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Center for Music in the Brain

Our publications

Heinonen-Guzejev, M., Kliuchko, M., Vuust, P., Tervaniemi, M. & Brattico, E. (2017). Studying noise sensitivity on the brain level. Abstract from 12th ICBEN Congress on Noise as a Public Health Problem, Zurich, Switzerland.

Heinonen-Guzejev, M., Kliuchko, M., Vuust, P., Tervaniemi, M., Brattico, E., Shepherd, D., Heikkilä, K., Dirks, K. N., Hautus, M. J., Welch, D. & McBride, D. (2018). Studying the origins of noise sensitivity - negative affect or biological factors. 521-525. Paper presented at Euronoise, Heraklion, Greece. http://www.euronoise2018.eu/component/contentbuilder/details/11/110/euronoise-2018-10-health-effects-of-sound?Itemid=256&start=0

Heggli, O. A., Vuust, P. & Kringelbach, M. L. (2019). Please Please Me! The Pleasure of Music in the Brain. In The Routledge Companion to Music, Mind and Well-being (pp. 205-218). Routledge.

Heggli, O. A., Konvalinka, I., Kringelbach, M. L. & Vuust, P. (2019). Musical interaction is influenced by underlying predictive models and musical expertise. Scientific Reports, 9(1), Article 11048. https://doi.org/10.1038/s41598-019-47471-3

Heggli, O. A., Cabral, J., Konvalinka, I., Vuust, P. & Kringelbach, M. L. (2019). A Kuramoto model of self-other integration across interpersonal synchronization strategies. PLOS Computational Biology, 15(10), Article e1007422. https://doi.org/10.1371/journal.pcbi.1007422

Heggli, O. A., Konvalinka, I., Cabral, J., Brattico, E., Kringelbach, M. & Vuust, P. (2021). Transient brain networks underlying interpersonal strategies during synchronized action. Social Cognitive and Affective Neuroscience, 16(1-2), 19-30. Advance online publication. https://doi.org/10.1093/scan/nsaa056

Heggli, O. A., Konvalinka, I., Kringelbach, M. L. & Vuust, P. (2021). A Metastable Attractor Model of Self-Other Integration (MEAMSO) in Rhythmic Synchronization. Philosophical Transactions of the Royal Society B: Biological Sciences, 376(1835), Article 20200332. https://doi.org/10.1098/rstb.2020.0332

Heggli, O. A., Stupacher, J. & Vuust, P. (2021). Diurnal fluctuations in musical preference. Royal Society Open Science, 8(11), Article 210885. https://doi.org/10.1098/rsos.210885

Haumann, N. T. (2015). An Introduction to Cognitive Musicology: Historical-Scientific Presuppositions in the Psychology of Music. In Dansk Musikforskning Online Særnummer, 2015: Musik- og hjerneforskning http://www.danishmusicologyonline.dk/arkiv/arkiv_dmo/dmo_saernummer_2015/dmo_saernummer_2015_musik_hjerneforskning_01.pdf

Haumann, N. T., Parkkonen, L., Kliuchko, M., Vuust, P. & Brattico, E. (2016). Comparing the Performance of Popular MEG/EEG Artifact Correction Methods in an Evoked-Response Study. Computational Intelligence and Neuroscience, 2016, 1-10. Article 7489108. https://doi.org/10.1155/2016/7489108

Haumann, N. T., Vuust, P., Bertelsen, F. C. B. & Garza-Villarreal, E. A. (2018). Influence of Musical Enculturation on Brain Responses to Metric Deviants. Frontiers in Neuroscience, 12(APR), Article 218. https://doi.org/10.3389/fnins.2018.00218

Haumann, N. T., Kliuchko, M., Vuust, P. & Brattico, E. (2018). Applying Acoustical and Musicological Analysis to Detect Brain Responses to Realistic Music: A Case Study. Applied Sciences, 8(5), Article 716. https://doi.org/10.3390/app8050716

Haumann, N. T., Petersen, B., Vuust, P. & Brattico, E. (2023). Age differences in central auditory system responses to naturalistic music. Biological Psychology, 179, Article 108566. https://doi.org/10.1016/j.biopsycho.2023.108566

