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Center for Music in the Brain

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Shoemark, H., Dahlstrøm, M., Bedford, O. & Stewart, L. (2021). The effect of a voice-centered psycho-educational program on maternal self-efficacy: A feasibility study. International Journal of Environmental Research and Public Health, 18(5), Article 2537. https://doi.org/10.3390/ijerph18052537

Fasano, M. C., Cabral, J., Stevner, A., Vuust, P., Cantou, P., Brattico, E. & Kringelbach, M. L. (2020). The early adolescent brain on music: analysis of functional dynamics reveals engagement of orbitofrontal cortex reward system. bioRxiv. https://doi.org/10.1101/2020.06.18.148072

Fasano, M. C., Cabral, J., Stevner, A., Vuust, P., Cantou, P., Brattico, E. & Kringelbach, M. L. (2023). The early adolescent brain on music: Analysis of functional dynamics reveals engagement of orbitofrontal cortex reward system. Human Brain Mapping, 44(2), 429-446. https://doi.org/10.1002/hbm.26060

Deco, G., Kringelbach, M. L., Jirsa, V. K. & Ritter, P. (2017). The dynamics of resting fluctuations in the brain: metastability and its dynamical cortical core. Scientific Reports, 7(1), 3095. Article 3095. https://doi.org/10.1038/s41598-017-03073-5

Cruzat, J., Deco, G., Tauste-Campo, A., Principe, A., Costa, A., Kringelbach, M. L. & Rocamora, R. (2018). The dynamics of human cognition: Increasing global integration coupled with decreasing segregation found using iEEG. NeuroImage, 172, 492-505. https://doi.org/10.1016/j.neuroimage.2018.01.064

Alonso Martínez, S., Deco, G., Ter Horst, G. J. & Cabral, J. (2020). The Dynamics of Functional Brain Networks Associated With Depressive Symptoms in a Nonclinical Sample. Frontiers in Neural Circuits, 14, Article 570583. https://doi.org/10.3389/fncir.2020.570583

Nieminen, S., Istok, E., Brattico, E. & Tervaniemi, M. (2012). The development of the aesthetic experience of music: Preference, emotions, and beauty. Musicae Scientiae, 16(3), 372-391. https://doi.org/10.1177/1029864912450454

Nieminen, S., Istok, E., Brattico, E., Tervaniemi, M. & Huotilainen, M. (2011). The development of aesthetic responses to music and their underlying neural and psychological mechanisms. Cortex, 47(9), 1138-1146. https://doi.org/10.1016/j.cortex.2011.05.008

Møller, C., Hansen, N. C., Vuust, P. & Müllensiefen, D. (2024). The Danish Goldsmiths Musical Sophistication Index: Validation in Samples with Different Degrees of Representativeness. Music & Science, 7, 1-12. https://doi.org/10.1177/20592043241289087

Engler, B., Zamm, A. & Møller, C. (2024). The complex dynamics of spontaneous rates in musicians and non-musicians: Intra-individual stability and inter-individual differences. Poster session presented at The Neurosciences and Music VIII, Helsinki, Finland.

Brattico, E. (2006). The cognitive neuroscience of music. Musicae Scientiae, 10(1), 130-137.

Petersen, B., Friis Andersen, A. S., Dietz, M., Højlund, A., Brattico, E., Haumann, N. T., Michel, F., Kamaric Riis, S. & Vuust, P. (2018). The CI MuMuFe - a new MMN paradigm for measuring music discrimination in electric hearing. Poster session presented at MMN 2018: The 8th Mismatch Negativity Conference, Helsinki, Finland.

Petersen, B., Friis Andersen, A. S., Trusbak Haumann, N., Højlund, A., Dietz, M., Michel, F., Kamaric Riis, S., Brattico, E. & Vuust, P. (2021). The CI MuMuFe - a new MMN paradigm for measuring music discrimination in electric hearing: The CI MuMuFe. Poster session presented at Neuromusic VII: Connecting with music across lifespan.

Trusbak Haumann, N., Petersen, B., Friis Andersen, A. S., F. Faulkner, K., Brattico, E. & Vuust, P. (2021). The CI MuMuFe - a new MMN paradigm for measuring music discrimination in electric hearing.

Petersen, B., Andersen, A. S., Trusbak Haumann, N., Højlund, A., Dietz, M., Michel, F., Kamaric Riis, S., Brattico, E. & Vuust, P. (2020). The CI MuMuFe: A New MMN Paradigm for Measuring Music Discrimination in Electric Hearing. Frontiers in Neuroscience, 14, Article 2. https://doi.org/10.3389/fnins.2020.00002

Toiviainen, P., Burunat, I., Brattico, E., Vuust, P. & Alluri, V. (2020). The chronnectome of musical beat. NeuroImage, 216, Article 116191. https://doi.org/10.1016/j.neuroimage.2019.116191

Magee, W. L. & Stewart, L. (2015). The challenges and benefits of a genuine partnership between Music Therapy and Neuroscience: a dialog between scientist and therapist. Frontiers in Human Neuroscience, 9, 223. https://doi.org/10.3389/fnhum.2015.00223

Fasano, M. C., Glerean, E., Gold, B., Sheng, D., Sams, M., Rauschecker, J., Vuust, P. & Brattico, E. (2017). The brain correlates of engagement in music performance: A behavioral and fMRI study. Poster session presented at The Neurosciences and Music VI - Music, Sound and Health , Boston, Massachusetts, United States.

