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Cited by 254

The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.

Specificity of regions processing biological motion

Peuskens, H., Vanrie, J., Verfaillie, K., Orban, G. A.·2005·European Journal of Neuroscience

Abstract

Using functional magnetic resonance imaging and point light displays portraying six different human actions, we were able to show that several visual cortical regions, including human MT/V5 complex, posterior inferior temporal gyrus and superior temporal sulcus, are differentially active in the subtraction comparing biological motion to scrambled motion. Comparison of biological motion to three‐dimensional rotation (of a human figure), articulated motion and translation suggests that human superior temporal sulcus activity reflects the action portrayed in the biological motion stimuli, whereas posterior inferior temporal gyrus responds to the figure and hMT/V5+ to the complex motion pattern present in biological motion stimuli. These results were confirmed with implied action stimuli.

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Crossref · 10.1111/j.1460-9568.2005.04106.x

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Metadata

Authors
Peuskens, H., Vanrie, J., Verfaillie, K., & Orban, G. A.
Venue
European Journal of Neuroscience
Publisher
Wiley
Published
2005-05
Volume
21
Issue
10
Pages
2864-2875
ISSN
  • 0953-816X (ISSN-L)
  • 1460-9568
OpenAlex
W2011553630
Cited by
254
References
55
FWCI
21.51
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Specificity of regions processing biological motion. https://app.cochat.ai/papers/10.1111/j.1460-9568.2005.04106.x
The paper
Peuskens, H., Vanrie, J., Verfaillie, K., & Orban, G. A. (2005). Specificity of regions processing biological motion. European Journal of Neuroscience. https://doi.org/10.1111/j.1460-9568.2005.04106.x

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.