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Center for Music in the Brain

Our publications

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

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), [11048]. https://doi.org/10.1038/s41598-019-47471-3

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

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), [12422]. https://doi.org/10.1038/s41598-021-91820-0

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

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

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

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.

Witek, M. A. G., Matthews, T., Bodak, R., Blausz, M. W., Penhune, V. & Vuust, P. (2023). Musicians and non-musicians show different preference profiles for single chords of varying harmonic complexity. PLOS ONE, 18(2 February), [e0281057]. https://doi.org/10.1371/journal.pone.0281057

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, [907540]. https://doi.org/10.3389/fnins.2022.907540

Quiroga-Martinez, D. R., Hansen, N. C., Hojlund, A., Pearce, M., Brattico, E., Holmes, E., Friston, K. & Vuust, P. (2021). Musicianship and melodic predictability enhance neural gain in auditory cortex during pitch deviance detection. Human Brain Mapping, 42(17), 5595-5608. https://doi.org/10.1002/hbm.25638

Rosso, M., Heggli, O. A., Maes, P. J., Vuust, P. & Leman, M. (2022). Mutual beta power modulation in dyadic entrainment. NeuroImage, 257, [119326]. https://doi.org/10.1016/j.neuroimage.2022.119326

Teki, S., Kumar, S., von Kriegstein, K., Stewart, L., Lyness, C. R., Moore, B. C. J., Capleton, B. & Griffiths, T. D. (2012). Navigating the auditory scene: an expert role for the hippocampus. The Journal of neuroscience : the official journal of the Society for Neuroscience, 32(35), 12251-7. https://doi.org/10.1523/JNEUROSCI.0082-12.2012

Lumaca, M., Vuust, P. & Baggio, G. (2022). Network Analysis of Human Brain Connectivity Reveals Neural Fingerprints of a Compositionality Bias in Signaling Systems. Cerebral Cortex, 32(8), 1704-1720. https://doi.org/10.1093/cercor/bhab307

Engel, A., Hoefle, S., Monteiro, M. C., Moll, J. & Keller, P. E. (2022). Neural Correlates of Listening to Varying Synchrony Between Beats in Samba Percussion and Relations to Feeling the Groove. Frontiers in Neuroscience, 16, [779964]. https://doi.org/10.3389/fnins.2022.779964

Cameron, D. J., Zioga, I., Lindsen, J. P., Pearce, M. T., Wiggins, G. A., Potter, K. & Bhattacharya, J. (2019). Neural entrainment is associated with subjective groove and complexity for performed but not mechanical musical rhythms. Experimental Brain Research, 237(8), 1981-1991. https://doi.org/10.1007/s00221-019-05557-4

Krohn, K. I., Brattico, E., Valimaki, V. & Tervaniemi, M. (2007). Neural representations of the hierarchical scale pitch structure. Music Perception, 24(3), 281-296. https://doi.org/10.1525/MP.2007.24.3.281

Zou, L-Q., Zhou, H-Y., Zhuang, Y., van Hartevelt, T. J., Lui, S. S. Y., Cheung, E. F. C., Møller, A., Kringelbach, M. L. & Chan, R. C. K. (2018). Neural responses during the anticipation and receipt of olfactory reward and punishment in human. Neuropsychologia, 111, 172-179. https://doi.org/10.1016/j.neuropsychologia.2018.02.003

Martínez-Molina, N., Siponkoski, S. T., Pitkäniemi, A., Moisseinen, N., Kuusela, L., Pekkola, J., Laitinen, S., Särkämö, E. R., Melkas, S., Kleber, B., Schlaug, G., Sihvonen, A. & Särkämö, T. (2022). Neuroanatomical correlates of speech and singing production in chronic post-stroke aphasia. Brain Communications, 4(1), [fcac001]. https://doi.org/10.1093/braincomms/fcac001

Kliuchko, M., Puoliväli, T., Heinonen-Guzejev, M., Tervaniem, M., Toiviainen, P., Sams, M. & Brattico, E. (2018). Neuroanatomical substrate of noise sensitivity. NeuroImage, 167, 309-315. https://doi.org/10.1016/j.neuroimage.2017.11.041

