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Center for Music in the Brain

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Heggli, O. A., Konvalinka, I., Kringelbach, M. L. & Vuust, P. (2021). A Metastable Attractor Model of Self-Other Integration (MEAMSO) in Rhythmic Synchronization. Philosophical Transactions of the Royal Society B: Biological Sciences, 376(1835), Article 20200332. https://doi.org/10.1098/rstb.2020.0332

Tanne, A., Ma, B., Boudou, F., Tailleux, L., Botella, H., Badell, E., Levillain, F., Taylor, M. E., Drickamer, K., Nigou, J., Dobos, K. M., Puzo, G., Vestweber, D., Wild, M. K., Marcinko, M., Sobieszczuk, P., Stewart, L., Lebus, D., Gicquel, B. & Neyrolles, O. (2009). A murine DC-SIGN homologue contributes to early host defense against Mycobacterium tuberculosis. Journal of Experimental Medicine, 206(10), 2205-20. https://doi.org/10.1084/jem.20090188

Criscuolo, A., Pando-Naude, V., Bonetti, L., Vuust, P. & Brattico, E. (2022). An ALE meta-analytic review of musical expertise. Scientific Reports, 12(1), Article 11726. https://doi.org/10.1038/s41598-022-14959-4

Pando-Naude, V., Patyczek, A., Bonetti, L. & Vuust, P. (2021). An ALE meta-analytic review of top-down and bottom-up processing of music in the brain. Scientific Reports, 11(1), Article 20813. https://doi.org/10.1038/s41598-021-00139-3

Stewart, L. (2005). A neurocognitive approach to music reading. Annals of the New York Academy of Sciences, 1060, 377-86. https://doi.org/10.1196/annals.1360.032

Jadoul, Y., Hersh, T. A., Domingos, E. F., Gamba, M., Favaro, L. & Ravignani, A. (2025). An evolutionary model of rhythmic accelerando in animal vocal signalling. PLOS Computational Biology, 21(4), Article e1013011. https://doi.org/10.1371/journal.pcbi.1013011

Floridou, G. A., Williamson, V. J. & Stewart, L. (2017). A novel indirect method for capturing involuntary musical imagery under varying cognitive load. Quarterly Journal of Experimental Psychology, 70(11), 1-11. https://doi.org/10.1080/17470218.2016.1227860

Coelho, A., Magalhães, R., Moreira, P. S., Amorim, L., Portugal-Nunes, C., Castanho, T., Santos, N. C., Sousa, N. & Fernandes, H. M. (2022). A novel method for estimating connectivity-based parcellation of the human brain from diffusion MRI: Application to an aging cohort. Human Brain Mapping, 43(8), 2419-2443. https://doi.org/10.1002/hbm.25773

Haumann, N. T., Kliuchko, M., Vuust, P. & Brattico, E. (2018). Applying Acoustical and Musicological Analysis to Detect Brain Responses to Realistic Music: A Case Study. Applied Sciences, 8(5), Article 716. https://doi.org/10.3390/app8050716

Bruzzone, S. E. P., Trusbak Haumann, N., Kliuchko, M., Vuust, P. & Brattico, E. (2021). Applying Spike-density component analysis for high-accuracy auditory event-related potentials in children. Clinical Neurophysiology, 132(8), 1887-1896. https://doi.org/10.1016/j.clinph.2021.05.007

Trusbak Haumann, N., Hansen, B., Huotilainen, M., Vuust, P. & Brattico, E. (2020). Applying stochastic spike train theory for high-accuracy human MEG/EEG. Journal of Neuroscience Methods, 340, Article 108743. https://doi.org/10.1016/j.jneumeth.2020.108743

Griffiths, T. D., Kumar, S., Warren, J. D., Stewart, L., Stephan, K. E. & Friston, K. J. (2007). Approaches to the cortical analysis of auditory objects. Hearing Research, 229(1-2), 46-53. https://doi.org/10.1016/j.heares.2007.01.010

