039–1050 (1996).
Large, E. W. in Nonlinear Dynamics in Human Behavior (eds Huys, R. & Jirsa, V. K.) 193–211 (Springer, 2010).
Schellenberg, E. G. & Trehub, S. E. Natural musical intervals: evidence from infant listeners. Psychol. Sci. 7, 272–277 (1996).
Goldstein, J. L. An optimum processor theory for the central formation of the pitch of complex tones. J. Acoust. Soc. Am. 54, 1496–1516 (1973).
Larson, S. The problem of prolongation in tonal music: terminology, perception, and expressive meaning. J. Music Theory 41, 101–136 (1997).
Kim, J. C. A dynamical model of pitch memory provides an improved basis for implied harmony estimation. Front. Psychol. 8, 666 (2017).
Lerdahl, F. Tonal Pitch Space (Oxford Univ. Press, 2001).
Krumhansl, C. L. Cognitive Foundations of Musical Pitch (Oxford Univ. Press, 1990).
de Clercq, T. & Temperley, D. A corpus analysis of rock harmony. Pop. Music 30, 47–70 (2011).
Krumhansl, C. L., Louhivuori, J., Toiviainen, P., Järvinen, T. & Eerola, T. Melodic expectation in Finnish spiritual folk hymns: convergence of statistical, behavioral, and computational approaches. Music Percept. 17, 151–195 (1999).
Temperley, D. Music and Probability (MIT Press, 2007).
Leman, M. An auditory model of the role of short-term memory in probe-tone ratings. Music Percept. 17, 481–509 (2000).
Bigand, E., Delbé, C., Poulin-Charronnat, B., Leman, M. & Tillmann, B. Empirical evidence for musical syntax processing? Computer simulations reveal the contribution of auditory short-term memory. Front. Syst. Neurosci. 8, 94 (2014).
Krumhansl, C. L. & Kessler, E. J. Tracing the dynamic changes in perceived tonal organization in a spatial representation of musical keys. Psychol. Rev. 89, 334–368 (1982).
Castellano, M. A., Krumhansl, C. L. & Bharucha, J. J. Tonal hierarchies in the music of North India. J. Exp. Psychol. Gen. 113, 394–412 (1984).
Large, E. W., Kim, J. C., Flaig, N. K., Bharucha, J. J. & Krumhansl, C. L. A neurodynamic account of musical tonality. Music Percept. 33, 319–331 (2016).
Loui, P., Wessel, D. L. & Kam, C. L. H. Humans rapidly learn grammatical structure in a new musical scale. Music Percept. 27, 377–388 (2010).
Nieminen, S., Istók, E., Brattico, E. & Tervaniemi, M. The development of the aesthetic experience of music: preference, emotions, and beauty. Music Sci. 16, 372–391 (2012).
Hunter, P. G., Glenn Schellenberg, E. & Stalinski, S. M. Liking and identifying emotionally expressive music: age and gender differences. J. Exp. Child Psychol. 110, 80–93 (2011).
Fritz, T. et al. Universal recognition of three basic emotions in music. Curr. Biol. 19, 573–576 (2009).
Balkwill, L.-L. & Thompson, W. F. A cross-cultural investigation of the perception of emotion in music: psychophysical and cultural cues. Music Percept. 17, 43–64 (1999).
Chordia, P. & Rae, A. in Computer Music Modeling and Retrieval. Sense of Sounds (eds Kronland-Martinet, R. et al.) 110–124 (Springer, 2008).
Large, E. W., Lerud, K., Kim, J. C., & Harrell, D. GrFNN Toolbox. GitHub https://github.com/MusicDynamicsLab/GrFNNToolbox (2024).
Razdan, A. S. & Patel, A. D. Rhythmic consonance and dissonance: perceptual ratings of rhythmic analogs of musical pitch intervals and chords. In Proc. 14th International Conference on Music Perception and Cognition 807–812 (Causal Productions, 2016).
Lerousseau, J. P., Trébuchon, A., Morillon, B. & Schön, D. Frequency selectivity of persistent cortical oscillatory responses to auditory rhythmic stimulation. J. Neurosci. 41, 7991–8006 (2021).
Snyder, J. S., Gordon, R. L. & Hannon, E. E. Theoretical and empirical advances in understanding musical rhythm, beat and metre. Nat. Rev. Psychol. 3, 449–462 (2024).
