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Center for Music in the Brain

Our publications

Omigie, D., Muellensiefen, D. & Stewart, L. (2012). THE EXPERIENCE OF MUSIC IN CONGENITAL AMUSIA. Music Perception, 30(1), 1-18. https://doi.org/10.1525/MP.2012.30.1.1

Stewart, L., Walsh, V., Frith, U. & Rothwell, J. C. (2001). TMS produces two dissociable types of speech disruption. NeuroImage, 13(3), 472-8. https://doi.org/10.1006/nimg.2000.0701

Petersen, B., Andersen, A. S., Trusbak Haumann, N., Højlund, A., Dietz, M., Michel, F., Kamaric Riis, S., Brattico, E. & Vuust, P. (2020). The CI MuMuFe: A New MMN Paradigm for Measuring Music Discrimination in Electric Hearing. Frontiers in Neuroscience, 14, [2]. https://doi.org/10.3389/fnins.2020.00002

Alonso Martínez, S., Deco, G., Ter Horst, G. J. & Cabral, J. (2020). The Dynamics of Functional Brain Networks Associated With Depressive Symptoms in a Nonclinical Sample. Frontiers in Neural Circuits, 14, [570583]. https://doi.org/10.3389/fncir.2020.570583

Deco, G., Sanz Perl, Y., Bocaccio, H., Tagliazucchi, E. & Kringelbach, M. L. (2022). The INSIDEOUT framework provides precise signatures of the balance of intrinsic and extrinsic dynamics in brain states. Communications Biology, 5(1), [572]. https://doi.org/10.1038/s42003-022-03505-7

Fjaeldstad, A. W., Nørgaard, H. J. & Fernandes, H. M. (2019). The Impact of Acoustic fMRI-Noise on Olfactory Sensitivity and Perception. Neuroscience, 406, 262-267. https://doi.org/10.1016/j.neuroscience.2019.03.028

Näätänen, R., Petersen, B., Torppa, R., Lonka, E. & Vuust, P. (2017). The MMN as a viable and objective marker of auditory development in CI users. Hearing Research, (353), 57-75. https://doi.org/10.1016/j.heares.2017.07.007

De Filippi, E., Uribe, C., Avila-Varela, D. S., Martínez-Molina, N., Gashaj, V., Pritschet, L., Santander, T., Jacobs, E. G., Kringelbach, M. L., Sanz Perl, Y., Deco, G. & Escrichs, A. (2021). The Menstrual Cycle Modulates Whole-Brain Turbulent Dynamics. Frontiers in Neuroscience, 15, [753820]. https://doi.org/10.3389/fnins.2021.753820

Stark, E. A., Cabral, J., Riem, M. M. E., Van IJzendoorn, M. H., Stein, A. & Kringelbach, M. L. (2020). The Power of Smiling: The Adult Brain Networks Underlying Learned Infant Emotionality. Cerebral cortex (New York, N.Y. : 1991), 30(4), 2019-2029. https://doi.org/10.1093/cercor/bhz219

Matrone, C. & Brattico, E. (2015). The Power of music on Alzheimer ’s Disease and the need to understand the underlying molecular mechanisms. Journal of Alzheimer's disease and parkinsonism, 5(3). https://doi.org/10.4172/2161-0460.1000196

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

Yan, X., Joshi, A., Zang, Y., Assunção, F., Fernandes, H. M. & Hummel, T. (2022). The Shape of the Olfactory Bulb Predicts Olfactory Function. Brain sciences, 12(2), [128]. https://doi.org/10.3390/brainsci12020128

Peretz, I., Brattico, E., Jarvenpaa, M. & Tervaniemi, M. (2009). The amusic brain: in tune, out of key, and unaware. Brain, 132, 1277-1286. https://doi.org/10.1093/brain/awp055

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

Magee, W. L. & Stewart, L. (2015). The challenges and benefits of a genuine partnership between Music Therapy and Neuroscience: a dialog between scientist and therapist. Frontiers in Human Neuroscience, 9, 223. https://doi.org/10.3389/fnhum.2015.00223

Toiviainen, P., Burunat, I., Brattico, E., Vuust, P. & Alluri, V. (2020). The chronnectome of musical beat. NeuroImage, 216, [116191]. https://doi.org/10.1016/j.neuroimage.2019.116191

Nieminen, S., Istok, E., Brattico, E. & Tervaniemi, M. (2012). The development of the aesthetic experience of music: Preference, emotions, and beauty. Musicae Scientiae, 16(3), 372-391. https://doi.org/10.1177/1029864912450454

Cruzat, J., Deco, G., Tauste-Campo, A., Principe, A., Costa, A., Kringelbach, M. L. & Rocamora, R. (2018). The dynamics of human cognition: Increasing global integration coupled with decreasing segregation found using iEEG. NeuroImage, 172, 492-505. https://doi.org/10.1016/j.neuroimage.2018.01.064

Deco, G., Kringelbach, M. L., Jirsa, V. K. & Ritter, P. (2017). The dynamics of resting fluctuations in the brain: metastability and its dynamical cortical core. Scientific Reports, 7(1), 3095. https://doi.org/10.1038/s41598-017-03073-5

