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Center for Music in the Brain

Our publications

Peng-Li, D., Alves da Mota, P., Costa Correa, C. M., Chan, R. C. K., Byrne, D. V. & Wang, Q. J. (2022). “Sound” Decisions: The Combined Role of Ambient Noise and Cognitive Regulation on the Neurophysiology of Food Cravings. Frontiers in Neuroscience, 16, [827021]. https://doi.org/10.3389/fnins.2022.827021

Sabharwal, S. R., Varlet, M., Breaden, M., Volpe, G., Camurri, A. & Keller, P. E. (2022). huSync - A model and system for the measure of synchronization in small groups: A case study on musical joint action. IEEE Access, 10, 92357-92372. https://doi.org/10.1109/ACCESS.2022.3202959

Stewart, L., Overath, T., Warren, J. D., Foxton, J. M. & Griffiths, T. D. (2008). fMRI evidence for a cortical hierarchy of pitch pattern processing. PLOS ONE, 3(1), e1470. https://doi.org/10.1371/journal.pone.0001470

Stewart, L. (2002). Zoning in on music and the brain. Trends in Cognitive Sciences, 6(11), 451.

Møller, C., Højlund, A., Bærentsen, K. B., Hansen, N. C., Skewes, J. & Vuust, P. (2019). You get what you need: individual differences in visually-induced amplification of the auditory mismatch negativity. Poster session presented at Neuroscience Day 2019, Aarhus, Denmark.

Klarlund, M., Brattico, E., Pearce, M., Wu, Y., Vuust, P., Overgaard, M. & Du, Y. (2023). Worlds apart? Testing the cultural distance hypothesis in music perception of Chinese and Western listeners. Cognition, 235, [105405]. https://doi.org/10.1016/j.cognition.2023.105405

Bonetti, L., Haumann, N. T., Brattico, E., Kliuchko, M., Vuust, P. & Näätänen, R. (2017). Working memory regulates frontal Mismatch Negativity to sound intensity and slide deviants. Abstract from Neuroscience Day - Let's rethink memory 2017, Aarhus, Denmark.

Bonetti, L., Haumann, N. T., Brattico, E., Kliuchko, M., Vuust, P. & Näätänen, R. (2017). Working memory performance predicts the neural discrimination of sound deviants as indexed by frontal mismatch negativity: an MEG study. In Working memory performance predicts the neural discrimination of sound deviants as indexed by frontal mismatch negativity: an MEG study

Ahonen, L., Huotilainen, M. & Brattico, E. (2016). Within- and between-session replicability of cognitive brain processes: An MEG study with an N-back task. Physiology & Behavior, 158, 43-53. https://doi.org/10.1016/j.physbeh.2016.02.006

Ravignani, A., Thompson, B., Lumaca, M. & Grube, M. (2018). Why do durations in musical rhythms conform to small integer ratios? Frontiers in Computational Neuroscience, 12.

Toiviainen, P., Alluri, V., Burunat, I. & Brattico, E. (2015). Whole-brain functional connectivity during naturalistic music listening: Effect of musical training. Abstract from Ninth Triennial Conference of the European Society for the Cognitive Sciences of Music, Manchester, United Kingdom.

Uribe, C., Escrichs, A., de Filippi, E., Sanz-Perl, Y., Junque, C., Gomez-Gil, E., Kringelbach, M. L., Guillamon, A. & Deco, G. (2022). Whole-brain dynamics differentiate among cisgender and transgender individuals. Human Brain Mapping, 43(13), 4103-4115. https://doi.org/10.1002/hbm.25905

Bonetti, L., Carlomagno, F., Kliuchko, M., Gold, B. P., Palva, S., Trusbak Haumann, N., Tervaniemi, M., Huotilainen, M., Vuust, P. & Brattico, E. (2022). Whole-brain computation of cognitive versus acoustic errors in music: A mismatch negativity study. Neuroimage: Reports, 2(4), [100145]. https://doi.org/10.1016/j.ynirp.2022.100145

Deco, G., Cruzat, J., Cabral, J., Knudsen, G. M., Carhart-Harris, R. L., Whybrow, P. C., Logothetis, N. K. & Kringelbach, M. L. (2018). Whole-Brain Multimodal Neuroimaging Model Using Serotonin Receptor Maps Explains Non-linear Functional Effects of LSD. Current Biology, 28(19), 3065-+. https://doi.org/10.1016/j.cub.2018.07.083

Lumaca, M., Baggio, G. & Vuust, P. (2021). White matter variability in auditory callosal pathways contributes to variation in the cultural transmission of auditory symbolic systems. Brain Structure and Function, 226(6), 1943–1959. https://doi.org/10.1007/s00429-021-02302-y

Duffy, S. & Pearce, M. (2018). What makes rhythms hard to perform? An investigation using Steve Reich’s Clapping Music. PLOS ONE, 13(10), e0205847. https://doi.org/10.1371/journal.pone.0205847

