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Center for Music in the Brain

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Lund, H. N., Kreutz, G. & Jespersen, K. V. (2019). Music and sleep: Improving mental health.

Pereira, C. S., Teixeira, J., Figueiredo, P., Xavier, J., Castro, S. L. & Brattico, E. (2011). Music and emotions in the brain: Familiarity matters. P L o S One, 6(11), Article 27241. https://doi.org/10.1371/journal.pone.0027241

Burunat, I., Brattico, E., Hartmann, M., Vuust, P., Särkämö, T. & Toiviainen, P. (2018). Musical training predicts cerebello-hippocampal coupling during music listening. Psychomusicology: Music, Mind & Brain, 28(3), 152-163.

Cantou, P., Fasano, M. C., Alexander Kleber, B., Vuust, P. & Brattico, E. (2018). Musical tension processing in preadolescents: a free-listening fMRI study. 1.

Rohrmeier, M. & Pearce, M. (2018). Musical syntax I: Theoretical perspectives. In R. Bader (Ed.), Springer Handbooks (pp. 473-486). Springer. https://doi.org/10.1007/978-3-662-55004-5_25

Pearce, M. & Rohrmeier, M. (2018). Musical syntax II: Empirical perspectives. In R. Bader (Ed.), Springer Handbooks (pp. 487-505). Springer. https://doi.org/10.1007/978-3-662-55004-5_26

Møller, C., Hansen, N. C., Vuust, P. & Müllensiefen, D. (2021). Musical sophistication and mental speed in the Danish general population. Poster session presented at Neuromusic VII: Connecting with music across lifespan.

Brattico, E., Tervaniemi, M., Naatanen, R. & Peretz, I. (2006). Musical scale properties are automatically processed in the human auditory cortex. Gene Expression Patterns, 1117, 162-174. https://doi.org/10.1016/j.brainres.2006.08.023

Witek, M. A. G., Kringelbach, M. L. & Vuust, P. (2015). Musical rhythm and affect: Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al. Physics of Life Reviews. https://doi.org/10.1016/j.plrev.2015.04.029

Quiroga Martinez, D. R., Hansen, N. C., Højlund, A., Pearce, M., Brattico, E. & Vuust, P. (2020). Musical prediction error responses similarly reduced by predictive uncertainty in musicians and non-musicians. European Journal of Neuroscience, 51(11), 2250-2269. https://doi.org/10.1111/ejn.14667

Schiavio, A., Stupacher, J., Xypolitaki, E., Parncutt, R. & Timmers, R. (2021). Musical novices perform with equal accuracy when learning to drum alone or with a peer. Scientific Reports, 11(1), Article 12422. https://doi.org/10.1038/s41598-021-91820-0

Bonetti, L. & Costa, M. (2017). Musical mode and visual-spatial cross-modal associations in infants and adults. Musicae Scientiae, 8, Article 1218.

Petersen, B., Mortensen, M. V. & Vuust, P. (2011). Musical Methods for Little Digital Ears –music training and testing in preschool children with cochlear implants. Poster session presented at The Neurosciences and Music - IV, Edinburgh, United Kingdom.

Petersen, B., Hardgrove Hansen, R., Beyer, K., Mortensen, M. V. & Vuust, P. (2010). Musical Methods for Little Digital Ears — Musical Learning with Preschool Cochlear Implant Users.

Petersen, B., Friis Andersen, A. S., Dietz, M., Højlund, A., Brattico, E., Haumann, N. T., Michel, F., Kamaric Riis, S. & Vuust, P. (2018). Musical Listening in Electric Hearing –Two Novel EEG Paradigms for Studying Music Discrimination in Cochlear Implant Users. Poster session presented at 2nd International Music and CI symposium, Montreal, Canada.

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

Alluri, V., Toiviainen, P., Burunat, I., Bogert, B., Numminen, J. & Brattico, E. (2015). Musical expertise modulates functional connectivity of limbic regions during continuous music listening. Psychomusicology: Music, Mind & Brain, 25(4), 443. https://doi.org/10.1037/pmu0000124

Petersen, B. (2017). Musical Ear Training Through Active Music Making in Adolescent CI Users. Bits and Pieces, CICS Cochlear Implanted Children's Support Group, (Summer Newsletter), 13-17.

