Agres, K. R., Schaefer, R. S., Volk, A., van Hooren, S., Holzapfel, A., Dalla Bella, S., Müller, M., de Witte, M., Herremans, D., Ramirez Melendez, R., Neerincx, M., Ruiz, S., Meredith, D., Dimitriadis, T., & Magee, W. L. (2021). Music, computing, and health: A roadmap for the current and future roles of music technology for health care and well-being. Music & Science, 4, 2059204321997709. https://doi.org/10.1177/2059204321997709

Article  Google Scholar 

Allman, M. J., & Meck, W. H. (2012). Pathophysiological distortions in time perception and timed performance. Brain, 135(3), 656–677. https://doi.org/10.1093/brain/awr210

Article  PubMed  Google Scholar 

Allman, M. J., Pelphrey, K. A., & Meck, W. H. (2011). Developmental neuroscience of time and number: Implications for autism and other neurodevelopmental disabilities. Frontiers in Integrative Neuroscience, 6, 7. https://doi.org/10.3389/fnint.2012.00007

Article  PubMed  Google Scholar 

Anglada-Tort, M., Harrison, P. M. C., & Jacoby, N. (2022). REPP: A robust cross-platform solution for online sensorimotor synchronization experiments. Behavior Research Methods, 54(5), 2271–2285. https://doi.org/10.3758/s13428-021-01722-2

Article  PubMed  PubMed Central  Google Scholar 

Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67, 1–48. https://doi.org/10.18637/jss.v067.i01

Article  Google Scholar 

Bégel, V., Benoit, C.-E., Correa, A., Cutanda, D., Kotz, S. A., & Dalla Bella, S. (2017). “Lost in time” but still moving to the beat. Neuropsychologia, 94, 129–138. https://doi.org/10.1016/j.neuropsychologia.2016.11.022

Article  PubMed  Google Scholar 

Bégel, V., Verga, L., Benoit, C.-E., Kotz, S. A., & Dalla Bella, S. (2018). Test–retest reliability of the Battery for the Assessment of Auditory Sensorimotor and Timing Abilities (BAASTA). Annals of Physical and Rehabilitation Medicine, 61(6), 395–400. https://doi.org/10.1016/j.rehab.2018.04.001

Article  PubMed  Google Scholar 

Bégel, V., Dalla Bella, S., Devignes, Q., Vandenbergue, M., Lemaître, M.-P., & Dellacherie, D. (2022). Rhythm as an independent determinant of developmental dyslexia. Developmental Psychology, 58(2), 339–358. https://doi.org/10.1037/dev0001293

Article  PubMed  Google Scholar 

Benoit, C.-E., Dalla Bella, S., Farrugia, N., Obrig, H., Mainka, S., & Kotz, S. A. (2014). Musically cued gait-training improves both perceptual and motor timing in Parkinson’s disease. Frontiers in Human Neuroscience, 8, 494. https://doi.org/10.3389/fnhum.2014.00494

Article  PubMed  PubMed Central  Google Scholar 

Ben-Shachar, M. S., Lüdecke, D., & Makowski, D. (2020). effectsize: Estimation of effect size indices and standardized parameters. Journal of Open Source Software, 5(56), 2815. https://doi.org/10.21105/joss.02815

Article  ADS  Google Scholar 

Berens, P. (2009). CircStat: A MATLAB toolbox for circular statistics. Journal of Statistical Software, 31, 1–21. https://doi.org/10.18637/jss.v031.i10

Article  Google Scholar 

Bonacina, S., Krizman, J., White-Schwoch, T., Nicol, T., & Kraus, N. (2019). How rhythmic skills relate and develop in school-age children. Global Pediatric Health, 6, 2333794X19852045. https://doi.org/10.1177/2333794X19852045

Article  PubMed  PubMed Central  Google Scholar 

Bouwer, F. L., Honing, H., & Slagter, H. A. (2020). Beat-based and memory-based temporal expectations in rhythm: Similar perceptual effects, different underlying mechanisms. Journal of Cognitive Neuroscience, 32(7), 1221–1241. https://doi.org/10.1162/jocn_a_01529

Article  PubMed  Google Scholar 

Brozek, J., & Alexander, H. (1947). Components of variation and the consistency of repeated measurements. Research Quarterly, 18(2), 152–166.

