Abstract
The visual system is tuned to natural image statistics in a variety of ways. Disruptions of natural texture appearance are known to negatively impact performance in texture discrimination tasks, for example, such that contrast-negated textures, synthetic textures, and textures depicting abstract art are processed less efficiently than natural textures. In the current study, we chose to examine how early visual ERP responses (the P1 and the N1) were affected by violations of natural texture appearance. Specifically, we presented participants with texture images that depicted either natural textures or synthetic textures made from the original stimuli . Both stimulus types were additionally rendered either in positive or negative contrast. These appearance manipulations (negation and texture synthesis) preserve a range of low-level features, but also disrupt higher-order aspects of texture appearance. We recorded continuous EEG while 15 participants (8 female) completed a same/different task using the textures described above. On each trial (128 per condition), participants viewed two texture patches presented in sequence (500ms per image, 1000ms ISI) and indicated via a button press whether the two images were identical or not. "Different" trials were comprised of two non-overlapping texture patches drawn from the same larger image. Visual ERPs were time-locked to the onset of the first stimulus in each pair to avoid response-related activity. Analysis of the P1 revealed no effects of either contrast negation or synthetic texture appearance on component amplitude or latency. Both factors did influence the N1 response, however: We observed main effects of contrast polarity (p=0.038) and natural vs. synthetic appearance (p<0.001) on the mean amplitude of the N1, as well as a main effect of synthetic appearance on latency (p=0.004). We conclude that this sensitivity to the differences between natural and unnatural textures suggests early processing of higher-order statistical regularities.
Meeting abstract presented at VSS 2014