Find

Center for Music in the Brain

Our publications

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

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

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

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

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.

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

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

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

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

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

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

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

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

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

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

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

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 of the United States of America, 116(42), 20813-20814. https://doi.org/10.1073/pnas.1913244116

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

Displaying results 351 to 400 out of 619

8

Revised 26.03.2021

-

Hella Kastbjerg