Brattico, E. & Tervaniemi, M. (2006). Musical creativity and the human brain. In Musical Creativity: Multidisciplinary Research in Theory and Practice (pp. 289-321). Psychology Press. https://doi.org/10.4324/9780203088111

Spaccavento, S., Carraturo, G., Brattico, E., Matarrelli, B., Rivolta, D., Montenegro, F., Picciola, E., Haumann, N. T., Jespersen, K. V., Vuust, P. & Losavio, E. (2024). Musical and electrical stimulation as intervention in disorder of consciousness (DOC) patients: A randomised cross-over trial. PLOS ONE, 19(5), Article e0304642. https://doi.org/10.1371/journal.pone.0304642

Clemente, A., Pearce, M. T. & Nadal, M. (2022). Musical Aesthetic Sensitivity. Psychology of Aesthetics, Creativity, and the Arts, 16(1), 58-73. https://doi.org/10.1037/aca0000381

Rosselló, J., Vila-Borrellas, E., Alba-Foz, G. & Celma-Miralles, A. (2023). Música, autisme i prosòdia a la llum d’un estudi de cas. Language, Society & Communication, 20, 48-62. https://doi.org/10.1344/LSC-2022.20.5

Møller, C. (2019). Multisensory processing in brain and behavior: One size fits all?.

Nartallo-Kaluarachchi, R., Bonetti, L., Fernández-Rubio, G., Vuust, P., Deco, G., Kringelbach, M. L., Lambiotte, R. & Goriely, A. (2025). Multilevel irreversibility reveals higher-order organization of nonequilibrium interactions in human brain dynamics. Proceedings of the National Academy of Sciences of the United States of America, 122(10), Article e2408791122. Advance online publication. https://doi.org/10.1073/pnas.2408791122

Pedro, K., Grierson, M., Bodak, R., Ward, N., Brander, F., Kelly, K., Newman, N. & Stewart, L. (2016). Motivating stroke rehabilitation through music: A feasibility study using digital musical instruments in the home. In CHI 2016 - Proceedings, 34th Annual CHI Conference on Human Factors in Computing Systems (pp. 1781-1785) https://doi.org/10.1145/2858036.2858376

Young, K. S., Parsons, C., Stein, A. & Kringelbach, M. L. (2015). Motion and emotion: depression reduces psychomotor performance and alters affective movements in caregiving interactions. Frontiers in Behavioral Neuroscience, 9, 26. https://doi.org/10.3389/fnbeh.2015.00026

Turriziani, P., Campo, F. F., Bonaventura, R. E., Mangano, G. R. & Oliveri, M. (2024). Modulation of memory by prism adaptation in healthy subjects. Scientific Reports, 14(1), Article 25358. https://doi.org/10.1038/s41598-024-77027-z

Eraifej, J., Cabral, J., Fernandes, H. M., Kahan, J., He, S., Mancini, L., Thornton, J., White, M., Yousry, T., Zrinzo, L., Akram, H., Limousin, P., Foltynie, T., Aziz, T. Z., Deco, G., Kringelbach, M. & Green, A. L. (2023). Modulation of limbic resting-state networks by subthalamic nucleus deep brain stimulation. Network Neuroscience, 7(2), 478-495. https://doi.org/10.1162/netn_a_00297

Brattico, E., Tupala, T., Glerean, E. & Tervaniemi, M. (2013). Modulated neural processing of Western harmony in folk musicians. Psychophysiology, 50(7), 653-663. https://doi.org/10.1111/psyp.12049

Capouskova, K., Kringelbach, M. L. & Deco, G. (2022). Modes of cognition: Evidence from metastable brain dynamics. NeuroImage, 260, Article 119489. https://doi.org/10.1016/j.neuroimage.2022.119489

Bonetti, L., Bruzzone, S. E. P., Paunio, T., Kantojärvi, K., Kliuchko, M., Vuust, P., Palva, S. & Brattico, E. (2023). Moderate associations between BDNF Val66Met gene polymorphism, musical expertise, and mismatch negativity. Heliyon, 9(5), Article e15600. https://doi.org/10.1016/j.heliyon.2023.e15600

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.

Ipiña, I. P., Kehoe, P. D., Kringelbach, M., Laufs, H., Ibañez, A., Deco, G., Perl, Y. S. & Tagliazucchi, E. (2020). Modeling regional changes in dynamic stability during sleep and wakefulness. NeuroImage, 215, Article 116833. https://doi.org/10.1016/j.neuroimage.2020.116833

Kaplan, T., Cannon, J., Jamone, L. & Pearce, M. (2022). Modeling enculturated bias in entrainment to rhythmic patterns. PLOS Computational Biology, 18(9), Article e1010579. https://doi.org/10.1371/journal.pcbi.1010579

