Topological dominance in peripheral vision

The question of what peripheral vision is good for, especially in pattern recognition, is one of the most important and controversial issues in cognitive science. In a series of experiments, we provide substantial evidence that observers’ behavioral performance in the periphery is consistently superior to central vision for topological change detection, while nontopological change detection deteriorates with increasing eccentricity. These experiments generalize the topological account of object perception in the periphery to different kinds of topological changes (i.e., including introduction, disappearance, and change in number of holes) in comparison with a broad spectrum of geometric properties (e.g., luminance, similarity, spatial frequency, perimeter, and shape of the contour). Moreover, when the stimuli were scaled according to cortical magnification factor and the task difficulty was well controlled by adjusting luminance of the background, the advantage of topological change detection in the periphery remained. The observed advantage of topological change detection in the periphery supports the view that the topological definition of objects provides a coherent account for object perception in peripheral vision, allowing pattern recognition with limited acuity.