Jespersen, K. V., Otto, M., Kringelbach, M. L., Van Someren, E. & Vuust, P. (2019). A randomized controlled trial of bedtime music for insomnia disorder. Journal of Sleep Research, 28(4), Article e12817. https://doi.org/10.1111/jsr.12817

Paldam, E., Roepstorff, A., Steensgaard, R., Lundsgård, S. S., Steensig, J. & Gebauer, L. (2022). A robot or a dumper truck? Facilitating play-based social learning across neurotypes. Autism & Developmental Language Impairments, 7. https://doi.org/10.1177/23969415221086714

Hansen, N. C. & Reymore, L. (2021). Articulatory motor planning and timbral idiosyncrasies as underlying mechanisms of instrument-specific absolute pitch in expert musicians. PLOS ONE, 16(2 ), Article e0247136. https://doi.org/10.1371/journal.pone.0247136

Clemente, A., Vila-Vidal, M., Pearce, M. T., Aguiló, G., Corradi, G. & Nadal, M. (2020). A Set of 200 Musical Stimuli Varying in Balance, Contour, Symmetry, and Complexity: Behavioral and Computational Assessments. Behavior Research Methods, 52(4), 1491-1509. https://doi.org/10.3758/s13428-019-01329-8

Grimaldi, M., Sisinni, B., Fivela, B. G., Invitto, S., Resta, D., Alku, P. & Brattico, E. (2014). Assimilation of L2 vowels to L1 phonemes governs L2 learning in adulthood: a behavioral and ERP study. Frontiers in Human Neuroscience, 8, Article 279. https://doi.org/10.3389/fnhum.2014.00279

Kleber, B., Sitges, C., Brattico, E., Vuust, P. & Zamorano, A. M. (2025). Association Between Interoceptive Accuracy and Pain Perception: Insights From Trained Musicians and Athletes. European journal of pain (London, England), 29(5), e70012. Article e70012. https://doi.org/10.1002/ejp.70012

Brownlee, WJ., Altmann, DR., Alves Da Mota, P., Swanton, JK., Miszkiel, KA., Gandini Wheeler-Kingshott, CAM., Ciccarelli, O. & Miller, DH. (2017). Association of asymptomatic spinal cord lesions and atrophy with disability 5 years after a clinically isolated syndrome. Multiple Sclerosis Journal, 23(5), 665–674.

Fernández Rubio, G., Carlomagno, F., Vuust, P., Kringelbach, M. L. & Bonetti, L. (2022). Associations between abstract working memory abilities and brain activity underlying long-term recognition of auditory sequences. PNAS Nexus, 1(4), 1-10. Article pgac216. https://doi.org/10.1093/pnasnexus/pgac216

Hoy, C. W., Quiroga-Martinez, D. R., Sandoval, E., King-Stephens, D., Laxer, K. D., Weber, P., Lin, J. J. & Knight, R. T. (2023). Asymmetric coding of reward prediction errors in human insula and dorsomedial prefrontal cortex. Nature Communications, 14(1), Article 8520. https://doi.org/10.1038/s41467-023-44248-1

Stupacher, J., Bechtold, T. & Senn, O. (2024). A text mining approach to the use of “groove” in everyday language. Psychology of Music, 52(3), 340-361. https://doi.org/10.1177/03057356231205883

Reymore, L. & Hansen, N. C. (2020). A Theory of Instrument-Specific Absolute Pitch. Frontiers in Psychology, 11, Article 560877. https://doi.org/10.3389/fpsyg.2020.560877

Mencke, I., Omigie, D., Wald-Fuhrmann, M. & Brattico, E. (2019). Atonal Music: Can Uncertainty Lead to Pleasure? Frontiers in Neuroscience, 12(979), Article 979. https://doi.org/10.3389/fnins.2018.00979

Mencke, I., Omigie, D., Quiroga-Martinez, D. R. & Brattico, E. (2022). Atonal Music as a Model for Investigating Exploratory Behavior. Frontiers in Neuroscience, 16, Article 793163. https://doi.org/10.3389/fnins.2022.793163

