The Influence of a Low-Level Color or Figure Adaptation on a High-Level Face Perception

Miao SONG  Keizo SHINOMORI  Shiyong ZHANG  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E93-D   No.1   pp.176-184
Publication Date: 2010/01/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E93.D.176
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Biocybernetics, Neurocomputing
Keyword: 
human visual system,  low level neural representation,  high-level neural representation,  adaptation paradigm,  face perception,  

Full Text: PDF(340.6KB)>>
Buy this Article




Summary: 
Visual adaptation is a universal phenomenon associated with human visual system. This adaptation affects not only the perception of low-level visual systems processing color, motion, and orientation, but also the perception of high-level visual systems processing complex visual patterns, such as facial identity and expression. Although it remains unclear for the mutual interaction mechanism between systems at different levels, this issue is the key to understand the hierarchical neural coding and computation mechanism. Thus, we examined whether the low-level adaptation influences on the high-level aftereffect by means of cross-level adaptation paradigm (i.e. color, figure adaptation versus facial identity adaptation). We measured the identity aftereffects within the real face test images on real face, color chip and figure adapting conditions. The cross-level mutual influence was evaluated by the aftereffect size among different adapting conditions. The results suggest that the adaptation to color and figure contributes to the high-level facial identity aftereffect. Besides, the real face adaptation obtained the significantly stronger aftereffect than the color chip or the figure adaptation. Our results reveal the possibility of cross-level adaptation propagation and implicitly indicate a high-level holistic facial neural representation. Based on these results, we discussed the theoretical implication of cross-level adaptation propagation for understanding the hierarchical sensory neural systems.