CAS  PubMed  Google Scholar 

Cannon, J. J., & Patel, A. D. (2021). How beat perception co-opts motor neurophysiology. Trends in Cognitive Sciences, 25(2), 137–150. https://doi.org/10.1016/j.tics.2020.11.002

Article  PubMed  Google Scholar 

Cerrato, P., & Halamka, J. (2019). The Transformative Power of Mobile Medicine: Leveraging Innovation. Elsevier Science.

Google Scholar 

Chen, J. L., Penhune, V. B., & Zatorre, R. J. (2008). Listening to musical rhythms recruits motor regions of the brain. Cerebral Cortex, 18(12), 2844–2854. https://doi.org/10.1093/cercor/bhn042

Article  PubMed  Google Scholar 

Corriveau, K. H., & Goswami, U. (2009). Rhythmic motor entrainment in children with speech and language impairments: Tapping to the beat. Cortex, 45(1), 119–130. https://doi.org/10.1016/j.cortex.2007.09.008

Article  PubMed  Google Scholar 

Dalla Bella, S. (2020). The use of rhythm in rehabilitation for patients with movement disorders. In L. L. Cuddy, S. Belleville, & A. Moussard (Eds.), Music and the Aging Brain (pp. 383–406). UK: Academic Press. https://doi.org/10.1016/B978-0-12-817422-7.00015-8

Chapter  Google Scholar 

Dalla Bella, S. (2022). Rhythmic serious games as an inclusive tool for music-based interventions. Annals of the New York Academy of Sciences, 1517(1), 15–24. https://doi.org/10.1111/nyas.14878

Article  ADS  PubMed  Google Scholar 

Dalla Bella, S., Benoit, C.-E., Farrugia, N., Keller, P. E., Obrig, H., Mainka, S., & Kotz, S. A. (2017). Gait improvement via rhythmic stimulation in Parkinson’s disease is linked to rhythmic skills. Scientific Reports, 7, 42005. https://doi.org/10.1038/srep42005

Article  ADS  CAS  Google Scholar 

Dalla Bella, S., Farrugia, N., Benoit, C.-E., Begel, V., Verga, L., Harding, E., & Kotz, S. A. (2017). BAASTA: Battery for the Assessment of Auditory Sensorimotor and Timing Abilities. Behavior Research Methods, 49(3), 1128–1145. https://doi.org/10.3758/s13428-016-0773-6

Article  PubMed  Google Scholar 

Dalla Bella, S., Dotov, D., Bardy, B., & Cochen de Cock, V. (2018). Individualization of music-based rhythmic auditory cueing in Parkinson’s disease. Annals of the New York Academy of Sciences, 1423, 308–317. https://doi.org/10.1111/nyas.13859

Article  ADS  Google Scholar 

Dalla Bella, S., Janaqi, S., Benoit, C.-E., Farrugia, N., Bégel, V., Verga, L., Harding, E. E., & Kotz, S. A. (2024). Unravelling individual rhythmic abilities using machine learning. Scientific Reports, 14, 1135. https://doi.org/10.1038/s41598-024-51257-7

Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

Dalla Bella, S., & Andary, S. (2020). High-precision temporal measurement of vibro-acoustic events in synchronisation with a sound signal on a touch-screen device. (World Intellectual Property Organization (WIPO), No WO 2020/128088 A1).