Burchardt, L. S., Van De Sande, Y., Kehy, M., Gamba, M., Ravignani, A. & Pouw, W. (2024). A toolkit for the dynamic study of air sacs in siamang and other elastic circular structures. PLOS Computational Biology, 20(6), Article e1012222. https://doi.org/10.1371/journal.pcbi.1012222

Boccard, S. G., Fernandes, H., Jbabdi, S., van Hartevelt, T. J., Kringelbach, M. L., Quaghebeur, G., Moir, L., Mancebo, V. P., Pereira, E. A., Fitzgerald, J. J., Green, A. L., Stein, J. & Aziz, T. Z. (2015). A tractography study of Deep Brain Stimulation of the Anterior Cingulate Cortex in chronic pain: a key to improve the targeting. World Neurosurgery. https://doi.org/10.1016/j.wneu.2015.08.065

Møller, C., Garza-Villarreal, E. A., Hansen, N. C., Højlund, A., Bærentsen, K. B., Chakravarty, M. M. & Vuust, P. (2021). Audiovisual structural connectivity in musicians and non-musicians: a cortical thickness and diffusion tensor imaging study. Scientific Reports, 11(1), Article 4324. https://doi.org/10.1038/s41598-021-83135-x

Stefaniak, J. D., Lambon Ralph, M. A., De Dios Perez, B., Griffiths, T. D. & Grube, M. (2021). Auditory beat perception is related to speech output fluency in post-stroke aphasia. Scientific Reports, 11, Article 3168. https://doi.org/10.1038/s41598-021-82809-w

Zioga, I., Harrison, P. M. C., Pearce, M. T., Bhattacharya, J. & Luft, C. D. B. (2020). Auditory but not audiovisual cues lead to higher neural sensitivity to the statistical regularities of an unfamiliar musical style. Journal of Cognitive Neuroscience, 32(12), 2241-2259. https://doi.org/10.1162/jocn_a_01614

Robson, H., Griffiths, T. D., Grube, M. & Woollams, A. M. (2019). Auditory, Phonological, and Semantic Factors in the Recovery From Wernicke’s Aphasia Poststroke: Predictive Value and Implications for Rehabilitation. Neurorehabilitation and Neural Repair, 33(10), 800-812. https://doi.org/10.1177/1545968319868709

Bonetti, L., Haumann, N. T., Brattico, E., Kliuchko, M., Vuust, P., Särkämö, T. & Näätänen, R. (2018). Auditory sensory memory and working memory skills: Association between frontal MMN and performance scores. Brain Research, 1700, 86-98. https://doi.org/10.1016/j.brainres.2018.06.034

Stark, E., Stacey, J., Mandy, W., Kringelbach, M. L. & Happé, F. (2021). Autistic Cognition: Charting Routes to Anxiety. Trends in Cognitive Sciences, 25(7), 571-581. https://doi.org/10.1016/j.tics.2021.03.014

Stewart, M. E., Griffiths, T. D. & Grube, M. (2018). Autistic Traits and Enhanced Perceptual Representation of Pitch and Time. Journal of Autism and Developmental Disorders, 48(4), 1350-1358.

Desser, D., Assunção, F., Yan, X., Alves, V., Fernandes, H. & Hummel, T. (2021). Automatic segmentation of the olfactory bulb. Brain sciences, 11(9), Article 1141. https://doi.org/10.3390/brainsci11091141

Deco, G., Cruzat, J., Cabral, J., Tagliazucchi, E., Laufs, H., Logothetis, N. K. & Kringelbach, M. L. (2019). Awakening: Predicting external stimulation to force transitions between different brain states. Proceedings of the National Academy of Sciences (PNAS), 116(36), 18088-18097. https://doi.org/10.1073/pnas.1905534116

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. Article 39236. https://doi.org/10.1038/srep39236

Møller, C., Stupacher, J., Celma-Miralles, A. & Vuust, P. (2021). Beat perception in polyrhythms: Time is structured in binary units. PLOS ONE, 16(8 ), Article e0252174. https://doi.org/10.1371/journal.pone.0252174

