Our publications

Contribution to book anthology

Petersen, B. (2018). KUV på Det Jyske Musikkonservatorium. In KUV-netværkets årbog 2018 (pp. 50)

Petersen, B. (2015). Music in the deaf adolescent brain. In H. Blæsild Vuust & L. Østergaard (Eds.), CFIN Annual Report 2014 (pp. 42-44).

Petersen, B. (2010). Music in the (deaf) brain. In CFIN Annual report 2009 (pp. 40-41)

Petersen, B. & Friis Andersen, A. S. (2018). The Times They Are A Changin’: Two Novel EEG Paradigms for Studying Music Discrimination in Electric Hearing. In Annual report 2017 (pp. 42-47) http://musicinthebrain.au.dk/fileadmin/user_upload/Annual_Report_2017_2.pdf

Vuust, P. (2018). Groove on the Brain. In M. E. P. Davies, M. Aramaki, R. Kronland-Martinet & S. Ystad (Eds.), Music Technology with Swing - 13th International Symposium, CMMR 2017, Revised Selected Papers (pp. 101-110). Springer. https://doi.org/10.1007/978-3-030-01692-0_7

Tsatsishvili, V., Cong, F., Puoliväli, T., Alluri, V., Toiviainen, P., Nandi, A. K., Brattico, E. & Ristaniemi, T. (2013). Dimension reduction for individual ICA to decompose FMRI during real-world experiences: Principal component analysis vs. canonical correlation analysis. In ESANN 2013 proceedings, 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (pp. 137-142)

Tsatsishvili, V., Cong, F., Ristaniemi, T., Toiviainen, P., Alluri, V., Brattico, E. & Nandi, A. (2014). Generation of stimulus features for analysis of FMRI during natural auditory experiences. In European Signal Processing Conference (pp. 2490-2494). Article 6952938 European Signal Processing Conference, EUSIPCO.

Stupacher, J. A. & Wood, G. (2018). Effects of cultural background and musical preference on affective social entrainment with music. In Proceedings of ICMPC15/ESCOM10 (pp. 438-441).

Quiroga Martinez, D. R., Bonetti, L., Knight, R. T. & Vuust, P. (2022). Representational dynamics of listened and imagined musical sound sequences. In 2022 Conference on Cognitive Computational Neuroscience https://doi.org/10.32470/CCN.2022.1069-0

Pedro, K., Grierson, M., Bodak, R., Ward, N., Brander, F., Kelly, K., Newman, N. & Stewart, L. (2016). Motivating stroke rehabilitation through music: A feasibility study using digital musical instruments in the home. In CHI 2016 - Proceedings, 34th Annual CHI Conference on Human Factors in Computing Systems (pp. 1781-1785) https://doi.org/10.1145/2858036.2858376

Niranjan, D., Toiviainen, P., Brattico, E. & Alluri, V. (2019). Dynamic Functional Connectivity in the Musical Brain. In P. Liang, V. Goel & C. Shan (Eds.), Brain Informatics : 12th International Conference, BI 2019 Haikou, China, December 13–15, 2019 Proceedings (pp. 82-91). Springer. https://doi.org/10.1007/978-3-030-37078-7_9

Moorthigari, V., Carlson, E., Toiviainen, P., Brattico, E. & Alluri, V. (2020). Differential Effects of Trait Empathy on Functional Network Centrality. In M. Mahmud, S. Vassanelli, M. S. Kaiser & N. Zhong (Eds.), Brain informatics (pp. 107-117). Springer. https://doi.org/10.1007/978-3-030-59277-6_10

Liu, C., Abu-Jamous, B., Brattico, E. & Nandi, A. (2015). Clustering consistency in neuroimaging data analysis. In IEEE Proceedings of 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) 2015 (pp. 1118-1122). IEEE.

Jensen, M. S., Heggli, O. A., Alves da Mota, P. & Vuust, P. (2017). A low-cost MRI compatible keyboard. In Proceedings of the international conference on new interfaces for musical expression (pp. 257-260)

Heinonen-Guzejev, M., Klyuchko, M., Heikkilä, K., Spinosa, V., Tervaniemi, M. & Brattico, E. (2014). Noise sensitivity modulates the auditory-cortex discrimination of sound feature changes. In INTERNOISE 2014 - 43rd International Congress on Noise Control Engineering: Improving the World Through Noise Control Australian Acoustical Society.