Perl, Y. S., Fittipaldi, S., Campo, C. G., Moguilner, S., Cruzat, J., Fraile-Vazquez, M. E., Herzog, R., Kringelbach, M. L., Deco, G., Prado, P., Ibanez, A. & Tagliazucchi, E. (2023). Model-based whole-brain perturbational landscape of neurodegenerative diseases. eLife, 12, Article e83970. https://doi.org/10.7554/elife.83970

Trusbak Haumann, N., Petersen, B., Andersen, A. S., F. Faulkner, K., Brattico, E. & Vuust, P. (2021). MMN as a reliable marker of music discrimination in individual cochlear implant users: MMN in individual CI. Poster session presented at 3RD MUSIC & COCHLEAR IMPLANTS SYMPOSIUM, Cambridge, United Kingdom.

Celma-Miralles, A., Kliuchko, M., Bruzzone, S. E. P., Trusbak Haumann, N., Zachariasson, P., Vuust, P. & Brattico, E. (2022). Mismatch responses to violations of musical features in children compared to adult. In MMN 2022: Mismatch negativity: neural basis and biomarker development (pp. 104-105). Article P-14 https://www.c-linkage.co.jp/mmn2022/file/mmn2022_program_abstract.pdf

Bonetti, L., Haumann, N. T., Vuust, P., Kliuchko, M. & Brattico, E. (2017). Mismatch Negativity to sound pitch deviants as a possible screening tool for depression. In Mismatch Negativity to sound pitch deviants as a possible screening tool for depression

Näätänen, R., Brattico, E. & Tervaniemi, M. (2003). Mismatch negativity (MMN): A probe to auditory cognition and perception in basic and clinical research. In A. Zani & A. M. Proverbio (Eds.), The Cognitive Electrophysiology of Mind and Brain (pp. 343-355). Psychology Press.

Trusbak Haumann, N., Petersen, B., Andersen, A. S., F. Faulkner, K., Brattico, E. & Vuust, P. (2023). Mismatch negativity as a marker of music perception in individual cochlear implant users: A spike density component analysis study. Clinical Neurophysiology, 148, 76-92. https://doi.org/10.1016/j.clinph.2023.01.015

Bonetti, L., Haumann, N. T., Kliuchko, M., Vuust, P. & Brattico, E. (2017). Mild depression enhances auditory pitch discrimination in the brain as indexed by the Mismatch Negativity. In Mild depression enhances auditory pitch discrimination in the brain as indexed by the Mismatch Negativity

Cabral, J., Castaldo, F., Vohryzek, J., Litvak, V., Bick, C., Lambiotte, R., Friston, K., Kringelbach, M. L. & Deco, G. (2022). Metastable oscillatory modes emerge from synchronization in the brain spacetime connectome. Communications Physics, 5(1), Article 184. https://doi.org/10.1038/s42005-022-00950-y

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

Deco, G. & Kringelbach, M. L. (2016). Metastability and Coherence: Extending the Communication through Coherence Hypothesis Using A Whole-Brain Computational Perspective. Trends in Neurosciences, 39(3), 125-35. https://doi.org/10.1016/j.tins.2016.01.001

Williamson, V. J. & Stewart, L. (2010). Memory for pitch in congenital amusia: beyond a fine-grained pitch discrimination problem. Memory, 18(6), 657-69. https://doi.org/10.1080/09658211.2010.501339

Tervaniemi, M., Huotilainen, M. & Brattico, E. (2014). Melodic multi-feature paradigm reveals auditory profiles in music-sound encoding. Frontiers in Human Neuroscience, 8, Article 496. https://doi.org/10.3389/fnhum.2014.00496

Politimou, N., Douglass-Kirk, P., Pearce, M., Stewart, L. & Franco, F. (2021). Melodic expectations in 5- and 6-year-old children. Journal of Experimental Child Psychology, 203, Article 105020. https://doi.org/10.1016/j.jecp.2020.105020

Mohseni, H. R., Smith, P. P., Parsons, C., Young, K. S., Hyam, J. A., Stein, A., Stein, J. F., Green, A. L., Aziz, T. Z. & Kringelbach, M. L. (2012). MEG can map short and long-term changes in brain activity following deep brain stimulation for chronic pain. P L o S One, 7(6), Article 37993. https://doi.org/10.1371/journal.pone.0037993

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.

Lenc, T., Lenoir, C., Keller, P. E., Polak, R., Mulders, D. & Nozaradan, S. (2025). Measuring self-similarity in empirical signals to understand musical beat perception. European Journal of Neuroscience, 61(2), Article e16637. https://doi.org/10.1111/ejn.16637

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Hella Kastbjerg