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Large-scale web-based approach reveals predictors of successful motor learning

Nature Human Behaviour volume 8, pages 420–421 (2024)Cite this article

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Leveraging over 2,000 data sessions from a citizen science website, this large-scale exploratory research study revealed demographic (age, sex and daily computer usage) and task features (task enjoyment and baseline movement times) that predicted the extent of successful sensorimotor adaptation in participants’ reaching movements after a visuomotor perturbation.

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Fig. 1: Assessment of sensorimotor adaptation using a web-based reaching task.

References

  1. Tsay, J. S., Kim, H., Haith, A. M. & Ivry, R. B. Understanding implicit sensorimotor adaptation as a process of proprioceptive re-alignment. eLife 11, e76639 (2022). This paper is a thorough theoretical review that focuses on implicit motor learning.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Tsay, J. S. et al. Strategic processes in sensorimotor learning: reasoning, refinement, and retrieval. Preprint at PsyArXiv, https://doi.org/10.31234/osf.io/x4652 (2023). This preprint is a thorough theoretical review that focuses on explicit motor learning.

  3. Kim, H. E., Avraham, G. & Ivry, R. B. The psychology of reaching: action selection, movement implementation, and sensorimotor learning. Annu. Rev. Psychol. 7, 61–95 (2020). This paper provides a comprehensive review of the field of motor learning.

    Google Scholar 

  4. Krakauer, J., Hadjiosif, A. M., Xu, J., Wong, A. L. & Haith, A. M. Motor learning. Compr. Physiol. 9, 613–663 (2019). This paper offers another comprehensive review of motor learning.

    Article  PubMed  Google Scholar 

  5. Tsay, J. S., Lee, A., Ivry, R. B. & Avraham, G. Moving outside the lab: the viability of conducting sensorimotor learning studies online. Neurons Behav. Data Anal. Theory. 5, 1–22 (2021). This paper validates the effectiveness of conducting web-based motor adaptation studies.

    Google Scholar 

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This is a summary of: Tsay, J. S. et al. Large-scale citizen science reveals predictors of sensorimotor adaptation. Nat. Hum. Behav. https://doi.org/10.1038/s41562-023-01798-0 (2024).

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Large-scale web-based approach reveals predictors of successful motor learning. Nat Hum Behav 8, 420–421 (2024). https://doi.org/10.1038/s41562-023-01809-0

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