Nave-Blodgett, J. E., Snyder, J. S. & Hannon, E. E. Auditory superiority for perceiving the beat level but not measure level in music. J. Exp. Psychol. Hum. Percept. Perform. 47, 1516–1542 (2021).
Kotz, S. A., Ravignani, A. & Fitch, W. T. The evolution of rhythm processing. Trends Cogn. Sci. 22, 896–910 (2018).
Ravignani, A., Delgado, T. & Kirby, S. Musical evolution in the lab exhibits rhythmic universals. Nat. Hum. Behav. 1, 0007 (2016).
Schubert, E. Modeling perceived emotion with continuous musical features. Music Percept. 21, 561–585 (2004).
Pliego, A., Vega, R., Gómez, R., Reyes-Lagos, J. J. & Soto, E. A transient decrease in heart rate with unilateral and bilateral galvanic vestibular stimulation in healthy humans. Eur. J. Neurosci. 54, 4670–4681 (2021).
Rajagopalan, A. et al. Understanding the links between vestibular and limbic systems regulating emotions. J. Nat. Sci. Biol. Med. 8, 11–15 (2017).
Harding, E. E. et al. Musical emotion categorization with vocoders of varying temporal and spectral content. Trends Hear. 27, 1–19 (2023).
Harding, E. E. et al. Vocal and musical emotion perception, voice cue discrimination, and quality of life in cochlear implant users with and without acoustic hearing. Q. J. Exp. Psychol.https://doi.org/10.1177/17470218251316499 (2025).
Cannon, J. & Kaplan, T. Inferred representations behave like oscillators in dynamic Bayesian models of beat perception. J. Math. Psychol. 122, 102869 (2024).
Zemlianova, K., Bose, A. & Rinzel, J. Dynamical mechanisms of how an RNN keeps a beat, uncovered with a low-dimensional reduced model. Sci. Rep. 14, 26388 (2024).
Gámez, J., Mendoza, G., Prado, L., Betancourt, A. & Merchant, H. The amplitude in periodic neural state trajectories underlies the tempo of rhythmic tapping. PLoS Biol. 17, e3000054 (2019).
Cook, P., Rouse, A., Wilson, M. & Reichmuth, C. A California sea lion (Zalophus californianus) can keep the beat: motor entrainment to rhythmic auditory stimuli in a non vocal mimic. J. Comp. Psychol. https://doi.org/10.1037/a0032345 (2013).
Rajendran, V. G., Marquez, J. P., Prado, L. & Merchant, H. Monkeys have rhythm. Preprint at bioRxiv https://doi.org/10.1101/2024.03.11.584468 (2024).
Kerrebroeck, B. V., Wanderley, M. M., Demos, A. P. & Palmer, C. Human-machine trios show different tempo changes in musical tasks. In Proc. Annual Meeting of the Cognitive Science Society Vol. 46 (eds Samuelson, L. K. et al.) 650–656 (Cognitive Science Society, 2024).
Butler, B. E. & Lomber, S. G. Functional and structural changes throughout the auditory system following congenital and early-onset deafness: implications for hearing restoration. Front. Syst. Neurosci. 7, 92 (2013).
Author information
Authors and Affiliations
Contributions
The authors all researched data for the article, provided substantial contributions to discussion of its content, wrote the article, and reviewed and edited the manuscript before submission.
Corresponding author
Ethics declarations
Competing interests
E.W.L. is founder of, and owns stock in, Oscilloscape, Inc. (dba Oscillo Biosciences). J.C.K. is currently a paid employee of, and owns stock in, Oscilloscape, Inc. E.W.L. and J.C.K. are authors of patents owned by Oscilloscape, Inc. The subject matter of the current paper is not directly related to the business interests of Oscilloscape, and no products of Oscilloscape are discussed in this paper.
Peer review
Peer review information
Nature Reviews Neuroscience thanks Joel Snyder and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Glossary
- Anticipation
-
The process by which a system responds to an expected event before the event occurs.
- Attraction
-
The evolving state of a dynamical system towards a more stable state, such as an orbit.
- Attunement
-
The adaptation of neural circuits to the environment, enhancing response stability and flexibility.
- Beat
-
In Western music theory, a simple (often periodic) rhythm that can be perceived within another rhythm.
- Bistable systems
-
Systems with two stable states.