Harry, B. B., Margulies, D. S., Falkiewicz, M. & Keller, P. E. (2023). Brain networks for temporal adaptation, anticipation, and sensory-motor integration in rhythmic human behavior. Neuropsychologia, 183, Article 108524. https://doi.org/10.1016/j.neuropsychologia.2023.108524

Harrison, P. & Pearce, M. (2018). An energy-based generative sequence model for testing sensory theories of Western harmony. In Proceedings of the 19th International Society for Music Information Retrieval Conference, ISMIR 2018 (pp. 160-167). http://webprojects.eecs.qmul.ac.uk/marcusp/papers/HarrisonPearce2018b.pdf

Harrison, P. & Pearce, M. (2018). Dissociating sensory and cognitive theories of harmony perception through computational modeling. In Proceedings of the 15th International Conference on Music Perception & Cognition http://webprojects.eecs.qmul.ac.uk/marcusp/papers/HarrisonPearce2018a.pdf

Harrison, P. M. C., Bianco, R., Chait, M. & Pearce, M. T. (2020). PPM-Decay: A computational model of auditory prediction with memory decay. PLOS Computational Biology, 16(11), Article e1008304. https://doi.org/10.1371/journal.pcbi.1008304

Harrison, P. M. C. & Pearce, M. T. (2020). Simultaneous Consonance in Music Perception and Composition. Psychological Review, 127(2), 216-244. https://doi.org/10.1037/rev0000169

Hansen, N. C., Loui, P., Vuust, P. & Pearce, M. (2015). Modelling short- and long-term statistical learning of music as a process of predictive entropy reduction. Paper presented at International Conference on Interdisciplinary Advances in Statistical Learning, San Sebastian, Spain.

Hansen, N. C. (2015). Nye perspektiver på studiet af musikalsk ekspertise. Dansk Musikforskning Online, Special Issue 2015: Music and Brain Research, 69-102. http://danishmusicologyonline.dk/arkiv/arkiv_dmo/dmo_saernummer_2015/dmo_saernummer_2015_musik_hjerneforskning_04.pdf

Hansen, N. C., Sadakata, M. & Pearce, M. (2016). Nonlinear Changes in the Rhythm of European Art Music: Quantitative Support for Historical Musicology. Music Perception, 33(4), 414. Article 2. https://doi.org/10.1525/mp.2016.33.4.414

Hansen, N. C., Højlund, A., Møller, C., Pearce, M. & Vuust, P. (2016). Enhanced feature integration in musicians: Expertise modulates the additivity of the MMNm response. Poster session presented at 14th International Conference on Music Perception and Cognition, San Francisco, United States.

Hansen, N. C., Vuust, P. & Pearce, M. (2016). "If You Have to Ask, You'll Never Know": Effects of Specialised Stylistic Expertise on Predictive Processing of Music. P L o S One, 11(10), 1-20. Article e0163584. https://doi.org/10.1371/journal.pone.0163584

Hansen, N. C. (2016). Born and made: Musical experts are no geniuses. In Australian Music & Psychology Society Newsletter (Vol. 4, pp. 4-5). Australian Music & Psychology Society (AMPS). https://lookaside.fbsbx.com/file/AMPS%20newsletter%20edition%204.pdf?token=AWxsuJvWln5KE4PasMr2Y7g9h3ffBqEckwbQT2c8yFfMtBNpS0EwfYQZzqZTCYPW-r_7MWWvT5VEtWrAYq16-gzhs97PluCEzaFgkh1T0DDrbMl-dI34VJDCDJkNLMxuxvGadWiVC_Iu4BAQTRR7GBpH5yoNPN3fMab3uBGaEm7O-A

Hansen, N. C., Dietz, M. & Vuust, P. (2017). Commentary: Predictions and the brain: how musical sounds become rewarding. Frontiers in Human Neuroscience, 11, Article 168. https://doi.org/10.3389/fnhum.2017.00168

