The DOI matches its Crossref record; 64 of the 64 references it cites were found in a registry or an index.
Causal reasoning with forces
Open accessAbstract
Causal composition allows people to generate new causal relations by combining existing causal knowledge. We introduce a new computational model of such reasoning, the force theory, which holds that people compose causal relations by simulating the processes that join forces in the world, and compare this theory with the mental model theory (Khemlani et al., 2014) and the causal model theory (Sloman et al., 2009), which explain causal composition on the basis of mental models and structural equations, respectively. In one experiment, the force theory was uniquely able to account for people's ability to compose causal relationships from complex animations of real-world events. In three additional experiments, the force theory did as well as or better than the other two theories in explaining the causal compositions people generated from linguistically presented causal relations. Implications for causal learning and the hierarchical structure of causal knowledge are discussed.
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Cited by
Begemann, M. J., Brand, B. A., Ćurčić-Blake, B., Aleman, A., & Sommer, I. E. (2020) · Psychological Medicine · doi:10.1017/s0033291720003670 · Cited by 368
Neurofeedback with fMRI: A critical systematic review
Thibault, R. T., MacPherson, A., Lifshitz, M., Roth, R. R., & Raz, A. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2017.12.071 · Cited by 312
The self-regulating brain and neurofeedback: experimental science and clinical promise
Thibault, R. T., Lifshitz, M., & Raz, A. (2016) · Cortex · doi:10.1016/j.cortex.2015.10.024 · Cited by 272
Behavioural clusters and predictors of performance during recovery from stroke
Ramsey, L. E., Siegel, J. S., Lang, C. E., Strube, M., Shulman, G. L., & Corbetta, M. (2017) · Nature Human Behaviour · doi:10.1038/s41562-016-0038 · Cited by 219
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Metadata
- Authors
- Wolff, P., & Barbey, A. K.
- Venue
- Frontiers in Human Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2015-01-21
- Volume
- 9
- Pages
- 1-1
- ISSN
- 1662-5161 (ISSN-L)
- OpenAlex
- W1998709220
- Cited by
- 788
- References
- 64
- FWCI
- 114.18
- Type
- journal article
- Language
- en
- Open access
- gold
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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.