- Consonance
-
The perceived pleasantness of a musical interval.
- Critical oscillation
-
An oscillation poised at a bifurcation point, the transition between damped and self-sustained oscillation.
- Dissonance
-
The perceived unpleasantness of a musical interval.
- Dynamic attending
-
Entrainment of attentional processes with external temporal signals to focus on specific events in time.
- Embodiment
-
A state of the brain and/or body that has a lawful, physical relationship to external events (for example, sounds) determined by physical principles. This embodied representation contrasts with the notion of a symbolic representation, in which symbols have arbitrary relationships to external events.
- Enculturation
-
The process by which individuals learn, adopt and maintain their cultural traditions. Musical enculturation occurs through exposure to the structure of music of one’s native culture, including tuning, scale and metre.
- Expectation
-
The prediction of events and event timing based on context and prior experience. Musical expectations are violated when unexpected events occur or when (expected) events occur at unexpected times.
- Groove
-
Embodied sense of rhythmic movement or the desire to move in response to a patterned sequence of sounds such as music.
- Harmonic intervals
-
The pitch difference between simultaneous musical tones.
- Harmony
-
Two or more complementary notes played or sung at the same time. The chords that accompany a melody.
- Hebbian learning
-
An increase in synaptic efficacy that arises from a presynaptic cell’s repeated and persistent stimulation of a postsynaptic cell. Hebbian learning in oscillatory neural networks occurs only when the neural oscillators resonate to each other (phase- or mode-lock).
- Implied harmony
-
The (simultaneous) harmony implied by a (sequential) melody, without being explicitly present.
- Just intonation
-
A tuning system in which intervals are tuned to whole number frequency ratios (such as 3:2 and 4:3).
- Limit cycle
-
A closed orbit (self-sustained oscillation) on which a dynamical system remains.
- Melodic interval
-
The pitch difference between two tones that are sounded one after another (as in a melody).
- Metre
-
In Western music theory, nested patterns of strong and weak beats perceived in a rhythm.
- Missing fundamental
-
The pitch perceived as the first harmonic, when the first harmonic is absent from the waveform.
- Mode-locking
-
Synchronization in an integer (non-1:1) ratio.
- Natural frequency
-
The inherent rate at which a system oscillates when not subjected to external forces, which is determined by its physical characteristics.
- Nonlinear oscillator
-
An oscillator for which nonlinear processes determine the internal states and the response to external signals.
- Nonlinear resonance
-
Phase and amplitude response of a nonlinear oscillator to stimulation.
- Oscillation
-
A motion characterized by a stable frequency and amplitude that repeat over time, such as a sinusoidal pattern.
- Pattern forming
-
The orderly outcome of self-organization as observed in biology, chemistry and physics.
- Phase-locking
-
Synchronization in 1:1 frequency ratio where the phase difference between two systems (or a system and an external stimulus) is maintained constant.
- Pitch
-
That aspect of auditory sensation that allows us to order tones on a musical scale.
- Predictive coding of music
-
Theory that states the brain deploys a predictive model based on prior experience to minimize prediction errors, through a recursive Bayesian process, when listening to music.
- Pulse
-
The most perceptually salient beat; that is, the beat to which a listener would tap when synchronizing with a rhythm.
- Rhythm
-
The complex pattern of timing and accentuation.
- Stability
-
A state or an orbit of a dynamical system is stable if the system is attracted to it.
- Strong anticipation
-
Anticipatory behaviour in interactions with the environment that emerges owing to transmission delays (delay coupling).
- Synchronization
-
Phase and/or frequency locking of coupled oscillators to one another or to external stimulation. Used interchangeably with entrainment.
- Syncopation
-
The displacement of a musical accent from strong beats to weak beats.
- Tonal hierarchy
-
The structured organization of tones in which specific tones are perceived as more stable than others, and less stable tones are attracted towards more stable ones.
- Tonality
-
The perception of stability and attraction relationships among the pitches in musical work.
- Transmission delays
-
A time delay in communication between neural areas, biophysically explained by long-range axonal transmission of information.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Harding, E.E., Kim, J.C., Demos, A.P. et al. Musical neurodynamics. Nat. Rev. Neurosci. 26, 293–307 (2025). https://doi.org/10.1038/s41583-025-00915-4
Accepted:
Published:
Issue date:
DOI: https://doi.org/10.1038/s41583-025-00915-4