Hansen, N. C. (2020). The expectancy dynamics of anti-tonal twelve-tone rows: a commentary and reanalysis of von Hippel & Huron (2020). Empirical Musicology Review, 15(1-2), 128-140. https://doi.org/10.18061/emr.v15i1-2.7806

Hansen, N. C., Treider, J. M. G., Swarbrick, D., Bamford, J. S., Wilson, J. & Vuoskoski, J. K. (2021). A Crowd-Sourced Database of Coronamusic: Documenting Online Making and Sharing of Music During the COVID-19 Pandemic. Frontiers in Psychology, 12, Article 684083. https://doi.org/10.3389/fpsyg.2021.684083

Hansen, N. C., Kragness, H. E., Vuust, P., Trainor, L. & Pearce, M. T. (2021). Predictive Uncertainty Underlies Auditory Boundary Perception. Psychological Science, 32(9), 1416-1425. https://doi.org/10.1177/0956797621997349

Hansen, N. C. & Keller, P. E. (2021). Oxytocin as an allostatic agent in the social bonding effects of music. Behavioral and Brain Sciences, 44, 61-64. Article 75. https://doi.org/10.1017/S0140525X20001235

Hansen, N. C., Wald-Fuhrmann, M. & Davidson, J. W. (2022). Editorial: Social Convergence in Times of Spatial Distancing: The Role of Music During the COVID-19 Pandemic. Frontiers in Psychology, 13, Article 910101. https://doi.org/10.3389/fpsyg.2022.910101

Hansen, N. C., Højlund, A., Møller, C., Pearce, M. & Vuust, P. (2022). Musicians show more integrated neural processing of contextually relevant acoustic features. Frontiers in Neuroscience, 16, Article 907540. https://doi.org/10.3389/fnins.2022.907540

Hallett, M., de Haan, W., Deco, G., Dengler, R., Di Iorio, R., Gallea, C., Gerloff, C., Grefkes, C., Helmich, R. C., Kringelbach, M. L., Miraglia, F., Rektor, I., Strýček, O., Vecchio, F., Volz, L. J., Wu, T. & Rossini, P. M. (2020). Human brain connectivity: Clinical applications for clinical neurophysiology. Clinical Neurophysiology, 131(7), 1621-1651. https://doi.org/10.1016/j.clinph.2020.03.031

Hall, C. A., Kader, A. S., Danielle McHale, A. M., Stewart, L., Fick, G. H. & Vilke, G. M. (2013). Frequency of signs of excited delirium syndrome in subjects undergoing police use of force: Descriptive evaluation of a prospective, consecutive cohort. Journal of forensic and legal medicine, 20(2), 102-7. https://doi.org/10.1016/j.jflm.2012.05.008

Hahn, G., Zamora-López, G., Uhrig, L., Tagliazucchi, E., Laufs, H., Mantini, D., Kringelbach, M. L., Jarraya, B. & Deco, G. (2021). Signature of consciousness in brain-wide synchronization patterns of monkey and human fMRI signals. NeuroImage, 226, Article 117470. https://doi.org/10.1016/j.neuroimage.2020.117470

Gugnowska, K., Novembre, G., Kohler, N., Villringer, A., Keller, P. E. & Sammler, D. (2022). Endogenous sources of interbrain synchrony in duetting pianists. Cerebral Cortex, 32(18), 4110-4127. https://doi.org/10.1093/cercor/bhab469

Grube, M., Brandl, S., Kindermans, P-J., Blankertz, B., Daehne, S. & Mueller, K-R. (2018). Can we “find the beat”? Searching the beta band in the human EEG as a function of acoustic rhythmic regularity and in correlation with behaviour.. 1. Poster session presented at 11th FENS Forum of Neuroscience, Berlin, Germany.

Grube, M., Kumar, S., Smith, F., Slater, H. & Griffiths, TD. (2019). Neural substrates of auditory sequence processing and language skill in early-to-mid adolescence.. Poster session presented at Annual Midwinter Meeting of the Association for Research in Otolaryngology (ARO), Baltimore, United States.