Soler-Toscano, F., Galadí, J. A., Escrichs, A., Perl, Y. S., López-González, A., Sitt, J. D., Annen, J., Gosseries, O., Thibaut, A., Panda, R., Esteban, F. J., Laureys, S., Kringelbach, M. L., Langa, J. A. & Deco, G. (2022). What lies underneath: Precise classification of brain states using time-dependent topological structure of dynamics. PLOS Computational Biology, 18(9), [e1010412]. https://doi.org/10.1371/journal.pcbi.1010412

Stewart, L. & Williamon, A. (2008). What are the implications of neuroscience for musical education? Educational Research, 50(2), 177-186. https://doi.org/10.1080/00131880802082666

Lumaca, M., Trusbak Haumann, N., Brattico, E., Grube, M. & Vuust, P. (2019). Weighting of neural prediction error by rhythmic complexity: A predictive coding account using Mismatch Negativity. Poster session presented at Organization for Human Brain Mapping (OHBM) Annual Meeting 2019, Rome, Italy.

Lumaca, M., Haumann, N. T., Brattico, E., Grube, M. & Vuust, P. (2019). Weighting of neural prediction error by rhythmic complexity: A predictive coding account using Mismatch Negativity. European Journal of Neuroscience, 49(12), 1597-1609. https://doi.org/10.1111/ejn.14329

Kleber, B., Veit, R., Moll, C. V., Gaser, C., Birbaumer, N. & Lotze, M. (2016). Voxel-based morphometry in opera singers: Increased gray-matter volume in right somatosensory and auditory cortices. NeuroImage, 133, 477-83. https://doi.org/10.1016/j.neuroimage.2016.03.045

Ravignani, A. & Herbst, C. T. (2023). Voices in the ocean. Science (New York, N.Y.), 379(6635), 881-882. https://doi.org/10.1126/science.adg5256

De Reus, K., Carlson, D., Lowry, A., Gross, S., Garcia, M., Rubio-Garcia, A., Salazar-Casals, A. & Ravignani, A. (2022). Vocal tract allometry in a mammalian vocal learner. Journal of Experimental Biology, 225(8), [jeb243766]. https://doi.org/10.1242/jeb.243766

Møller, C., Højlund, A., Bærentsen, K. B., Hansen, N. C., Skewes, J. C. & Vuust, P. (2018). Visually induced gains in pitch discrimination: Linking audio-visual processing with auditory abilities. Attention, Perception & Psychophysics, 80(4), 999-1010. https://doi.org/10.3758/s13414-017-1481-8

Rosselló, J., Celma-Miralles, A. & Dias Martins, M. (2020). Visual recursion develops in absence of linguistic recursion. A case-report. In Proceedings of the 13th International Conference Evolution of Language (pp. 371-373). https://brussels.evolang.org/proceedings/evolang13_proceedings.pdf

Fink, L. K., Warrenburg, L. A., Howlin, C., Randall, W. M., Hansen, N. C. & Wald-Fuhrmann, M. (2021). Viral tunes: changes in musical behaviours and interest in coronamusic predict socio-emotional coping during COVID-19 lockdown. Humanities and social sciences communications, 8, [180]. https://doi.org/10.1057/s41599-021-00858-y

Fjaeldstad, A. W., Stiller-Stut, F., Gleesborg, C., Kringelbach, M. L., Hummel, T. & Fernandes, H. M. (2021). Validation of Olfactory Network Based on Brain Structural Connectivity and Its Association With Olfactory Test Scores. Frontiers in Systems Neuroscience, 15, [638053]. https://doi.org/10.3389/fnsys.2021.638053

McDonald, C. & Stewart, L. (2008). Uses and functions of music in congenital amusia. Music Perception, 25(4), 345-355. https://doi.org/10.1525/MP.2008.25.4.345

Kaasgaard, M., Rasmussen, D. B., Hjerrild Andreasson, K., Hilberg, O., Løkke, A., Vuust, P. & Bodtger, U. (2022). Use of Singing for Lung Health as an alternative training modality within pulmonary rehabilitation for COPD: a randomised controlled trial. The European Respiratory Journal, 59(5), [2101142]. https://doi.org/10.1183/13993003.01142-2021

Escrichs, A., Perl, Y. S., Uribe, C., Camara, E., Türker, B., Pyatigorskaya, N., López-González, A., Pallavicini, C., Panda, R., Annen, J., Gosseries, O., Laureys, S., Naccache, L., Sitt, J. D., Laufs, H., Tagliazucchi, E., Kringelbach, M. L. & Deco, G. (2022). Unifying turbulent dynamics framework distinguishes different brain states. Communications Biology, 5(1), [638]. https://doi.org/10.1038/s42003-022-03576-6

Parsons, C., Stark, E. A., Young, K. S., Stein, A. & Kringelbach, M. L. (2013). Understanding the human parental brain. A critical role of the orbitofrontal cortex. Social Neuroscience, 8(6), 525-43. https://doi.org/10.1080/17470919.2013.842610

Lord, L-D., Stevner, A. B., Deco, G. & Kringelbach, M. L. (2017). Understanding principles of integration and segregation using whole-brain computational connectomics: implications for neuropsychiatric disorders. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 375(2096), [20160283]. https://doi.org/10.1098/rsta.2016.0283