Vuust, P., Brattico, E., Glerean, E., Seppänen, M., Pakarinen, S., Tervaniemi, M. & Näätänen, R. (2011). New fast mismatch negativity paradigm for determining the neural prerequisites for musical ability. Cortex, 47(9), 1091-8. https://doi.org/10.1016/j.cortex.2011.04.026

Celma-Miralles, A. & Toro, J. M. (2020). Non-human animals detect the rhythmic structure of a familiar tune. Psychonomic Bulletin and Review, 27(4), 694-699. https://doi.org/10.3758/s13423-020-01739-2

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. [2]. https://doi.org/10.1525/mp.2016.33.4.414

Deco, G., Tagliazucchi, E., Laufs, H., Sanjuán, A. & Kringelbach, M. L. (2017). Novel Intrinsic Ignition Method Measuring Local-Global Integration Characterizes Wakefulness and Deep Sleep. eNeuro , 4(5). https://doi.org/10.1523/ENEURO.0106-17.2017

Fernandes, H. M., van Hartevelt, T. J., Boccard, S. G. J., Owen, S. L. F., Cabral, J., Deco, G., Green, A. L., Fitzgerald, J. J., Aziz, T. Z. & Kringelbach, M. L. (2015). Novel fingerprinting method characterises the necessary and sufficient structural connectivity from deep brain stimulation electrodes for a successful outcome. New Journal of Physics, 17(1), 015001. http://stacks.iop.org/1367-2630/17/i=1/a=015001

Vuust, P., Dietz, M., Witek, M. & Kringelbach, M. L. (2018). Now you hear it: a predictive coding model for understanding rhythmic incongruity. Annals of the New York Academy of Sciences, 1423(1), 19-29. https://doi.org/10.1111/nyas.13622

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

Fjaeldstad, A., Kjaergaard, T., van Hartevelt, T. J., Moeller, A., Kringelbach, M. L. & Ovesen, T. (2015). Olfactory screening: Validation of Sniffin' Sticks in Denmark. Clinical Otolaryngology, 40(6), 545-550. https://doi.org/10.1111/coa.12405

Kringelbach, M. L., Stark, E. A., Alexander, C., Bornstein, M. H. & Stein, A. (2016). On Cuteness: Unlocking the Parental Brain and Beyond. Trends in Cognitive Sciences, 20(7), 545-58. https://doi.org/10.1016/j.tics.2016.05.003

Criscuolo, A., Bonetti, L., Sarkamo, T., Kliuchko, M. & Brattico, E. (2019). On the Association Between Musical Training, Intelligence and Executive Functions in Adulthood. Frontiers in Psychology, 10, [1704]. https://doi.org/10.3389/fpsyg.2019.01704

Shestakova, A., Brattico, E., Soloviev, A., Klucharev, U. & Huotilainen, M. (2004). Orderly cortical representation of vowel categories presented by multiple exemplars. Brain Research, 21(3), 342-350. https://doi.org/10.1016/j.cogbrainres.2004.06.011

Kleber, B., Birbaumer, Veit, Trevorrow & Lotze (2007). Overt and imagined singing of an Italian aria. NeuroImage, 36(3), 889-900.

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. [75]. https://doi.org/10.1017/S0140525X20001235

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

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), [e1008304]. https://doi.org/10.1371/journal.pcbi.1008304

Matthews, T. E., Witek, M. A. G., Thibodeau, J. L. N., Vuust, P. & Penhune, V. B. (2022). Perceived Motor Synchrony With the Beat is More Strongly Related to Groove Than Measured Synchrony. Music Perception, 39(5), 423-442. https://doi.org/10.1525/MP.2022.39.5.423

Williamson, V. J., Liu, F., Peryer, G., Grierson, M. & Stewart, L. (2012). Perception and action de-coupling in congenital amusia: sensitivity to task demands. Neuropsychologia, 50(1), 172-80. https://doi.org/10.1016/j.neuropsychologia.2011.11.015

