Interferences in the Transformation of Reference Frames during a Posture Imitation Task

We present a biologically-inspired neural model addressing the problem of transformations across frames of reference in a posture imitation task. Our modeling is based on the hypothesis that imitation is mediated by two concurrent transformations selectively sensitive to spatial and anatomical cues. In contrast to classical approaches, we also assume that separate instances of this pair of transformations are responsible for the control of each side of the body. We also devised an experimental paradigm which allowed us to model the interference patterns caused by the interaction between the anatomical on one hand, and the spatial imitative strategy on the other hand. The results from our simulation studies thus provide predictions of real behavioral responses.

Published in:
In Proceeding of the International Conference on Artificial Neural Networks, ICANN 07, Porto, Portugal
Presented at:
Conference on Artificial Neural Networks, ICANN 07, Porto, Portugal, 2007

 Record created 2007-11-06, last modified 2018-03-17

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