Nina van Mastrigt, Ph.D.
 |
Research Associate Room: 344, Building F1 Consultation: by appointment |
I am a human movement scientist interested in perception, motor control and learning. During my PhD, I studied reward-based motor learning in target-directed reaching tasks without visual feedback of the moving limb, with only binary success and failure feedback to learn from. Whereas this reward feedback is easy to manipulate, proprioceptive feedback of the moving limb is not. Where people feel their moving limb may thus influence learning, but currently, most paradigms haven’t manipulated this proprioceptive feedback. At present, I am manipulating proprioceptive feedback of a moving limb with muscle tendon vibration to study the role of proprioception in motor control and learning.
Scientific Training & Education
|
04/2024 - Present |
Postdoctoral Researcher, Justus-Liebig-Universität Gießen NWO Rubicon grant “Somatosensation: an overlooked sense in motor learning” Advisor: Prof. Dr. Katja Fiehler |
|
06/2023 - 12/2023 |
Postdoctoral Researcher, Vrije Universiteit Amsterdam Reward-based motor learning in children Advisors: Dr. Katinka van der Kooij, Prof. Dr. J.B.J. Smeets |
|
2023 |
University teaching qualification (BKO), Vrije Universiteit Amsterdam |
|
01/2022 – 04/2022 |
PhD Human Movement Science, Vrije Universiteit Amsterdam Doctoral Research Visit Project at Cognition & Action Lab, UC Berkeley: Implicit reward-based motor learning Advisor (US): Prof. Dr. R. Ivry Advisors: Dr. Katinka van der Kooij, Prof. Dr. J.B.J. Smeets |
|
2018 - 2023 |
PhD Human Movement Science, Vrije Universiteit Amsterdam Thesis: Exploration in reward-based motor learning (10.5463/thesis.443) Advisors: Dr. Katinka van der Kooij, Prof. Dr. J.B.J. Smeets |
|
2017 / 2018 |
Research project member “Gait recognition in forensics”, Dutch Forensic Institute (Den Haag) Advisor: Prof. dr. ing. Z.M.J.H. Geradts |
|
2013 - 2016 |
MSc Research Master Human Movement Sciences: Sport, Exercise & Health (cum laude), Vrije Universiteit Amsterdam Thesis: Classifying physical function in knee osteoarthritis patients using kinematics of gait and single-limb mini squat Advisors: Prof. dr. J. Harlaar, Prof. dr. A. Daffertshofer |
|
2013 / 2014 |
Higher education (HBO) teaching qualification, Vrije Universiteit Amsterdam |
|
09 / 2010 – 08 / 2013 |
BSc Human Movement Sciences, Vrije Universiteit Amsterdam |
Publications
- van Mastrigt, N.M., Smeets, J.B.J., van Leeuwen, A.M., van Wijk, B.C.M., van der Kooij, K. A Circle-Drawing Task for Studying Reward-Based Motor Learning in Children and Adults. Behav. Sci. (2024), 14, 1055. https://doi.org/10.3390/bs14111055
- van Mastrigt, N.M., van der Kooij, K. & Smeets, J.B.J. The influence of movement speed on reward-based motor learning. BioRXiv. https://doi.org/10.1101/2023.06.28.546754
- van Mastrigt, N.M., Tsay, J.S., Wang, T., Avraham, G., Abram, S.J., van der Kooij, K., Smeets, J.B.J. & Ivry R.B (2023). Experimental Brain Research 241 (9) 2287-2298. Implicit reward-based motor learning. https://doi.org/10.1007/s00221-023-06683-w
- van der Kooij, K., van Mastrigt, N.M., & Cashaback, J.G.A. (2023). Failure induces task-irrelevant exploration during a stencil task. Experimental Brain Research, 241(2), 677–686. https://doi.org/10.1007/s00221-023-06548-2
- van der Kooij, K., van Mastrigt, N.M., Crowe, E.M. & Smeets, J.B.J. Learning a reach trajectory based on binary reward feedback. Sci Rep 11, 2667 (2021). https://doi.org/10.1038/s41598-020-80155-x
- van Mastrigt, N.M., van der Kooij, K. & Smeets, J.B.J. Pitfalls in quantifying exploration in reward-based motor learning and how to avoid them. Biol Cybern 115, 365–382 (2021). https://doi.org/10.1007/s00422-021-00884-8
- van Mastrigt N.M., Smeets J.B.J., van der Kooij K. (2020) Quantifying exploration in reward- based motor learning. PLoS ONE 15(4): e0226789. https://doi.org/10.1371/journal.pone.0226789
- van Mastrigt N.M., Celie K., Mieremet A.L., Ruifrok A.C.C. & Geradts Z. (2018) Critical review of the use and scientific basis of forensic gait analysis, Forensic Sciences Research, 3:3, 183-193, https://doi.org/10.1080/20961790.2018.1503579