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Authorship effects in the prediction of handwriting strokes: Evidence for action simulation during action perception
Abstract
Does the action system contribute to action perception? Recent evidence suggests that actions are simulated while being observed. Given that the planning and simulating system are the same only when one observes one's own actions, it might be easier to predict the future outcomes of actions when one has carried them out oneself earlier on. In order to test this hypothesis, three experiments were conducted in which participants observed parts of earlier self- and other-produced trajectories and judged whether another stroke would follow or not. When the trajectories were produced without constraints, participants accomplished this task only for self-produced trajectories. When the trajectories were produced under narrow constraints, the predictions were equally accurate for self- and for other-generated trajectories. These results support the action simulation assumption. The more the actions that one observes resemble the way one would carry them out oneself, the more accurate the simulation.
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Metadata
- Authors
- Knoblich, G., Seigerschmidt, E., Flach, R., & Prinz, W.
- Venue
- The Quarterly Journal of Experimental Psychology Section A
- Publisher
- SAGE Publications
- Published
- 2002-08
- Volume
- 55
- Issue
- 3
- Pages
- 1027-1046
- ISSN
- 0272-4987 (ISSN-L)
- 1464-0740
- OpenAlex
- W1999851851
- Cited by
- 163
- References
- 9
- FWCI
- 16.22
- Type
- journal article
- Language
- en
- Open access
- closed
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- Knoblich, G., Seigerschmidt, E., Flach, R., & Prinz, W. (2002). Authorship effects in the prediction of handwriting strokes: Evidence for action simulation during action perception. The Quarterly Journal of Experimental Psychology Section A. https://doi.org/10.1080/02724980143000631
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.