Harrison, P. & Pearce, M. (2018). An energy-based generative sequence model for testing sensory theories of Western harmony. In Proceedings of the 19th International Society for Music Information Retrieval Conference, ISMIR 2018 (pp. 160-167). http://webprojects.eecs.qmul.ac.uk/marcusp/papers/HarrisonPearce2018b.pdf

Harrison, P. & Pearce, M. (2018). Dissociating sensory and cognitive theories of harmony perception through computational modeling. In Proceedings of the 15th International Conference on Music Perception & Cognition http://webprojects.eecs.qmul.ac.uk/marcusp/papers/HarrisonPearce2018a.pdf

Vuust, P. & Kringelbach, M. L. (2017). Music Improvisation: A Challenge for Empirical Research. In R. Ashley & R. Timmers (Eds.), The Routledge Companion to Music Cognition (pp. 265-276). Routledge.

van Hartevelt, T. J., Fernandes, H., Stevner, A., Deco, G. & Kringelbach, M. L. (2017). Neural plasticity in human brain connectivity: the effects of deep brain stimulation. In The Rewiring Brain: A Computational Approach to Structural Plasticity in the Adult Brain (pp. 527-546). elsevier. https://doi.org/10.1016/B978-0-12-803784-3.00025-1

van Hartevelt, T. J. & Kringelbach, M. L. (2015). The Olfactory Cortex. In A. W. Toga (Ed.), Brain Mapping (pp. 347-355). Academic Press. https://doi.org/10.1016/B978-0-12-397025-1.00235-9

Stupacher, J., Hove, M. J. & Vuust, P. (2023). The experience of musical groove: Body movement, pleasure, and social bonding. In Performing Time: Synchrony and Temporal Flow in Music and Dance (pp. 321-328). Oxford University Press.

Stewart, L., Von Kriegstein, K., Bella, S. D., Warren, J. D. & Griffiths, T. D. (2008). Disorders of Musical Cognition. In The Oxford Handbook of Music Psychology Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199298457.013.0017

Stark, E. A., Berridge, K. C. & Kringelbach, M. L. (2023). The neurobiology of liking. In M. Skov & M. Nadal (Eds.), The Routledge International Handbook of Neuroaesthetics (pp. 63-70). Routledge. https://doi.org/10.4324/9781003008675-4

Sedghi, N. A. & Brattico, E. (2019). Musik og evolution. In T. K. Nielsen, C. Andersen, A. R. Kratschmer & M. Clasen (Eds.), Mennesket, kultur, evolution: et biokulturelt perspektiv (pp. 201-214). Aarhus Universitetsforlag.

Rohrmeier, M. & Pearce, M. (2018). Musical syntax I: Theoretical perspectives. In R. Bader (Ed.), Springer Handbooks (pp. 473-486). Springer. https://doi.org/10.1007/978-3-662-55004-5_25

Reybrouck, M., Vuust, P. & Brattico, E. (2018). Music and the plastic brain: How sounds trigger neurogenerative adaptations. In Neuroplasticity - Insights of Neural Reorganization InTechOpen.

Reybrouck, M. & Brattico, E. (2023). Music, mindfulness and meditation: A neuroscientific account. In Arts and Mindfulness Education for Human Flourishing (pp. 69-88). Routledge. https://doi.org/10.4324/9781003158790-7

Pearce, M. & Rohrmeier, M. (2018). Musical syntax II: Empirical perspectives. In R. Bader (Ed.), Springer Handbooks (pp. 487-505). Springer. https://doi.org/10.1007/978-3-662-55004-5_26

Näätänen, R., Brattico, E. & Tervaniemi, M. (2003). Mismatch negativity (MMN): A probe to auditory cognition and perception in basic and clinical research. In A. Zani & A. M. Proverbio (Eds.), The Cognitive Electrophysiology of Mind and Brain (pp. 343-355). Psychology Press.

Morrison, S., Demorest, S. & Pearce, M. (2019). Cultural Distance: A Computational Approach to Exploring Cultural Influences on Music Cognition. In M. Thaut & D. Hodges (Eds.), Oxford Handbook of Music and the Brain Oxford University Press. https://doi.org/10.1093/oxfordhb/9780198804123.013.3

Jespersen, K. V. (2022). A lullaby to the brain: The use of music as a sleep aid. In B. Colombo (Ed.), The Musical Neurons (pp. 53-63). Springer. https://doi.org/10.1007/978-3-031-08132-3

Heggli, O. A., Vuust, P. & Kringelbach, M. L. (2019). Please Please Me! The Pleasure of Music in the Brain. In The Routledge Companion to Music, Mind and Well-being (pp. 205-218). Routledge.

Haumann, N. T. (2015). An Introduction to Cognitive Musicology: Historical-Scientific Presuppositions in the Psychology of Music. In Dansk Musikforskning Online Særnummer, 2015: Musik- og hjerneforskning http://www.danishmusicologyonline.dk/arkiv/arkiv_dmo/dmo_saernummer_2015/dmo_saernummer_2015_musik_hjerneforskning_01.pdf

Fjældstad, A., van Hartevelt, T. J. & Kringelbach, M. L. (2016). Pleasure of Food in the Brain. In B. Piqueras-Fiszman & C. Spence (Eds.), Multisensory Flavor Perception: From Fundamental Neuroscience Through to the Marketplace (pp. 211-234). Woodhead Publishing. https://doi.org/10.1016/B978-0-08-100350-3.00011-0

