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. 2021 Oct 13;11:20377. doi: 10.1038/s41598-021-99864-y

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© The Author(s) 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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The Virtual Racquetball task. An illustration of the experimental set-up (a), example gameplay footage (b), and a side-view of ball trajectory distributions (c). Note: for all trials, virtual balls stayed fixed on the midline of the room and followed the same pre-bounce speed and trajectory. Differences between expected and unexpected trials were therefore consigned to ball elasticity (i.e., ‘bounciness’) manipulations only. See Supplementary Videos of the protocol at https://osf.io/ewnh9/.