Our publications

Cantou, P., Fasano, M. C., Toiviainen, P., Alexander Kleber, B., Burunat, I., Vuust, P. & Brattico, E. (2017). Neural underpinnings of musical tension in preadolescents: a free-listening fMRI study. Poster session presented at The Neurosciences and Music VI - Music, Sound and Health , Boston, Massachusetts, United States.

Cantou, P., Fasano, M. C., Alexander Kleber, B., Vuust, P. & Brattico, E. (2018). Musical tension processing in preadolescents: a free-listening fMRI study. 1.

Capouskova, K., Kringelbach, M. L. & Deco, G. (2022). Modes of cognition: Evidence from metastable brain dynamics. NeuroImage, 260, [119489]. https://doi.org/10.1016/j.neuroimage.2022.119489

Carlson, E., Saarikallio, S., Toiviainen, P., Bogert, B., Kliuchko, M. & Brattico, E. (2015). Maladaptive and adaptive emotion regulation through music: a behavioral and neuroimaging study of males and females. Frontiers in Human Neuroscience, 9, [466]. https://doi.org/10.3389/fnhum.2015.00466

Celma-Miralles, A. & Toro, J. M. (2020). Non-human animals detect the rhythmic structure of a familiar tune. Psychonomic Bulletin and Review, 27(4), 694-699. https://doi.org/10.3758/s13423-020-01739-2

Celma-Miralles, A., Alexander Kleber, B., Toro, J. & Vuust, P. (2020). The subdivision benefit in the brain. Poster session presented at Brain. Cognition. Emotion. Music. Conference, Leeds, United Kingdom.

Celma-Miralles, A., Møller, C., Stupacher, J. & Vuust, P. (2021). Neural entrainment to an ambiguous polyrhythm with distinct metrical contexts (a pilot study). Abstract from Rhythm Production and Perception Workshop 2021, Oslo, Norway. https://www.uio.no/ritmo/english/news-and-events/events/conferences/2021/RPPW/videos/talks/121%20celma-miralles.mp4?vrtx=view-as-webpage

Celma-Miralles, A., Kliuchko, M., Bruzzone, S. E. P., Trusbak Haumann, N., Zachariasson, P., Vuust, P. & Brattico, E. (2022). Mismatch responses to violations of musical features in children compared to adult. In MMN 2022: Mismatch negativity: neural basis and biomarker development (pp. 104-105). [P-14] https://www.c-linkage.co.jp/mmn2022/file/mmn2022_program_abstract.pdf

Chan, R. C. K. & Kringelbach, M. L. (2016). Editorial: At Risk for Neuropsychiatric Disorders: An Affective Neuroscience Approach to Understanding the Spectrum. Frontiers in Behavioral Neuroscience, 10, [165]. https://doi.org/10.3389/fnbeh.2016.00165

Charquero-Ballester, M., Kleim, B., Vidaurre, D., Ruff, C., Stark, E., Tuulari, J. J., McManners, H., Bar-Haim, Y., Bouquillon, L., Moseley, A., Williams, S. C. R., Woolrich, M. W., Kringelbach, M. L. & Ehlers, A. (2022). Effective psychological therapy for PTSD changes the dynamics of specific large-scale brain networks. Human Brain Mapping, 43(10), 3207-3220. https://doi.org/10.1002/hbm.25846

Chemi, T., Brattico, E., Fjorback, L. O. & Harmat, L. (Eds.) (2022). Arts and mindfulness education for human flourishing. Taylor & Francis. Routledge Research in Arts Education https://doi.org/10.4324/9781003158790

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. Routledge Research in Arts Education https://doi.org/10.4324/9781003158790-1

Chemi, T., Brattico, E., Fjorback, L. O. & Harmat, L. (2022). Conclusion: A beam of light to conclude with. In T. Chemi, E. Brattico, L. O. Fjorback & L. Harma (Eds.), Arts and Mindfulness Education for Human Flourishing (pp. 285-287). Taylor & Francis. Routledge Research in Arts Education https://doi.org/10.4324/9781003158790-21

Chen, J. L., Kumar, S., Williamson, V. J., Scholz, J., Griffiths, T. D. & Stewart, L. (2015). Detection of the arcuate fasciculus in congenital amusia depends on the tractography algorithm. Frontiers in Psychology, 6, 9. https://doi.org/10.3389/fpsyg.2015.00009

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

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

Clemente, A., Pearce, M. T., Skov, M. & Nadal, M. (2021). Evaluative judgment across domains: Liking balance, contour, symmetry and complexity in melodies and visual designs. Brain and Cognition, 151, [105729]. https://doi.org/10.1016/j.bandc.2021.105729

Coelho, A., Fernandes, H. M., Magalhães, R., Moreira, P. S., Marques, P., Soares, J. M., Amorim, L., Portugal-Nunes, C., Castanho, T., Santos, N. C. & Sousa, N. (2021). Signatures of white-matter microstructure degradation during aging and its association with cognitive status. Scientific Reports, 11(1), [4517]. https://doi.org/10.1038/s41598-021-83983-7

Coelho, A., Fernandes, H. M., Magalhães, R., Moreira, P. S., Marques, P., Soares, J. M., Amorim, L., Portugal-Nunes, C., Castanho, T., Santos, N. C. & Sousa, N. (2021). Reorganization of brain structural networks in aging: A longitudinal study. Journal of Neuroscience Research, 99(5), 1354-1376. https://doi.org/10.1002/jnr.24795

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

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.

