August 2010
Volume 10, Issue 7
Free
Vision Sciences Society Annual Meeting Abstract  |   August 2010
Mapping Shape to Visuomotor Mapping: Generalization to Novel Shapes
Author Affiliations
  • Marc Ernst
    Max Planck Institute for Biological Cybernetics, Tübingen, Germany
  • Loes van Dam
    Max Planck Institute for Biological Cybernetics, Tübingen, Germany
Journal of Vision August 2010, Vol.10, 1077. doi:10.1167/10.7.1077
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      Marc Ernst, Loes van Dam; Mapping Shape to Visuomotor Mapping: Generalization to Novel Shapes. Journal of Vision 2010;10(7):1077. doi: 10.1167/10.7.1077.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

The accuracy of visually guided motor movements largely depends on the stability of the sensory environment that defines the required response mapping. Thus, as the environment keeps changing we constantly have to adapt our motor responses to stay accurate. The more sensory information we receive about the current state of the environment the more accurate we may be. Recruitment of additional cues that correlate with the environment can therefore aid in this adaptation process. It has previously been shown that subjects recruit previously irrelevant cues to help them switch between 2 specific visuomotor mappings (e.g. Martin et al., 1996; van Dam et al., 2008). However, in rapidly changing environments additional cues will only be of real benefit if it is possible to learn a more continuous correlation between the cue and required visuomotor response. Here we investigate transfer of explicitly trained cue-element/response-mapping combinations to other cue elements from the same continuous scale (a shape morph). In our experiment subjects performed a rapid pointing task to targets for which we manipulated the visuomotor mapping. During training subject simultaneously learned two mappings to two different target shapes. The target shapes were taken from a set of shape morphs (we morphed between spiky and circular shapes). After five sessions of 180 training trials, using catch trials, we tested subjects' performance on different target shape morphs that could either come from an interpolation or an extrapolation along the shape morph axis. Results show that for 7 out of the 12 subjects learning is not restricted to the trained shapes but interpolates and partially also extrapolates to other shapes along the morph axis. We conclude that participants learned implicitly the newly defined shape axis when trained with two distinct visuomotor mappings and they generalize their visuomotor mappings to this new dimension.

Ernst, M. van Dam, L. (2010). Mapping Shape to Visuomotor Mapping: Generalization to Novel Shapes [Abstract]. Journal of Vision, 10(7):1077, 1077a, http://www.journalofvision.org/content/10/7/1077, doi:10.1167/10.7.1077. [CrossRef]
Footnotes
 HFSP Grant on Mechanisms of Associative Learning in Human Perception.
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