F
Floris T. van Vugt
Researcher at Université de Montréal
Publications - 34
Citations - 526
Floris T. van Vugt is an academic researcher from Université de Montréal. The author has contributed to research in topics: Motor learning & Auditory feedback. The author has an hindex of 11, co-authored 28 publications receiving 364 citations. Previous affiliations of Floris T. van Vugt include French Institute of Health and Medical Research & Haskins Laboratories.
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Journal ArticleDOI
Structural neuroplasticity in expert pianists depends on the age of musical training onset
Lucía Vaquero,Karl Hartmann,Pablo Ripollés,Nuria Rojo,Joanna Sierpowska,Clément François,Estela Camara,Floris T. van Vugt,Bahram Mohammadi,Amir Samii,Thomas F. Münte,Antoni Rodríguez-Fornells,Antoni Rodríguez-Fornells,Eckart Altenmüller +13 more
TL;DR: Structural brain differences in expert pianists compared to non-musician controls as well as the effect of the age of onset of music-training are investigated, revealing the link between onset of musical practice, behavioral performance, and putaminal gray matter structure.
Journal ArticleDOI
Risk Perception in a Real-World Situation (COVID-19): How It Changes From 18 to 87 Years Old
Alessia Rosi,Floris T. van Vugt,Floris T. van Vugt,Serena Lecce,Irene Ceccato,Martine Vallarino,Filippo Rapisarda,Tomaso Vecchi,Elena Cavallini +8 more
TL;DR: In this paper, the authors examined age-related differences in risk perception in the early stages of COVID-19 lockdown, analyzing variables that can explain the differences in perception of risk at different ages.
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Tap Arduino: An Arduino microcontroller for low-latency auditory feedback in sensorimotor synchronization experiments.
TL;DR: The setup is validated by having participants tap on a force-sensitive resistor pad connected to the Arduino and on an electronic percussion pad with various levels of force and tempi, and the Arduino outperformed the percussion pad regardless of tapping force.
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Individuality That is Unheard of: Systematic Temporal Deviations in Scale Playing Leave an Inaudible Pianistic Fingerprint
TL;DR: The results indicate that even non-expressive playing of scales reveals consistent, partially effector-unspecific, but inaudible inter-individual differences, and suggest that machine learning studies into individuality in performance will need to take into account unintentional but consistent variability below the perceptual threshold.
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Thresholds of auditory-motor coupling measured with a simple task in musicians and non-musicians: was the sound simultaneous to the key press?
TL;DR: The findings indicate that the brain has a relatively large window of integration within which an action and its resulting effect are judged as simultaneous, and musical expertise may narrow this window down, potentially due to a more refined temporal prediction.