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Center for Music in the Brain

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Hoegholt, N. F., Bonetti, L., Stevner, A. B. A., Andersen, C. E., Fernandes, H. M., Vuust, P. & Kringelbach, M. L. (2023). A magnetoencephalography study of first-time mothers listening to infant cries. Cerebral Cortex, 33(10), 5896–5905. https://doi.org/10.1093/cercor/bhac469

Hoegholt, N. F., Buus, S., Stevner, A. B. A., Sui, J., Vuust, P. & Kringelbach, M. L. (2023). Sleep-deprived new mothers gave their infants a higher priority than themselves. Acta Paediatrica, International Journal of Paediatrics, 112(1), 93-99. https://doi.org/10.1111/apa.16560

Hoegholt, N. F., Buus, S., Fernandes, H. M., Sui, J., Vuust, P. & Kringelbach, M. L. (2023). On screen experiment showed that becoming a parent for the first time shifted people's priorities from themselves to their infant at 1 year of age. Acta Paediatrica, International Journal of Paediatrics, 112(1), 85-92. https://doi.org/10.1111/apa.16561

Hoegholt, N. F., Krænge, C. E., Vuust, P., Kringelbach, M. & Jespersen, K. V. (2025). Music and Sleep Hygiene Interventions for Pregnancy-Related Insomnia: An Online Randomized Controlled Trial. Journal of Midwifery and Women's Health, 70(3), 387-395. https://doi.org/10.1111/jmwh.13699

Hindriks, R., Woolrich, M., Luckhoo, H., Joensson, M., Mohseni, H., Kringelbach, M. L. & Deco, G. (2015). Role of white-matter pathways in coordinating alpha oscillations in resting visual cortex. NeuroImage, 106, 328-339. https://doi.org/10.1016/j.neuroimage.2014.10.057

Hersh, T. A., Ravignani, A. & Burchardt, L. S. (2023). Robust rhythm reporting will advance ecological and evolutionary research. Methods in Ecology and Evolution, 14(6), 1398-1407. https://doi.org/10.1111/2041-210X.14118

Hersh, T. A., Ravignani, A. & Whitehead, H. (2024). Cetaceans are the next frontier for vocal rhythm research. Proceedings of the National Academy of Sciences of the United States of America, 121(25), e2313093121. Article e2313093121. https://doi.org/10.1073/pnas.2313093121

Hersh, T. A., Jadoul, Y., Gamba, M., Ravignani, A. & Favaro, L. (2025). Accelerando and crescendo in African penguin ecstatic display songs. Annals of the New York Academy of Sciences. Advance online publication. https://doi.org/10.1111/nyas.15383

Herff, S. A., Bonetti, L., Cecchetti, G., Vuust, P., Kringelbach, M. L. & Rohrmeier, M. A. (2024). Hierarchical syntax model of music predicts theta power during music listening. Neuropsychologia, 199, Article 108905. https://doi.org/10.1016/j.neuropsychologia.2024.108905

Heng, J. G., Zhang, J., Bonetti, L., Lim, W. P. H., Vuust, P., Agres, K. & Chen, S. H. A. (2024). Understanding music and aging through the lens of Bayesian inference. Neuroscience and Biobehavioral Reviews, 163, Article 105768. https://doi.org/10.1016/j.neubiorev.2024.105768

Heinonen-Guzejev, M., Klyuchko, M., Heikkilä, K., Spinosa, V., Tervaniemi, M. & Brattico, E. (2014). Noise sensitivity modulates the auditory-cortex discrimination of sound feature changes. In INTERNOISE 2014 - 43rd International Congress on Noise Control Engineering: Improving the World Through Noise Control Australian Acoustical Society.

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. 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

Haumann, N. T., Petersen, B., Seeberg, A. B., Vuust, P. & Brattico, E. (2025). It takes experience to tango: Experienced cochlear implant users show cortical evoked potentials to naturalistic music. bioRxiv. https://doi.org/10.1101/2025.06.04.657805

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. & Reymore, L. (2021). Articulatory motor planning and timbral idiosyncrasies as underlying mechanisms of instrument-specific absolute pitch in expert musicians. PLOS ONE, 16(2 ), Article e0247136. https://doi.org/10.1371/journal.pone.0247136

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

Hancock, F., Rosas, F. E., Luppi, A. I., Zhang, M., Mediano, P. A. M., Cabral, J., Deco, G., Kringelbach, M. L., Breakspear, M., Kelso, J. A. S. & Turkheimer, F. E. (2025). Metastability demystified — the foundational past, the pragmatic present and the promising future. Nature Reviews Neuroscience, 26(2), 82-100. Article e1000072. https://doi.org/10.1038/s41583-024-00883-1

Hamilton, M. & Pearce, M. (2024). Trajectories and revolutions in popular melody based on U.S. charts from 1950 to 2023. Scientific Reports, 14(1), Article 14749. https://doi.org/10.1038/s41598-024-64571-x

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

Guzmán, E. G., Perl, Y. S., Vohryzek, J., Escrichs, A., Manasova, D., Türker, B., Tagliazucchi, E., Kringelbach, M., Sitt, J. D. & Deco, G. (2023). The lack of temporal brain dynamics asymmetry as a signature of impaired consciousness states. Interface Focus, 13(3), Article 20220086. https://doi.org/10.1098/rsfs.2022.0086

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