AbstractWe effortlessly interact with objects in our environment, but how do we know where something is? An object’s apparent position does not simply correspond to its retinotopic location but is influenced by its surrounding context. In the natural environment, this context is highly complex, and little is known about how visual information in a scene influences the apparent location of the objects within it. We measured the influence of local image statistics (luminance, edges, object boundaries, and saliency) on the reported location of a brief target superimposed on images of natural scenes. For each image statistic, we calculated the difference between the image value at the physical center of the target and the value at its reported center, using observers’ cursor responses, and averaged the resulting values across all trials. To isolate image-specific effects, difference scores were compared to a randomly-permuted null distribution that accounted for any response biases. The observed difference scores indicated that responses were significantly biased toward darker regions, luminance edges, object boundaries, and areas of high saliency, with relatively low shared variance among these measures. In addition, we show that the same image statistics were associated with observers’ saccade errors, despite large differences in response time, and that some effects persisted when high-level scene processing was disrupted by 180° rotations and color negatives of the originals. Together, these results provide evidence for landmark effects within natural images, in which feature location reports are pulled toward low- and high-level informative content in the scene.
A Unified Theory Of Early Visual Representations From Retina To Cortex Through Anatomically Constrained Deep CNNs
