We used color contrast adaptation to examine the chromatic and contrast selectivity of central color mechanisms. Adaptation to a field whose color varies along a single axis of color space induces a selective loss in sensitivity to the adapting axis. The resulting changes in color appearance are consistent with mechanisms formed by different linear combinations of the cone signals. We asked whether the visual system could also adjust to higher-order variations in the adapting stimulus, by adapting observers to interleaved variations along both the L versus M and the S versus LM cardinal axes. The perceived hue of test stimuli was then measured with an asymmetric matching task. Frequency analysis of the hue shifts revealed weak but systematic hue rotations away from each cardinal axis and toward the diagonal intermediate axes. Such shifts could arise if the adapted channels include mechanisms with narrow chromatic selectivity, as some physiological recordings suggest, but could also reflect how adaptation alters the contrast response function. In either case they imply the presence of more than two mechanisms within the chromatic plane. In a second set of measurements, we adapted to either the L versus M or the S versus LM axis alone and tested whether the changes in hue could be accounted for by changes in relative contrast along the two axes. For high contrasts the hue biases are larger than the contrast changes predict. This dissociation implies that the contrast and hue changes are not carried by a common underlying signal, and could arise if the contrast along a single color direction is encoded by more than one mechanism with different contrast sensitivities or if different subsets of channels encode contrast and hue. Such variations in contrast sensitivity are also consistent with physiological recordings of cortical neurons.
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.
No abstract
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.