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Updated: Dec 29, 2025

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation
Published on: March 1, 2017
Decoding identity from motion: how motor similarities colour our perception of self and others
Alexandre Coste1, Benoît G Bardy2, Stefan Janaqi2
1EuroMov Digital Health in Motion, Univ. Montpellier, IMT Mines Alès, Montpellier, France. alexandre.coste1@umontpellier.fr.
Abstract:
For more than 4 decades, it has been shown that humans are particularly sensitive to biological motion and extract socially relevant information from it such as gender, intentions, emotions or a person's identity. A growing number of findings, however, indicate that identity perception is not always highly accurate, especially due to large inter-individual differences and a fuzzy self-recognition advantage compared to the recognition of others. Here, we investigated the self-other identification performance and sought to relate this performance to the metric properties of perceptual/physical representations of individual motor signatures. We show that identity perception ability varies substantially across individuals and is associated to the perceptual/physical motor similarities between self and other stimuli. Specifically, we found that the perceptual representations of postural signatures are veridical in the sense that closely reflects the physical postural trajectories and those similarities between people' actions elicit numerous misattributions. While, on average, people can well recognize their self-generated actions, they more frequently attribute to themselves the actions of those acting in a similar way. These findings are consistent with the common coding theory and support that perception and action are tightly linked and may modulate each other by virtue of similarity.
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