What are experts made of? Uncovering expertise in motor sequence learning

Despite over 70 years of motor learning research, the field has yet to fully understand how learning expertise is developed in the brain (Richard, Clegg, & Seger, 2009; Willingham, 1999; Willingham, Wells, Farrell, & Stemwedel, 2000). This project will use MEG to investigate the changes in time-frequency wavelets as a function of expertise (Heideman, van Ede, & Nobre, 2018). The project will use a multimodal approach to combine both neurological signals and behavioural data and use multivariate approaches to differentiate the representation between experts and poorer motor sequence learners (Diedrichsen & Kriegeskorte, 2017). This project seeks to uncover one of the fundamental cognitive mechanisms of motor sequence learning.

1. Diedrichsen, J., & Kriegeskorte, N. (2017). Representational models: A common framework for understanding encoding, pattern-component, and representational-similarity analysis. PLoS Comput Biol, 13(4), e1005508. doi:10.1371/journal.pcbi.1005508
2. Heideman, S. G., van Ede, F., & Nobre, A. C. (2018). Temporal alignment of anticipatory motor cortical beta lateralisation in hidden visual-motor sequences. European Journal of Neuroscience, 48(8), 2684-2695. doi:10.1111/ejn.13700
3. Richard, M. V., Clegg, B. A., & Seger, C. A. (2009). Implicit motor sequence learning is not represented purely in response locations. Q J Exp Psychol (Hove), 62(8), 1516-1522. doi:10.1080/17470210902732130
4. Willingham, D. B. (1999). Implicit motor sequence learning is not purely perceptual. Mem Cognit, 27(3), 561-572.
5. Willingham, D. B., Wells, L. A., Farrell, J. M., & Stemwedel, M. E. (2000).

Project Leaders - Russell Chan, Tommaso Fedele.