Points and Stripes: A Novel Technique for Masking Biological Motion Point-Light Stimuli
Author(s) -
Georg Layher,
Heiko Neumann
Publication year - 2018
Publication title -
frontiers in psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.947
H-Index - 110
ISSN - 1664-1078
DOI - 10.3389/fpsyg.2018.01455
Subject(s) - biological motion , artificial intelligence , motion perception , computer vision , motion (physics) , computer science , perception , stimulus (psychology) , masking (illustration) , maxima and minima , communication , neuroscience , psychology , mathematics , cognitive psychology , art , mathematical analysis , visual arts
Human articulated motion can be readily recognized robustly even from impoverished so-called point-light displays. Such sequence information is processed by separate visual processing channels recruiting different stages at low and intermediate levels of the cortical visual processing hierarchy. The different contributions that motion and form information make to form articulated, or biological, motion perception are still under investigation. Here we investigate experimentally whether and how specific spatio-temporal features, such as extrema in the motion energy or maximum limb expansion, indicated by the lateral and longitudinal extension, constrain the formation of the representations of articulated body motion. In order to isolate the relevant stimulus properties we suggest a novel masking technique, which allows to selectively impair the ankle information of the body configuration while keeping the motion of the point-light locations intact. Our results provide evidence that maxima in feature channel representations, e.g., the lateral or longitudinal extension, define elemental features to specify key poses of biological motion patterns. These findings provide support for models which aim at automatically building visual representations for the cortical processing of articulated motion by identifying temporally localized events in a continuous input stream.
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