Grimaldi, M., Sisinni, B., Fivela, B. G., Invitto, S., Resta, D., Alku, P. & Brattico, E. (2014). Assimilation of L2 vowels to L1 phonemes governs L2 learning in adulthood: a behavioral and ERP study. Frontiers in Human Neuroscience, 8, Article 279. https://doi.org/10.3389/fnhum.2014.00279

Griffiths, T. D., Kumar, S., Warren, J. D., Stewart, L., Stephan, K. E. & Friston, K. J. (2007). Approaches to the cortical analysis of auditory objects. Hearing Research, 229(1-2), 46-53. https://doi.org/10.1016/j.heares.2007.01.010

Gold, B. P., Frank, M. J., Bogert, B. & Brattico, E. (2013). Pleasurable music affects reinforcement learning according to the listener. Frontiers in Psychology, 4, Article 541. https://doi.org/10.3389/fpsyg.2013.00541

Gold, B. P., Pearce, M. T., Mas-Herrero, E., Dagher, A. & Zatorre, R. J. (2019). Predictability and Uncertainty in the Pleasure of Music: A Reward for Learning? The Journal of neuroscience : the official journal of the Society for Neuroscience, 39(47), 9397-9409. https://doi.org/10.1523/JNEUROSCI.0428-19.2019

Glomb, K., Kringelbach, M. L., Deco, G., Hagmann, P., Pearson, J. & Atasoy, S. (2021). Functional harmonics reveal multi-dimensional basis functions underlying cortical organization. Cell Reports, 36(8), Article 109554. https://doi.org/10.1016/j.celrep.2021.109554

Gebauer, L., Kringelbach, M. L. & Vuust, P. (2015). Predictive coding links perception, action, and learning to emotions in music. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al. Physics of Life Reviews, 13, 50-52. https://doi.org/10.1016/j.plrev.2015.04.023

Gebauer, L., Witek, M., Hansen, N. C., Thomas, J., Konvalinka, I. & Vuust, P. (2016). Oxytocin improves synchronisation in leader-follower interaction. Scientific Reports, 6, Article 38416. Advance online publication. https://doi.org/10.1038/srep38416

Gebauer, L., Højlund, A. & Vuust, P. (2018). The no-standard musical multi-feature paradigm (MuMUFE). Poster session presented at MMN 2018: The 8th Mismatch Negativity Conference, Helsinki, Finland.

Garza-Villarreal, E. A., Jiang, Z., Vuust, P., Alcauter, S., Vase, L., Pasaye, E. H., Cavazos-Rodriguez, R., Brattico, E., Jensen, T. S. & Barrios, F. A. (2015). Music reduces pain and increases resting state fMRI BOLD signal amplitude in the left angular gyrus in fibromyalgia patients. Frontiers in Psychology, 6, 1051. https://doi.org/10.3389/fpsyg.2015.01051

Garza-Villarreal, E. A., Pando, V., Vuust, P. & Parsons, C. (2017). Music-Induced Analgesia in Chronic Pain Conditions: A Systematic Review and Meta-Analysis. Pain Physician, 20(7), 597-610.

Garrido, L., Eisner, F., McGettigan, C., Stewart, L., Sauter, D., Hanley, J. R., Schweinberger, S. R., Warren, J. D. & Duchaine, B. (2009). Developmental phonagnosia: a selective deficit of vocal identity recognition. Neuropsychologia, 47(1), 123-31. https://doi.org/10.1016/j.neuropsychologia.2008.08.003

Galadí, J. A., Silva Pereira, S., Sanz Perl, Y., Kringelbach, M. L., Gayte, I., Laufs, H., Tagliazucchi, E., Langa, J. A. & Deco, G. (2021). Capturing the non-stationarity of whole-brain dynamics underlying human brain states. NeuroImage, 244, Article 118551. https://doi.org/10.1016/j.neuroimage.2021.118551

G, F., V, W. & Stewart, L. (2015). Measuring the earworm experience: The involuntary musical imagery scale (IMIS). Poster session presented at Ninth Triennial Conference of the European Society for the Cognitive Sciences of Music, Manchester, United Kingdom.

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Hella Kastbjerg