Marin, M. M., Gingras, B. & Stewart, L. (2012). Perception of musical timbre in congenital amusia: categorization, discrimination and short-term memory. Neuropsychologia, 50(3), 367-78. https://doi.org/10.1016/j.neuropsychologia.2011.12.006

Lumaca, M., Dietz, M., Hansen, N. C., Quiroga Martinez, D. R. & Vuust, P. (2021). Perceptual learning of tone patterns changes the effective connectivity between Heschl's gyrus and planum temporale. Human Brain Mapping, 42(4), 941-952. https://doi.org/10.1002/hbm.25269

Deco, G., Cabral, J., Saenger, V. M., Boly, M., Tagliazucchi, E., Laufs, H., Van Someren, E., Jobst, B., Stevner, A. & Kringelbach, M. L. (2018). Perturbation of whole-brain dynamics in silico reveals mechanistic differences between brain states. NeuroImage, 169, 46-56. https://doi.org/10.1016/j.neuroimage.2017.12.009

Perl, Y. S., Pallavicini, C., Ipiña, I. P., Demertzi, A., Bonhomme, V., Martial, C., Panda, R., Annen, J., Ibañez, A., Kringelbach, M., Deco, G., Laufs, H., Sitt, J., Laureys, S. & Tagliazucchi, E. (2021). Perturbations in dynamical models of whole-brain activity dissociate between the level and stability of consciousness. PLOS Computational Biology, 17(7), [e1009139]. https://doi.org/10.1371/journal.pcbi.1009139

Ahrends, C., Bravo, F., Kringelbach, M. L., Vuust, P. & Rohrmeier, M. A. (2019). Pessimistic outcome expectancy does not explain ambiguity aversion in decision-making under uncertainty. Scientific Reports, 9, [12177]. https://doi.org/10.1038/s41598-019-48707-y

Kaasgaard, M., Rasmussen, D. B., Løkke, A., Vuust, P., Hilberg, O. & Bodtger, U. (2022). Physiological changes related to 10 weeks of singing for lung health in patients with COPD. B M J Open Respiratory Research, 9(1), [e001206]. https://doi.org/10.1136/bmjresp-2022-001206

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

Berridge, K. C. & Kringelbach, M. L. (2015). Pleasure Systems in the Brain. Neuron, 86(3), 646-664. https://doi.org/10.1016/j.neuron.2015.02.018

Stark, E. A., Parsons, C. E., Hartevelt, T. J. V., Charquero-Ballester, M., McManners, H., Ehlers, A., Stein, A. & Kringelbach, M. L. (2015). Post-traumatic stress influences the brain even in the absence of symptoms: A systematic, quantitative meta-analysis of neuroimaging studies. Neuroscience & Biobehavioral Reviews, 56, 207-221. https://doi.org/10.1016/j.neubiorev.2015.07.007

Seppanen, M., Brattico, E. & Tervaniemi, M. (2007). Practice strategies of musicians modulate neural processing and the learning of sound-patterns. Neurobiology of Learning and Memory, 87(2), 236-247. https://doi.org/10.1016/j.nlm.2006.08.011

Takegata, R., Brattico, E., Tervaniemi, M., Varyagina, O., Naatanen, R. & Winkler, M. (2005). Preattentive representation of feature conjunctions for concurrent spatially distributed auditory objects. Brain Research, 25(1), 169-179. https://doi.org/10.1016/j.cogbrainres.2005.05.006

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

Mencke, I., Quiroga-Martinez, D. R., Omigie, D., Michalareas, G., Schwarzacher, F., Haumann, N. T., Vuust, P. & Brattico, E. (2021). Prediction under uncertainty: Dissociating sensory from cognitive expectations in highly uncertain musical contexts. Brain Research, 1773, [147664]. https://doi.org/10.1016/j.brainres.2021.147664

Displaying results 251 to 300 out of 687

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Revised 26.03.2021

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Hella Kastbjerg