Damm, L., Varoqui, D., De Cock, V. C., Dalla Bella, S., & Bardy, B. (2020). Why do we move to the beat? A multi-scale approach, from physical principles to brain dynamics. Neuroscience and Biobehavioral Reviews, 112, 553–584. https://doi.org/10.1016/j.neubiorev.2019.12.024

Article  PubMed  Google Scholar 

Dauvergne, C., Bégel, V., Gény, C., Puyjarinet, F., Laffont, I., & Dalla Bella, S. (2018). Home-based training of rhythmic skills with a serious game in Parkinson’s disease: Usability and acceptability. Annals of Physical and Rehabilitation Medicine, 61(6), 380–385. https://doi.org/10.1016/j.rehab.2018.08.002

Article  PubMed  Google Scholar 

Dotov, D. G., Cochen de Cock, V., Geny, C., Ihalainen, P., Moens, B., Leman, M., Bardy, B., & Dalla Bella, S. (2019). The role of interaction and predictability in the spontaneous entrainment of movement. Journal of Experimental Psychology: General, 148(6), 1041–1057. https://doi.org/10.1037/xge0000609

Article  PubMed  Google Scholar 

Falk, S., Müller, T., & Dalla Bella, S. (2015). Non-verbal sensorimotor timing deficits in children and adolescents who stutter. Frontiers in Psychology, 6, 847. https://doi.org/10.3389/fpsyg.2015.00847

Article  PubMed  PubMed Central  Google Scholar 

Fisher, N. I. (1993). Statistical analysis of circular data. Cambridge University Press. https://doi.org/10.1017/CBO9780511564345

Book  Google Scholar 

Fiveash, A., Dalla Bella, S., Bigand, E., Gordon, R. L., & Tillmann, B. (2022). You got rhythm, or more: The multidimensionality of rhythmic abilities. Attention, Perception & Psychophysics, 84(4), 1370–1392. https://doi.org/10.3758/s13414-022-02487-2

Article  Google Scholar 

Fleiss, J. L. (1986). The Design and Analysis of Clinical Experiments. Wiley.

Google Scholar 

Fujii, S., & Schlaug, G. (2013). The Harvard Beat Assessment Test (H-BAT): A battery for assessing beat perception and production and their dissociation. Frontiers in Human Neuroscience, 7, 771. https://doi.org/10.3389/fnhum.2013.00771

Article  PubMed  PubMed Central  Google Scholar 

Gamer, M., Lemon, J., & Singh, I. F. P. (2019). irr: Various coefficients of interrater reliability and agreement (0.84.1) [Computer software]. Available from https://cran.r-project.org/web/packages/irr/index.html. Accessed 15 Feb 2024

Grahn, J. A., & Brett, M. (2007). Rhythm and beat perception in motor areas of the brain. Journal of Cognitive Neuroscience, 19(5), 893–906. https://doi.org/10.1162/jocn.2007.19.5.893

Article  PubMed  Google Scholar 

Grahn, J. A., & Brett, M. (2009). Impairment of beat-based rhythm discrimination in Parkinson’s disease. Cortex, 45(1), 54–61. https://doi.org/10.1016/j.cortex.2008.01.005

Article  PubMed  Google Scholar 

Grondin, S. (2010). Timing and time perception: A review of recent behavioral and neuroscience findings and theoretical directions. Attention, Perception, and Psychophysics, 72(3), 561–582. https://doi.org/10.3758/APP.72.3.561

Article  Google Scholar 

Halekoh, U., & Højsgaard, S. (2014). A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models – The R Package pbkrtest. Journal of Statistical Software, 59, 1–32. https://doi.org/10.18637/jss.v059.i09

Article  Google Scholar 

Hidalgo, C., Zécri, A., Pesnot-Lerousseau, J., Truy, E., Roman, S., Falk, S., Dalla Bella, S., & Schön, D. (2021). Rhythmic abilities of children with hearing loss. Ear and Hearing, 42(2), 364–372. https://doi.org/10.1097/AUD.0000000000000926

Article  PubMed  Google Scholar 

Iversen, J., & Patel, A. D. (2008). The Beat Alignment Test (BAT): Surveying beat processing abilities in the general population. 10th International Conference on Music Perception and Cognition (ICMPC10), Sapporo, Japan. Available from