Find

Center for Music in the Brain

Our publications

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

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

Displaying results 651 to 677 out of 677

14

Revised 26.03.2021

-

Hella Kastbjerg