Shoemark, H., Dahlstrøm, M., Bedford, O. & Stewart, L. (2021). The effect of a voice-centered psycho-educational program on maternal self-efficacy: A feasibility study. International Journal of Environmental Research and Public Health, 18(5), [2537]. https://doi.org/10.3390/ijerph18052537

Jakubowski, K., Halpern, A. R., Grierson, M. & Stewart, L. (2015). The effect of exercise-induced arousal on chosen tempi for familiar melodies. Psychonomic Bulletin & Review, 22(2), 559-65. https://doi.org/10.3758/s13423-014-0687-1

Iorio, C., Brattico, E., Munk Larsen, F., Vuust, P. & Bonetti, L. (2022). The effect of mental practice on music memorization. Psychology of Music, 50(1), 230-244. https://doi.org/10.1177/0305735621995234

Hansen, N. C. (2020). The expectancy dynamics of anti-tonal twelve-tone rows: a commentary and reanalysis of von Hippel & Huron (2020). Empirical Musicology Review, 15(1-2), 128-140. https://doi.org/10.18061/emr.v15i1-2.7806

Stupacher, J. (2019). The experience of flow during sensorimotor synchronization to musical rhythms. Musicae Scientiae, 23(3), 348–361. https://doi.org/10.1177/1029864919836720

Parsons, C. E., Young, K. S., Murray, L., Stein, A. & Kringelbach, M. L. (2010). The functional neuroanatomy of the evolving parent-infant relationship. Progress in Neurobiology, 91(3), 220-41. https://doi.org/10.1016/j.pneurobio.2010.03.001

Wells, C. A., Salvage-Jones, J. A., Li, X., Hitchens, K., Butcher, S., Murray, R. Z., Beckhouse, A. G., Lo, Y-L-S., Manzanero, S., Cobbold, C., Schroder, K., Ma, B., Orr, S., Stewart, L., Lebus, D., Sobieszczuk, P., Hume, D. A., Stow, J., Blanchard, H. & Ashman, R. B. (2008). The macrophage-inducible C-type lectin, Mincle, is an essential component of the innate immune response to Candida albicans. Journal of Immunology, 180(11), 7404-7413.

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

Deco, G., Van Hartevelt, T. J., Fernandes, H. M., Stevner, A. & Kringelbach, M. L. (2016). The most relevant human brain regions for functional connectivity: Evidence for a dynamical workspace of binding nodes from whole-brain computational modelling. NeuroImage, 146, 197-210. https://doi.org/10.1016/j.neuroimage.2016.10.047

Müllensiefen, D., Gingras, B., Musil, J. & Stewart, L. (2014). The musicality of non-musicians: an index for assessing musical sophistication in the general population. PLOS ONE, 9(2), e89642. https://doi.org/10.1371/journal.pone.0089642

Young, K. S., Parsons, C. E., Stein, A., Vuust, P., Craske, M. G. & Kringelbach, M. L. (2017). The neural basis of responsive caregiving behaviour: Investigating temporal dynamics within the parental brain. Behavioural Brain Research, 325, 105-116. https://doi.org/10.1016/j.bbr.2016.09.012

Zou, L-Q., van Hartevelt, T. J., Kringelbach, M. L., Cheung, E. F. C. & Chan, R. C. K. (2016). The neural mechanism of hedonic processing and judgment of pleasant odors: An activation likelihood estimation meta-analysis. Neuropsychology, 30(8), 970-979. https://doi.org/10.1037/neu0000292

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

Fjaeldstad, A. W., Konieczny, D. T., Fernandes, H., Gaini, L. M., Vejlø, M. & Sandberg, K. (2022). The relationship between individual significance of olfaction and measured olfactory function. Current Research in Behavioral Sciences, 3, [100076]. https://doi.org/10.1016/j.crbeha.2022.100076

Williamson, V. J., Cocchini, G. & Stewart, L. (2011). The relationship between pitch and space in congenital amusia. Brain and Cognition, 76(1), 70-6. https://doi.org/10.1016/j.bandc.2011.02.016

Burunat, I., Toiviainen, P., Alluri, V., Bogert, B., Ristaniemi, T., Sams, M. & Brattico, E. (2016). The reliability of continuous brain responses during naturalistic listening to music. NeuroImage, 124(Pt A), 224-31. https://doi.org/10.1016/j.neuroimage.2015.09.005

Costa, M., Bonetti, L., VIgnali, V., Lantieri, C. & Simone, A. (2018). The role of peripheral vision in vertical road sign identification and discrimination. Ergonomics, 61(12), 1619-1634. https://doi.org/10.1080/00140139.2018.1508756

Matthews, T. E., Witek, M. A. G., Heggli, O. A., Penhune, V. B. & Vuust, P. (2019). The sensation of groove is affected by the interaction of rhythmic and harmonic complexity. PLOS ONE, 14(1), [e0204539]. https://doi.org/10.1371/journal.pone.0204539

Jakubowski, K., Farrugia, N., Halpern, A. R., Sankarpandi, S. K. & Stewart, L. (2015). The speed of our mental soundtracks: Tracking the tempo of involuntary musical imagery in everyday life. Memory & Cognition. https://doi.org/10.3758/s13421-015-0531-5

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

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