Bonetti, L. & Costa, M. (2016). The Bologna tower paradox: An architectural zoom lens illusion in framed visual perception. In European Conference on Visual Perception (ECVP), University of Barcelona (Spain)

Mårup, S. H. (2025). The bodily hierarchy of rhythm and beat production in brain and behavior. [PhD dissertation, Aarhus University].

van der Werff, J., Ravignani, A. & Jadoul, Y. (2024). thebeat: A Python package for working with rhythms and other temporal sequences. Behavior Research Methods, 56(4), 3725-3736. https://doi.org/10.3758/s13428-023-02334-8

Stupacher, J., Møller, C., Celma-Miralles, A. & Vuust, P. (2021). The bass lays down the beat in polyrhythms. Poster session presented at Rhythm Production and Perception Workshop 2021, Oslo, Norway.

Scarratt, R. J., Heggli, O. A., Vuust, P. & Jespersen, K. V. (2023). The audio features of sleep music: universal and subgroup characteristics. PLoS One, 18(1), Article e0278813. https://doi.org/10.1371/journal.pone.0278813

Kliuchko, M., Heinonen-Guzejev, M., Monacis, L., Gold, B., Heikkilä, K., Spinosa, V., Tervaniemi, M. & Brattico, E. (2015). The association of noise sensitivity with music listening, training, and aptitude. Noise and Health, 17(78), 350-357. https://doi.org/10.4103/1463-1741.165065

Buus, R. M., Genovese, S. & Jespersen, K. V. (2025). The art of sleep: examining sleep strategies in the general population with a focus on the use of music for sleep. Journal of Sleep Research, 34(5), Article e70006. https://doi.org/10.1111/jsr.70006

Sadeghi, F., Agua Banyeres, E. D., Pizzuti, A., Okar, A., Grimm, K., Gerloff, C., Kringelbach, M. L., Goebel, R., Zittel, S. & Deco, G. (2025). The arrow of time in Parkinson's disease. NeuroImage: Clinical, 47, Article 103834. https://doi.org/10.1016/j.nicl.2025.103834

Peretz, I., Brattico, E., Jarvenpaa, M. & Tervaniemi, M. (2009). The amusic brain: in tune, out of key, and unaware. Brain, 132, 1277-1286. https://doi.org/10.1093/brain/awp055

Wehmeyer, L., Baldermann, J. C., Pogosyan, A., Rodriguez Plazas, F., Loehrer, P. A., Bonetti, L., Yassine, S., zur Mühlen, K., Schüller, T., Kuhn, J., Visser-Vandewalle, V., Tan, H. & Andrade, P. (2026). Thalamo-frontal functional connectivity patterns in Tourette Syndrome: Insights from combined intracranial DBS and EEG recordings. Molecular Psychiatry, 31(1), 231-242. https://doi.org/10.1038/s41380-025-03220-9

Cruzat, J., Herzog, R., Prado, P., Sanz-Perl, Y., Gonzalez-Gomez, R., Moguilner, S., Kringelbach, M. L., Deco, G., Tagliazucchi, E. & Ibañez, A. (2023). Temporal Irreversibility of Large-Scale Brain Dynamics in Alzheimer's Disease. The Journal of Neuroscience, 43(9), 1643-1656. https://doi.org/10.1523/JNEUROSCI.1312-22.2022

Basiński, K., Quiroga-Martinez, D. R. & Vuust, P. (2023). Temporal hierarchies in the predictive processing of melody: From pure tones to songs. Neuroscience and Biobehavioral Reviews, 145, Article 105007. https://doi.org/10.1016/j.neubiorev.2022.105007

Stupacher, J. & Mårup, S. H. (Eds.) (2021). SysMus21 Conference Proceedings. Aarhus Universitet. https://doi.org/10.17605/OSF.IO/HG6RZ

Waade, P. T., Zubek, J., Foster Vander Elst, O., Ring, L., Slivkaitė, R., Zamm, A., Baglini, R. B., Bamford, J. S., Rosas, F. E., Mediano, P. A. M., Vesper, C. & Tylén, K. (2023). Synergy and Synchrony in Dynamic Social Coordination: A Motion Capture Study of Improvised Lindy Hop Partner Dance.

