Abstract
Face animacy perception is categorical: Gradual changes in the real/artificial appearance of a face lead to nonlinear behavioral responses. Neural markers of face processing are also sensitive to face animacy, further suggesting that these are meaningful perceptual categories. Artificial faces also appear to be an “out-group” relative to real faces such that behavioral markers of expert-level processing are less evident with artificial faces than real ones. In the current study, we examined how categorical processing of real versus doll faces was impacted by the face inversion effect, which is one of the most robust markers of expert face processing. We examined how explicit categorization of faces drawn from a real/doll morph continuum was affected by face inversion (Experiment 1) and also how the response properties of the N170 were impacted by face animacy and inversion. We found that inversion does not change the position or steepness of the category boundary measured behaviorally. Further, neural markers of face processing are equally impacted by inversion regardless of whether they are elicited by real faces or doll faces. On balance, our results indicate that inversion has a limited impact on the categorical perception of face animacy.
Highlights
The perception of face animacy, which is the distinction between real and artificial faces, appears to be categorical
Participants shift rapidly from labeling faces as being real to labeling them as doll faces near the midpoint of the animacy spectrum, which could reflect the presence of a category boundary in this region
The microgenesis of animacy categorization has not been characterized and so it may be the case that observers require additional time to extract sufficient information about face appearance to enforce the conservative labeling that leads to this shift in the psychometric function
Summary
The perception of face animacy, which is the distinction between real and artificial faces, appears to be categorical. When participants are asked to categorize faces that fall along a morph continuum spanning real and doll appearance as either real or artificial, those judgments exhibit the sigmoidal shape that typically reflects categorical perception (Looser & Wheatley, 2010). This effect has been observed with both doll faces and computer-generated (CG) faces (Balas & Horski, 2012; Balas & Tonsager, 2014), suggesting that the particular type of artificial face does not matter. Besides these instances of face animacy impacting other categorical face properties, there is evidence that multiple indices of face-specific processing in the ventral visual stream are sensitive to real versus artificial appearance (Looser, Guntupalli, & Wheatley, 2013; Wheatley, Weinberg, Looser, Moran, & Hajcak, 2011), further suggesting that these stimuli differ categorically at later stages of cortical processing
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