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Center for Music in the Brain

Our publications

Kajihara, T., Verdonschot, R. G., Sparks, J. & Stewart, L. (2013). Action-perception coupling in violinists. Frontiers in Human Neuroscience, 7, 349. https://doi.org/10.3389/fnhum.2013.00349

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

Karageorghis, C. I., Lyne, L. P., Bigliassi, M. & Vuust, P. (2019). Effects of auditory rhythm on movement accuracy in dance performance. Human Movement Science, 67, [102511]. https://doi.org/10.1016/j.humov.2019.102511

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

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

Kleber, B., Friberg, A., Zeitouni, A. & Zatorre, R. (2016). Experience-dependent modulation of right anterior insula and sensorimotor regions as a function of noise-masked auditory feedback in singers and nonsingers. NeuroImage, 147, 97-110. https://doi.org/10.1016/j.neuroimage.2016.11.059

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

Kliuchko, M., Vuust, P., Toiviainen, P., Tervaniemi, M., Bogert, B. & Brattico, E. (2015). Effects of active vs. passive exposure to a musical style: An MMN study with the musical multifeature paradigm.

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

Kliuchko, M., Heinonen-Guzejev, M., Vuust, P., Tervaniemi, M. & Brattico, E. (2016). A window into the brain mechanisms associated with noise sensitivity. Scientific Reports, 6, 39236. https://doi.org/10.1038/srep39236

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

Kliuchko, M., Haumann, N. T., Huotilainen, M., Vuust, P., Tervaniemi, M. & Brattico, E. (2018). Expertise-dependent sensitivity to mistuning and melody transposition: MEG study with melodic multi-feature MMN paradigm. Abstract from 15th International Conference on Music Perception and Cognition & 10th triennial conference of the European Society for the Cognitive Sciences of Music, Graz, Austria.

Kliuchko, M., Tervaniemi, M., Vuust, P. & Brattico, E. (2018). Probing the functional specialization of auditory encoding following musical training with multi-feature MMN paradigms. Poster session presented at MMN 2018: The 8th Mismatch Negativity Conference, Helsinki, Finland.

Kliuchko, M., Puoliväli, T., Heinonen-Guzejev, M., Tervaniemi, M., Toiviainen, P., Sams, M. & Brattico, E. (2018). Neuroanatomical correlates of noise sensitivity. Poster session presented at 8th Mind Brain Body Symposium, Berlin, Germany.

Kliuchko, M. & Brattico, E. (2019). Interoception in the sensory sensitivities: Evidence from the auditory domain. Cognitive Neuroscience, 10(3), 166-168. https://doi.org/10.1080/17588928.2019.1592142

Kliuchko, M., Brattico, E., Gold, B. P., Tervaniemi, M., Bogert, B., Toiviainen, P. & Vuust, P. (2019). Fractionating auditory priors: A neural dissociation between active and passive experience of musical sounds. PLOS ONE, 14(5), [0216499]. https://doi.org/10.1371/journal.pone.0216499

Kliuchko, M. (2019). The role of musical enculturation on building melodic expectations in the brain. Poster session presented at Brain, Music and Cognition 2019, Jerusalem, Israel.

Knarborg Larsen, H., Heggli, O. A. & Petersen, B. (2019). Marimba, mallet and mind – enhancing the marimba sound by Ki-aikido approach. Journal of New Music Research, 48(5), 469-478. https://doi.org/10.1080/09298215.2019.1657465

Kobeleva, X., López-González, A., Kringelbach, M. L. & Deco, G. (2021). Revealing the Relevant Spatiotemporal Scale Underlying Whole-Brain Dynamics. Frontiers in Neuroscience, 15, [715861]. https://doi.org/10.3389/fnins.2021.715861

Koelsch, S., Vuust, P. & Friston, K. (2019). Predictive Processes and the Peculiar Case of Music. Trends in Cognitive Sciences, 23(1), 63-77. https://doi.org/10.1016/j.tics.2018.10.006

Kohler, N., Novembre, G., Gugnowska, K., Keller, P. E., Villringer, A. & Sammler, D. (2023). Cortico-cerebellar audio-motor regions coordinate self and other in musical joint action. Cerebral Cortex, 33(6), 2804-2822. https://doi.org/10.1093/cercor/bhac243

Kragness, H., Hansen, N. C., Vuust, P., Trainor, L. & Pearce, M. (2016). Information dynamics of boundary perception: Entropy in self-paced music listening. Paper presented at 14th International Conference on Music Perception and Cognition, San Francisco, United States.

Kringelbach, M. L. (2015). The pleasure of food: underlying brain mechanisms of eating and other pleasures. Flavour, 4(20).

Kringelbach, M. L., McIntosh, A. R., Ritter, P., Jirsa, V. K. & Deco, G. (2015). The Rediscovery of Slowness: Exploring the Timing of Cognition. Trends in Cognitive Sciences, 19(10), 616-28. https://doi.org/10.1016/j.tics.2015.07.011

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

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

Kringelbach, M. L., Cruzat, J., Cabral, J., Knudsen, G. M., Carhart-Harris, R., Whybrow, P. C., Logothetis, N. K. & Deco, G. (2020). Dynamic coupling of whole-brain neuronal and neurotransmitter systems. Proceedings of the National Academy of Sciences, 117(17), 9566-9576. https://doi.org/10.1073/pnas.1921475117

Kringelbach, M. L. & Deco, G. (2020). Brain States and Transitions: Insights from Computational Neuroscience. Cell Reports, 32(10), [108128]. https://doi.org/10.1016/j.celrep.2020.108128

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

Kujala, T. & Brattico, E. (2009). Detrimental noise effects on brain's speech functions. Biological Psychology, 81(3), 135-143. https://doi.org/10.1016/j.biopsycho.2009.03.010

Kübler, Nijboer, Mellinger, Matuz, Kleber, B., Eitel-Braitsch, Sellers, Vaughan, Wolpaw & Birbaumer (2005). Brain-computer interfaces - Communication with the P300. Psychophysiology, 19, 128-128.