Shinozuka, K., Jerotic, K., Mediano, P., Zhao, A. T., Preller, K. H., Carhart-Harris, R. & Kringelbach, M. L. (2024). Synergistic, multi-level understanding of psychedelics: three systematic reviews and meta-analyses of their pharmacology, neuroimaging and phenomenology. Translational Psychiatry, 14(1), Article 485. https://doi.org/10.1038/s41398-024-03187-1

Witek, M. A. G., Popescu, T., Clarke, E. F., Hansen, M., Konvalinka, I., Kringelbach, M. L. & Vuust, P. (2017). Syncopation affects free body-movement in musical groove. Experimental Brain Research, 235(4), 995-1005. https://doi.org/10.1007/s00221-016-4855-6

Corcoran, C., Stupacher, J. & Vuust, P. (2022). Swinging the Score? Swing Phrasing Cannot Be Communicated via Explicit Notation Instructions Alone. Music Perception, 39(4), 386-400. https://doi.org/10.1525/MP.2022.39.4.386

Foster Vander Elst, O., Vuust, P. & Kringelbach, M. L. (2021). Sweet anticipation and positive emotions in music, groove, and dance. Current Opinion in Behavioral Sciences, 39, 79-84. https://doi.org/10.1016/j.cobeha.2021.02.016

Brattico, E. & Jacobsen, T. (2009). Subjective Appraisal of Music Neuroimaging Evidence. Annals of the New York Academy of Sciences, 308-317. https://doi.org/10.1111/j.1749-6632.2009.04843.x

Donaire, A., Padilla, N., Escrichs, A., Khawja, M., Setoain, X., Rumia, J., Roldan, P., Bargallo, N., Boget, T., Pintor, L., Centeno, M., Conde, E., Vernet, O., Buendía, J., Manzanares, I., Ådén, U., Carreño, M., Kringelbach, M. & Deco, G. (2024). Subject-based assessment of large-scale integration dynamics in epileptic brain networks: insights from the intrinsic ignition framework. Cerebral cortex (New York, N.Y. : 1991), 34(10), Article bhae419. https://doi.org/10.1093/cercor/bhae419

Alluri, V., Toiviainen, P. & Brattico, E. (2015). Subcortical network hub differences in musicians and non-musicians during continuous listening to music. Abstract from ICME4, Geneve, 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

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.

Perl, Y. S., Escrichs, A., Tagliazucchi, E., Kringelbach, M. L. & Deco, G. (2022). Strength-dependent perturbation of wholebrain model working in different regimes reveals the role of fluctuations in brain dynamics. PLoS Computational Biology, 18(11), Article e1010662. https://doi.org/10.1371/journal.pcbi.1010662

Williamson, V. J., Liikkanen, L. A., Jakubowski, K. & Stewart, L. (2014). Sticky tunes: how do people react to involuntary musical imagery? PLoS One, 9(1), e86170. https://doi.org/10.1371/journal.pone.0086170

Pearce, M. (2018). Statistical learning and probabilistic prediction in music cognition: mechanisms of stylistic enculturation. Annals of the New York Academy of Sciences, 1423(1), 378-395. https://doi.org/10.1111/nyas.13654

Verga, L., Sroka, M. G. U., Varola, M., Villanueva, S. & Ravignani, A. (2022). Spontaneous rhythm discrimination in a mammalian vocal learner. Biology Letters, 18(10), 20220316. Article 20220316. https://doi.org/10.1098/rsbl.2022.0316

Engler, B., Zamm, A. & Møller, C. (2024). Spontaneous rates exhibit high intra-individual stability across movements involving different biomechanical systems and cognitive demands. PsyArXiv. https://doi.org/10.31234/osf.io/wtnax

Engler, B. H., Zamm, A. & Møller, C. (2024). Spontaneous rates exhibit high intra-individual stability across movements involving different biomechanical systems and cognitive demands. Scientific Reports, 14(1), Article 14876. https://doi.org/10.1038/s41598-024-65788-6

Engler, B., Zamm, A. & Møller, C. (2024). Spontaneous rates are consistent across domains of behavior involving different biomechanical constraints and cognitive demands.

Bonetti, L., Brattico, E., Carlomagno, F., Cabral, J., Stevner, A., Deco, G., Whybrow, P. C., Pearce, M., Pantazis, D., Vuust, P. & Kringelbach, M. L. (2024). Spatiotemporal whole-brain activity and functional connectivity of melodies recognition. Cerebral Cortex, 34(8), Article e320. https://doi.org/10.1093/cercor/bhae320

Bonetti, L., Fernández-Rubio, G., Carlomagno, F., Dietz, M., Pantazis, D., Vuust, P. & Kringelbach, M. L. (2024). Spatiotemporal brain hierarchies of auditory memory recognition and predictive coding. Nature Communications, 15(1), Article 4313. https://doi.org/10.1038/s41467-024-48302-4

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