Vohryzek, J., Cabral, J., Vuust, P., Deco, G. & Kringelbach, M. L. (2022). Understanding brain states across spacetime informed by whole-brain modelling. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 380(2227), [20210247]. https://doi.org/10.1098/rsta.2021.0247

Saenger, V. M., Kahan, J., Foltynie, T., Friston, K., Aziz, T. Z., Green, A. L., van Hartevelt, T. J., Cabral, J., Stevner, A. B. A., Fernandes, H. M., Mancini, L., Thornton, J., Yousry, T., Limousin, P., Zrinzo, L., Hariz, M., Marques, P., Sousa, N., Kringelbach, M. L. & Deco, G. (2017). Uncovering the underlying mechanisms and whole-brain dynamics of deep brain stimulation for Parkinson's disease. Scientific Reports, 7(1), 9882. https://doi.org/10.1038/s41598-017-10003-y

Vila-Vidal, M., Capouskova, K., Atasoy, S., Kringelbach, M. L. & Deco, G. (2020). Uncovering the spatiotemporal scales of common neuro-mental constructs: Comment on “Is temporo-spatial dynamics the ‘common currency’ of brain and mind? In Quest of ‘Spatiotemporal Neuroscience’ ” by Georg Northoff et al. Physics of Life Reviews, 33, 64-66. https://doi.org/10.1016/j.plrev.2019.10.004

Cheung, V. K. M., Harrison, P. M. C., Meyer, L., Pearce, M. T., Haynes, J. D. & Koelsch, S. (2019). Uncertainty and Surprise Jointly Predict Musical Pleasure and Amygdala, Hippocampus, and Auditory Cortex Activity. Current Biology, 29(23), 4084-4092.e4. https://doi.org/10.1016/j.cub.2019.09.067

Thaler, H., Skewes, J. C., Gebauer, L., Christensen, P., Prkachin, K. M. & Jegindø Elmholdt, E-M. (2017). Typical pain experience but underestimation of others’ pain: Emotion perception in self and others in autism spectrum disorder. Autism, 22(6), 751-762. https://doi.org/10.1177/1362361317701269

Deco, G. & Kringelbach, M. L. (2020). Turbulent-like Dynamics in the Human Brain. Cell Reports, 33(10), [108471]. https://doi.org/10.1016/j.celrep.2020.108471

Farrugia, N., Jakubowski, K., Cusack, R. & Stewart, L. (2015). Tunes stuck in your brain: The frequency and affective evaluation of involuntary musical imagery correlate with cortical structure. Consciousness and Cognition, 35, 66-77. https://doi.org/10.1016/j.concog.2015.04.020

Høgholt, N. F. & Kringelbach, M. L. (2019). Treating pregnancy-related insomnia with music and light: A neuroimaging study. In Frontiers Abstract Book (pp. 62-64). Frontiers Media SA.

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

Stewart, L., Walsh, V., Frith, U. & Rothwell, J. (2001). Transcranial magnetic stimulation produces speech arrest but not song arrest. Annals of the New York Academy of Sciences, 930, 433-5.

Omigie, D., Pearce, M. T. & Stewart, L. (2012). Tracking of pitch probabilities in congenital amusia. Neuropsychologia, 50(7), 1483-93. https://doi.org/10.1016/j.neuropsychologia.2012.02.034

Brandl, S., Trusbak Haumann, N., Brattico, E., Vuust, P. & Grube, M. (2019). Tracing rhythmic regularity processing in EEG and MEG.. Poster session presented at Engineering in Medicine & Biology Conference (EMBC) .

Liu, C., Abu-Jamous, B., Brattico, E. & Nandi, A. K. (2017). Towards tunable consensus clustering for studying functional brain connectivity during affective processing. International Journal of Neural Systems, 27(2), 1650042 . https://doi.org/10.1142/S0129065716500428

Brattico, E., Bogert, B. & Jacobsen, T. (2013). Toward a neural chronometry for the aesthetic experience of music. Frontiers in Psychology, 4, [206]. https://doi.org/10.3389/fpsyg.2013.00206

Kringelbach, M. L. & Rapuano, K. M. (2016). Time in the orbitofrontal cortex. Brain, 139(Pt 4), 1010-3. https://doi.org/10.1093/brain/aww049

Menouti, K., Akiva-Kabiri, L., Banissy, M. J. & Stewart, L. (2015). Timbre-colour synaesthesia: exploring the consistency of associations based on timbre. Cortex, 63, 1-3. https://doi.org/10.1016/j.cortex.2014.08.009

Brattico, E. & Vuust, P. (2017). The urge to judge: Why the judgmental attitude has anything to do with the aesthetic enjoyment of negative emotions. Behavioral and Brain Sciences, 40, [353]. https://doi.org/10.1017/S0140525X17001613

Stupacher, J., Matthews, T. E., Pando-Naude, V., Foster Vander Elst, O. & Vuust, P. (2022). The sweet spot between predictability and surprise: Musical groove in brain, body, and social interactions. Frontiers in Psychology, 13, [906190]. https://doi.org/10.3389/fpsyg.2022.906190

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Revised 26.03.2021

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Hella Kastbjerg