Investigating attention in complex visual search.

How we attend to and search for objects in the real world is influenced by a host of low-level and higher-level factors whose interactions are poorly understood. The vast majority of studies approach this issue by experimentally controlling one or two factors in isolation, often under conditions with limited ecological validity. We present a comprehensive regression framework, together with a matlab-implemented toolbox, which allows concurrent factors influencing saccade targeting to be more clearly distinguished. Based on the idea of gaze selection as a point process, the framework allows each putative factor to be modeled as a covariate in a generalized linear model, and its significance to be evaluated with model-based hypothesis testing. We apply this framework to visual search for faces as an example and demonstrate its power in detecting effects of eccentricity, inversion, task congruency, emotional expression, and serial fixation order on the targeting of gaze. Among other things, we find evidence for multiple goal-related and goal-independent processes that operate with distinct visuotopy and time course.