Areas of Interest as a Signal Detection Problem in Behavioral Eye-Tracking Research

摘要

Decision researchers frequently analyze attention to individual objects to test hypotheses about underlying cognitive processes. Generally, fixations are assigned to objects using a method known as area of interest (AOI). Ideally, an AOI includes all fixations belonging to an object while fixations to other objects are excluded. Unfortunately, due to measurement inaccuracy and insufficient distance between objects, the distributions of fixations to objects may overlap, resulting in a signal detection problem. If the AOI is to include all fixations to an object, it will also likely include fixations belonging to other objects (false positives). In a survey, we find that many researchers report testing multiple AOI sizes when performing analyses, presumably trying to balance the proportion of true and false positive fixations. To test whether AOI size influences the measurement of object attention and conclusions drawn about cognitive processes, we reanalyze four published studies and conduct a fifth tailored to our purpose. We find that in studies in which we expected overlapping fixation distributions, analyses benefited from smaller AOI sizes (0 degrees visual angle margin). In studies where we expected no overlap, analyses benefited from larger AOI sizes (>.5 degrees visual angle margins). We conclude with a guideline for the use of AOIs in behavioral eye-tracking research. Copyright (c) 2015 John Wiley & Sons, Ltd.