Probing the Feature Map for Faces in Visual Search

Controversy surrounds the mechanisms underlying the pop-out effect for faces in visual search. Is there a feature map for faces? If so, does it rely on the categorical distinction between faces and nonfaces, or on image-level face semblance? To probe the feature map, we compared search efficiency for faces, and nonface stimuli with high, low, and no face semblance. First, subjects performed a visual search task with objects as distractors. Only faces popped-out. Moreover, search efficiency for nonfaces correlated with image-level face semblance of the target. In a second experiment, faces were used as distractors but nonfaces did not pop-out. Interestingly, search efficiency for nonfaces was not modulated by face semblance, although searching for a face among faces was particularly difficult, reflecting a categorical boundary between nonfaces and faces. Finally, inversion and contrast negation significantly interacted with the effect of face semblance, ruling out the possibility that search efficiency solely depends on low-level features. Our study supports a parallel search for faces that is perhaps preattentive. Like other features (color, orientation etc.), there appears to be a continuous face feature map for visual search. Our results also suggest that this map may include both image-level face semblance and face categoricity