Fasano, M. C., Brattico, E., Lorenzen, I. S., Gargiulo, A., Kringelbach, M. L., Semeraro, C. & Cassibba, R. (2022). The impact of orchestral playing on children's lives. In T. Chemi, E. Brattico, L. Overby Fjorback & L. Harmat (Eds.), Arts and Mindfulness Education for Human Flourishing (pp. 106-123). Routledge. https://doi.org/10.4324/9781003158790-9

Dahlstrøm, M., Stewart, L. & Shoemark, H. (2020). The Potential of The Human Voice for Early Parent–infant Interactions in at-risk Populations. In R. Heydon, D. Fancourt & A. J. Cohen (Eds.), The Routledge Companion to Interdisciplinary Studies in Singing (Vol. III: Wellbeing, pp. 42-49). Routledge. https://doi.org/10.4324/9781315162546-3

Criscuolo, A. & Brattico, E. (2023). Fundamentals of Electroencephalography and Magnetoencephalography. In Language Electrified: Principles, Methods, and Future Perspectives of Investigation (pp. 163-194). Humana Press. https://doi.org/10.1007/978-1-0716-3263-5_6

Cohen, A. J., Levitin, D. & Alexander Kleber, B. (2020). Brain mechanisms underlying singing. In F. A. Russo, B. Ilari & A. J. Cohen (Eds.), The Routledge Companion to Interdisciplinary Studies in Singing, Volume I: Development (pp. 79-96). Routledge.

Chemi, T., Brattico, E., Fjorback, L. O. & Harmat, L. (2022). Introduction: A gaze into a complex jigsaw. In T. Chemi, E. Brattico, L. O. Fjorback & L. Harmat (Eds.), Arts and Mindfulness Education for Human Flourishing (pp. 1-8). Taylor & Francis. https://doi.org/10.4324/9781003158790-1

Burunat, I. & Brattico, E. (2017). Functional magnetic resonance imaging. In D. Worthington & G. D. Bodie (Eds.), The Sourcebook of Listening Research: Methodology and Measures (pp. 290-298). Wiley.

Brattico, E., Olcese, C. & Tervaniemi, M. (2016). Auditory sensory memory. In S. Koelsch (Ed.), Handbook of Systematic Musicology Springer.

Brattico, E., Olcese, C. & Tervaniemi, M. (2018). Automatic Processing of Musical Sounds in the Human Brain. In Springer Handbooks (pp. 441-452). Springer. https://doi.org/10.1007/978-3-662-55004-5_22

Brattico, E. & Vuust, P. (2017). Brain-to-brain coupling and culture as prerequisites for musical interaction. In M. LeSaffre, M. Leman & P.-J. Maes (Eds.), The Routledge Companion to Embodied Music Interaction (pp. 249-257). Routledge.

Brattico, E. & Tervaniemi, M. (2010). Creativity in musicians: Evidence from cognitive neuroscience. In Studies in Systematic Musicology: Festschrift in Honor of Professor Albrecht Schneider (pp. 233-244). Verlag Peter Lang.

Brattico, E. (2015). From pleasure to liking and back: Bottom-up and top-down neural routes to the aesthetic enjoyment of music. In J. P. Huston, M. Nadal, F. Mora, L. F. Agnati & C. J. Cela-Conde (Eds.), Art, Aesthetics and the Brain (pp. 303-318). Oxford University Press.

Brattico, E. & Tervaniemi, M. (2006). Musical creativity and the human brain. In Musical Creativity: Multidisciplinary Research in Theory and Practice (pp. 289-321). Psychology Press. https://doi.org/10.4324/9780203088111

Brattico, E. & Trusbak Haumann, N. (2020). Musicology. In D. L. Worthington & G. D. Bodie (Eds.), The Handbook of Listening (pp. 199-215). Wiley. https://doi.org/10.1002/9781119554189.ch12

Brattico, E. (2019). The neuroaesthetics of music: A research agenda coming of age. In M. Thaut & D. Hodges (Eds.), The Oxford Handbook of Music and the Brain Oxford University Press. https://doi.org/10.1093/oxfordhb/9780198804123.013.15

Atasoy, S., Vohryzek, J., Deco, G., Carhart-Harris, R. L. & Kringelbach, M. L. (2018). Common neural signatures of psychedelics: Frequency-specific energy changes and repertoire expansion revealed using connectome-harmonic decomposition. In T. Calvey (Ed.), PSYCHEDELIC NEUROSCIENCE (pp. 97-120). Elsevier. https://doi.org/10.1016/bs.pbr.2018.08.009

Abu-Jamous, B., Liu, C., Roberts, D. J., Brattico, E. & Nandi, A. (2017). Data-driven analysis of collections of big datasets by the Bi-CoPaM method yields field-specific novel insights. In Frontiers in Electronic Technologies - Trends and Challenges (pp. 25-53). Springer.

Displaying results 151 to 200 out of 832

Revised 20.09.2024

Hella Kastbjerg