Stimulus requirements for face perception: an analysis based on "totem poles".

The stimulus requirements for perceiving a face are not well defined but are presumably simple, for vivid faces can often by seen in random or natural images such as cloud or rock formations. To characterize these requirements, we measured where observers reported the impression of faces in images defined by symmetric 1/f noise. This allowed us to examine the prominence and properties of different features and their necessary configurations. In these stimuli many faces can be perceived along the vertical midline, and appear stacked at multiple scales, reminiscent of "totem poles." In addition to symmetry, the faces in noise are invariably upright and thus reveal the inversion effects that are thought to be a defining property of configural face processing. To a large extent, seeing a face required seeing eyes, and these were largely restricted to dark regions in the images. Other features were more subordinate and showed relatively little bias in polarity. Moreover, the prominence of eyes depended primarily on their luminance contrast and showed little influence of chromatic contrast. Notably, most faces were rated as clearly defined with highly distinctive attributes, suggesting that once an image area is coded as a face it is perceptually completed consistent with this interpretation. This suggests that the requisite trigger features are sufficient to holistically "capture" the surrounding noise structure to form the facial representation. Yet despite these well articulated percepts, we show in further experiments that while a pair of dark spots added to noise images appears face-like, these impressions fail to elicit other signatures of face processing, and in particular, fail to elicit an N170 or fixation patterns typical for images of actual faces. These results suggest that very simple stimulus configurations are sufficient to invoke many aspects of holistic and configural face perception while nevertheless failing to fully engage the neural machinery of face coding, implying that that different signatures of face processing may have different stimulus requirements.