Abstract
Since its inception, the standard framework to study vision has been, implicitly or explicitly, both hierarchical and feedforward. This framework has facilitated the deconstruction of complex mechanisms into smaller, more tractable problems, and has been extremely successful in characterizing the processing of basic visual elements. However, this framework can break down when elements are presented in context, as they are in every-day life. In crowding, peripheral object discrimination is hindered by the presence of nearby elements, as for example a Vernier embedded in a square is more difficult to discriminate than when presented alone. However, adding additional flanking squares can, counter-intuitively, ameliorate this deleterious effect (Manassi et al, 2013, J Vis). This example demonstrates how, in order to understand low-level vision, we must also understand higher-level processing. Here, we take a step toward this integrated approach by characterizing the effect of flanker configuration on crowding in a theory-agnostic manner. Previous studies have examined a small number of experimenter-selected configurations, whereas here we made no assumptions about which configurations should affect crowding. We placed a Vernier embedded in a square at the centre of all possible 3x5 arrays with an equal number of squares and stars (3432 total). Six observers discriminated this Vernier in the presence of each configuration, repeating each until responding incorrectly or achieving six correct responses in its presence. In this way, we were able to quantify the effect of all possible configurations on performance. Among the many interesting patterns in our large data set, we observed a strong positive correlation between the number of clustered square elements and discrimination performance, as well as evidence for an effect of symmetry. More generally, our data suggest that configurations encouraging separate grouping of target and flanker elements ameliorate crowding, using a paradigm in which grouping was not explicitly manipulated.
Meeting abstract presented at VSS 2017