Langer Bro, M., Jespersen, K. V., Hansen, J. B., Vuust, P., Abildgaard, N., Gram, J. & Johansen, C. (2018). Kind of blue - a systematic review and meta-analysis of music intervention in cancer treatment. Psycho-Oncology, 27(2), 386–400.

Lapenta, O. M., Keller, P. E., Nozaradan, S. & Varlet, M. (2023). Spatial and temporal (non)binding of audiovisual rhythms in sensorimotor synchronisation. Experimental Brain Research, 241(3), 875-887. https://doi.org/10.1007/s00221-023-06569-x

Launay, J., Grube, M. & Stewart, L. (2014). Dysrhythmia: a specific congenital rhythm perception deficit. Frontiers in Psychology, 5, 18. https://doi.org/10.3389/fpsyg.2014.00018

Lebedev, A. V., Abé, C., Acar, K., Deco, G., Kringelbach, M. L., Ingvar, M. & Petrovic, P. (2022). Large-scale societal dynamics are reflected in human mood and brain. Scientific Reports, 12, [4646]. https://doi.org/10.1038/s41598-022-08569-3

Lippolis, M., Müllensiefen, D., Frieler, K., Matarrelli, B., Vuust, P., Cassibba, R. & Brattico, E. (2022). Learning to play a musical instrument in the middle school is associated with superior audiovisual working memory and fluid intelligence: A cross-sectional behavioral study. Frontiers in Psychology, 13, [982704]. https://doi.org/10.3389/fpsyg.2022.982704

Liu, F., Jiang, C., Pfordresher, P. Q., Mantell, J. T., Xu, Y., Yang, Y. & Stewart, L. (2013). Individuals with congenital amusia imitate pitches more accurately in singing than in speaking: implications for music and language processing. Attention, Perception & Psychophysics, 75(8), 1783-98. https://doi.org/10.3758/s13414-013-0506-1

Liu, F., Patel, A. D., Fourcin, A. & Stewart, L. (2010). Intonation processing in congenital amusia: discrimination, identification and imitation. Brain, 133(Pt 6), 1682-93. https://doi.org/10.1093/brain/awq089

Liu, F., Jiang, C., Thompson, W. F., Xu, Y., Yang, Y. & Stewart, L. (2012). The mechanism of speech processing in congenital amusia: evidence from Mandarin speakers. PLOS ONE, 7(2), e30374. https://doi.org/10.1371/journal.pone.0030374

Liu, C., Fa, R., Abu-Jamous, B., Brattico, E. & Nandi, A. (2015). Scalable clustering based on enhanced-smart for large-scale fMRI datasets. I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings, 962-966.

Liu, C., Abu-Jamous, B., Brattico, E. & Nandi, A. (2015). Clustering consistency in neuroimaging data analysis. In IEEE Proceedings of 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) 2015 (pp. 1118-1122). IEEE.

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

Liu, C., Brattico, E., Abu-Jamous, B., Pereira, C. S., Jacobsen, T. & Nandi, A. K. (2017). Effect of Explicit Evaluation on Neural Connectivity Related to Listening to Unfamiliar Music. Frontiers in Human Neuroscience, 11, [611]. https://doi.org/10.3389/fnhum.2017.00611

Livingstone-Lee, S. A., Murchison, S., Zeman, P. M., Gandhi, M., van Gerven, D., Stewart, L., Livingston, N. J. & Skelton, R. W. (2011). Simple gaze analysis and special design of a virtual Morris water maze provides a new method for differentiating egocentric and allocentric navigational strategy choice. Behavioural Brain Research, 225(1), 117-25. https://doi.org/10.1016/j.bbr.2011.07.005

Lord, L-D., Expert, P., Fernandes, H., Petri, G., Van Hartevelt, T., Vaccarino, F., Deco, G., Turkheimer, F. & Kringelbach, M. (2016). Insights into brain architectures from the homological scaffolds of functional connectivity networks. Frontiers in Systems Neuroscience, 10(85). https://doi.org/10.3389/fnsys.2016.00085

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

Lord, L. D., Expert, P., Atasoy, S., Roseman, L., Rapuano, K., Lambiotte, R., Nutt, D. J., Deco, G., Carhart-Harris, R. L., Kringelbach, M. L. & Cabral, J. (2019). Dynamical exploration of the repertoire of brain networks at rest is modulated by psilocybin. NeuroImage, 199, 127-142. https://doi.org/10.1016/j.neuroimage.2019.05.060

Lumaca, M. & Baggio, G. (2017). Cultural Transmission and Evolution of Melodic Structures in Multi-generational Signaling Games. Artificial Life, 23(3), 406-423.

Lumaca, M. & Baggio, G. (2018). Signaling games and the evolution of structure in language and music: A reply to Ravignani & Verhoef (2018). Artificial Life, 154.

Lumaca, M., Ravignani, A. & Baggio, G. (2018). Music evolution in the laboratory: Cultural transmission meets neurophysiology. Frontiers in Neuroscience, 12, 246.

Displaying results 301 to 350 out of 687

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Revised 26.03.2021

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