Brattico, E., Brusa, A., Dietz, M., Jacobsen, T., Fernandes, H. M., Gaggero, G., Toiviainen, P., Vuust, P. & Proverbio, A. M. (2025). Beauty and the brain – Investigating the neural and musical attributes of beauty during naturalistic music listening. Neuroscience, 567, 308-325. https://doi.org/10.1016/j.neuroscience.2024.12.008

Stewart, L., Henson, R., Kampe, K., Walsh, V., Turner, R. & Frith, U. (2003). Becoming a pianist. An fMRI study of musical literacy acquisition. Annals of the New York Academy of Sciences, 999, 204-8.

Jespersen, K. V., Madsen, J. & Vuust, P. (2020). Bedtime Music for Sleep Problems in older Adults with Dementia: a pilot feasibility Study. Music and Medicine, 12(4), 222-230. https://mmd.iammonline.com/index.php/musmed/index

Sadaphal, D. P., Blum, C. R., Keller, P. E. & Fitch, W. T. (2025). Beyond perfect synchrony: shared interpersonal rhythmic timing enhances self-other merging judgements. Royal Society Open Science, 12(3), Article 241501. https://doi.org/10.1098/rsos.241501

Manriquez P, R., Kotz, S. A., Ravignani, A. & de Boer, B. (2024). Bioacoustic classification of a small dataset of mammalian vocalisations using deep learning. Bioacoustics, 33(4), 354-371. https://doi.org/10.1080/09524622.2024.2354468

Moguilner, S., Herzog, R., Perl, Y. S., Medel, V., Cruzat, J., Coronel, C., Kringelbach, M., Deco, G., Ibáñez, A. & Tagliazucchi, E. (2024). Biophysical models applied to dementia patients reveal links between geographical origin, gender, disease duration, and loss of neural inhibition. Alzheimer's Research & Therapy, 16(1), Article 79. https://doi.org/10.1186/s13195-024-01449-0

Stewart, L., Henson, R., Kampe, K., Walsh, V., Turner, R. & Frith, U. (2003). Brain changes after learning to read and play music. NeuroImage, 20(1), 71-83.

Fjældstad, A., Fernandes, H., van Hartevelt, T. J., Gleesborg, C., Møller, A., Ovesen, T. & Kringelbach, M. L. (2017). Brain fingerprints of olfaction: a novel structural method for assessing olfactory cortical networks in health and disease. Scientific Reports, 7(7), Article 42534. https://doi.org/10.1038/srep42534

Harry, B. B., Margulies, D. S., Falkiewicz, M. & Keller, P. E. (2023). Brain networks for temporal adaptation, anticipation, and sensory-motor integration in rhythmic human behavior. Neuropsychologia, 183, Article 108524. https://doi.org/10.1016/j.neuropsychologia.2023.108524

Bonetti, L., Bruzzone, S. E. P., Sedghi, N. A., Haumann, N. T., Paunio, T., Kantojärvi, K., Kliuchko, M., Vuust, P. & Brattico, E. (2021). Brain predictive coding processes are associated to COMT gene Val158Met polymorphism. NeuroImage, 233, Article 117954. https://doi.org/10.1016/j.neuroimage.2021.117954

Bonetti, L., Brattico, E., Bruzzone, S. E. P., Donati, G., Deco, G., Pantazis, D., Vuust, P. & Kringelbach, M. L. (2023). Brain recognition of previously learned versus novel temporal sequences: A differential simultaneous processing. Cerebral Cortex, 33(9), 5524–5537. https://doi.org/10.1093/cercor/bhac439

Petersen, B., Weed, E., Sandmann, P., Brattico, E., Hansen, M., Sørensen, S. D. & Vuust, P. (2015). Brain responses to musical feature changes in adolescent cochlear implant users. Frontiers in Human Neuroscience. https://doi.org/10.3389/fnhum.2015.00007

Displaying results 351 to 400 out of 883

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