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Center for Music in the Brain

Our publications

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

Møller, C. (2021). At klappe i takt. Turbulens.net : forum for samtidsrefleksion. https://turbulens.net/at-klappe-i-takt/

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.

Møller, C. (2018). Ph.d-stafet: At høre med øjnene. P Psykologernes fagmagasin, 4. årgang(10), 26-28.

Mohseni, H. R., Kringelbach, M. L., Smith, P. P., Green, A. L., Parsons, C. E., Young, K. S., Brittain, J-S., Hyam, J. A., Schweder, P. M., Stein, J. F. & Aziz, T. Z. (2010). Application of a Null-Beamformer to Source Localisation in MEG Data of Deep Brain Stimulation. IEEE Engineering in Medicine and Biology Society Conference Proceedings, 4120-4123.

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

Brattico, E., Tervaniemi, M., Valimaki, V., Van Zuijen, T. & Peretz, T. (2003). Cortical correlates of acquired deafness to dissonance. Annals of the New York Academy of Sciences, 158-160. https://doi.org/10.1196/annals.1284.019

Sipola, T., Cong, F., Ristaniemi, T., Alluri, V., Toiviainen, P., Brattico, E. & Nandi, A. K. (2013). Diffusion map for clustering fMRI spatial maps extracted by Indipendent Component Analysis. IEEE International Workshop on Machine Learning for Signal Processing. https://doi.org/10.1109/MLSP.2013.6661923

Brattico, E., Jacobsen, T., De Baene, W., Nakai, N. & Tervaniemi, M. (2003). Electrical brain responses to descriptive versus evaluative judgments of music. Annals of the New York Academy of Sciences, 155-157. https://doi.org/10.1196/annals.1284.018

Mueller, M., Hoefel, L., Brattico, E. & Jacobsen, T. (2009). Electrophysiological correlates of aesthetic music processing comparing experts with laypersons. Annals of the New York Academy of Sciences, 355-358. https://doi.org/10.1111/j.1749-6632.2009.04846.x

Tervaniemi, M., Tupala, T. & Brattico, E. (2012). Expertise in folk music alters the brain processing of Western harmony. Annals of the New York Academy of Sciences, 147-151. https://doi.org/10.1111/j.749-6632.2011.06428.x

James, A., Fernandes, H., Alves da Mota, P. & Hough, M. (2017). Frontostriatal dysconnectivity in adolescent onset schizophrenia and its associations with cognition: An MRI volumetric and diffusion tensor imaging study. European Psychiatry, 41, S59.

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.

Puolivali, T., Cong, F., Alluri, V., Lin, Q-H., Toiviainen, P., Nandi, A. K., Brattico, E. & Ristaniemi, T. (2013). Semi-blind Independent Component Analysis of functional MRI elicited by continuous listening to music. International Conference on Acoustics Speech and Signal Processing ICASSP, 1310-1314.

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

Stark, E., Stacey, J., Mandy, W., Kringelbach, M. L. & Happé, F. (2021). 'Uncertainty attunement' has explanatory value in understanding autistic anxiety. Trends in Cognitive Sciences, 25(12), 1011-1012. https://doi.org/10.1016/j.tics.2021.09.006

Luppi, A. I., Cabral, J., Cofre, R., Destexhe, A., Deco, G. & Kringelbach, M. L. (2022). Dynamical models to evaluate structure–function relationships in network neuroscience. Nature Reviews Neuroscience, 23(12), 767-768. https://doi.org/10.1038/s41583-022-00646-w

de Fleurian, R., Harrison, P. M. C., Pearce, M. T. & Quiroga-Martinez, D. R. (2019). Reward prediction tells us less than expected about musical pleasure. Proceedings of the National Academy of Sciences, 116(42), 20813-20814. https://doi.org/10.1073/pnas.1913244116

Oswald, J. N., Van Cise, A. M., Dassow, A., Elliott, T., Johnson, M. T., Ravignani, A. & Podos, J. (2022). A Collection of Best Practices for the Collection and Analysis of Bioacoustic Data. Applied Sciences (Switzerland), 12(23), [12046]. https://doi.org/10.3390/app122312046

Spinosa, V., Brattico, E., Campo, F. & Logroscino, G. (2022). A systematic review on resting state functional connectivity in patients with neurodegenerative disease and hallucinations. NeuroImage: Clinical, 35, [103112]. https://doi.org/10.1016/j.nicl.2022.103112

Fjaeldstad, A., Fernandes, H., Nyengaard, J. R. & Ovesen, T. (2018). Bag om smag. Ugeskrift for Læger, 180(18).

Reybrouck, M., Vuust, P. & Brattico, E. (2018). Brain Connectivity Networks and the Aesthetic Experience of Music. Brain sciences, 8(6), [107]. https://doi.org/10.3390/brainsci8060107

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

Jancke, D., Herlitze, S., Kringelbach, M. L. & Deco, G. (2022). Bridging the gap between single receptor type activity and whole-brain dynamics. FEBS Journal, 289(8), 2067-2084. https://doi.org/10.1111/febs.15855

Wang, Q. J., Barbosa Escobar, F., Mathiesen, S. L. & Alves da Mota, P. (2021). Can Eating Make Us More Creative? A Multisensory Perspective. Foods, 10(2), [469]. https://doi.org/10.3390/foods10020469

Displaying results 401 to 450 out of 687

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Revised 26.03.2021

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Hella Kastbjerg