Cong, F., Puolivali, T., Alluri, V., Sipola, T., Burunat, I., Toiviainen, P., Nandi, A. K., Brattico, E. & Ristaniemi, T. (2014). Key issues in decomposing fMRI during naturalistic and continuous music experience with independent component analysis. Journal of Neuroscience Methods, 223, 74-84. https://doi.org/10.1016/j.jneumeth.2013.11.025

Corcoran, C., Stupacher, J. & Vuust, P. (2022). Swinging the Score? Swing Phrasing Cannot Be Communicated via Explicit Notation Instructions Alone. Music Perception, 39(4), 386-400. https://doi.org/10.1525/MP.2022.39.4.386

Costa, M. & Bonetti, L. (2016). Geometrical factors in the perception of sacredness. Perception, 1240.

Costa, M., Bonetti, L., Belelli, M., Lantieri, C., Vignali, V. & Simone, A. (2016). Reflective tape applied to bicycle frame and conspicuity enhancement at night. Human Factors, 485.

Costa, M. & Bonetti, L. (2017). Linear perspective and framing in the vista paradox. Perception, 46(11), 1245-1268.

Costa, M. & Bonetti, L. (2018). Geometrical distortions in large-scale cognitive geographical maps. Journal of Environmental Psychology, 55, 53-69. https://doi.org/10.1016/j.jenvp.2017.12.004

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

Costa, M., Bonetti, L., VIgnali, V., Bichicchi, A., Lantieri, C. & Simone, A. (2019). Driver's visual attention to different categories of roadside advertising signs. Applied Ergonomics, 78, 127-136. https://doi.org/10.1016/j.apergo.2019.03.001

Criscuolo, A., Bonetti, L., Sarkamo, T., Kliuchko, M. & Brattico, E. (2019). On the Association Between Musical Training, Intelligence and Executive Functions in Adulthood. Frontiers in Psychology, 10, [1704]. https://doi.org/10.3389/fpsyg.2019.01704

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

Crisp, R. & Kringelbach, M. (2018). Higher and Lower Pleasures Revisited: Evidence from Neuroscience. Neuroethics, 11(2), 211-215. https://doi.org/10.1007/s12152-017-9339-2

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

Daffertshofer, A., Ton, R., Pietras, B., Kringelbach, M. L. & Deco, G. (2018). Scale-freeness or partial synchronization in neural mass phase oscillator networks: Pick one of two? NeuroImage, 180, 428-441. https://doi.org/10.1016/j.neuroimage.2018.03.070

Daffertshofer, A., Ton, R., Kringelbach, M. L., Woolrich, M. & Deco, G. (2018). Distinct criticality of phase and amplitude dynamics in the resting brain. NeuroImage, 180, 442-447. https://doi.org/10.1016/j.neuroimage.2018.03.002

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

Danielsen, A., Waadeland, C. H., Sundt, H. G. & Witek, M. A. G. (2015). Effects of instructed timing and tempo on snare drum sound in drum kit performance. Acoustical Society of America. Journal, 138(4), 2301-2316. https://doi.org/10.1121/1.4930950

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

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

Deco, G., Tononi, G., Boly, M. & Kringelbach, M. L. (2015). Rethinking segregation and integration: contributions of whole-brain modelling. Nature Reviews. Neuroscience, 16(7), 430-9. https://doi.org/10.1038/nrn3963

Deco, G. & Kringelbach, M. L. (2016). Metastability and Coherence: Extending the Communication through Coherence Hypothesis Using A Whole-Brain Computational Perspective. Trends in Neurosciences, 39(3), 125-35. https://doi.org/10.1016/j.tins.2016.01.001

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

Deco, G., Cabral, J., Woolrich, M. W., Stevner, A. B. A., van Hartevelt, T. J. & Kringelbach, M. L. (2017). Single or multiple frequency generators in on-going brain activity: A mechanistic whole-brain model of empirical MEG data. NeuroImage, (152), 538-550. https://doi.org/10.1016/j.neuroimage.2017.03.023

Deco, G. & Kringelbach, M. L. (2017). Hierarchy of Information Processing in the Brain: A Novel 'Intrinsic Ignition' Framework. Neuron, 94(5), 961-968. https://doi.org/10.1016/j.neuron.2017.03.028

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

Deco, G., Tagliazucchi, E., Laufs, H., Sanjuán, A. & Kringelbach, M. L. (2017). Novel Intrinsic Ignition Method Measuring Local-Global Integration Characterizes Wakefulness and Deep Sleep. eNeuro , 4(5). https://doi.org/10.1523/ENEURO.0106-17.2017

Deco, G., Cabral, J., Saenger, V. M., Boly, M., Tagliazucchi, E., Laufs, H., Van Someren, E., Jobst, B., Stevner, A. & Kringelbach, M. L. (2018). Perturbation of whole-brain dynamics in silico reveals mechanistic differences between brain states. NeuroImage, 169, 46-56. https://doi.org/10.1016/j.neuroimage.2017.12.009

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

Deco, G., Cruzat, J. & Kringelbach, M. L. (2019). Brain songs framework used for discovering the relevant timescale of the human brain. Nature Communications, 10, [583]. https://doi.org/10.1038/s41467-018-08186-7

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 of the United States of America, 116(36), 18088-18097. https://doi.org/10.1073/pnas.1905534116

Displaying results 101 to 150 out of 652

Revised 26.03.2021

Hella Kastbjerg