Large-scale citizen science reveals predictors of sensorimotor adaptation

Jonathan S. Tsay (), Hrach Asmerian (), Laura T. Germine, Jeremy Wilmer, Richard B. Ivry and Ken Nakayama
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Jonathan S. Tsay: Carnegie Mellon University
Hrach Asmerian: University of California, Berkeley
Laura T. Germine: Harvard Medical School
Jeremy Wilmer: Wellesley College
Richard B. Ivry: University of California, Berkeley
Ken Nakayama: University of California, Berkeley

Nature Human Behaviour, 2024, vol. 8, issue 3, 510-525

Abstract: Abstract Sensorimotor adaptation is essential for keeping our movements well calibrated in response to changes in the body and environment. For over a century, researchers have studied sensorimotor adaptation in laboratory settings that typically involve small sample sizes. While this approach has proved useful for characterizing different learning processes, laboratory studies are not well suited for exploring the myriad of factors that may modulate human performance. Here, using a citizen science website, we collected over 2,000 sessions of data on a visuomotor rotation task. This unique dataset has allowed us to replicate, reconcile and challenge classic findings in the learning and memory literature, as well as discover unappreciated demographic constraints associated with implicit and explicit processes that support sensorimotor adaptation. More generally, this study exemplifies how a large-scale exploratory approach can complement traditional hypothesis-driven laboratory research in advancing sensorimotor neuroscience.

Date: 2024
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DOI: 10.1038/s41562-023-01798-0

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