Understanding why and how we move visual attention – a perspective on low-level stimulus features and cost
Deciding how, whether, and where to move the eyes is arguably one of the most frequent decisions that humans make, but which factors determine its outcome? In my talk I will focus on two factors that shape this decision besides the top down goals of the beholder.
First, I will talk about how low-level stimulus features (such as contrasts, spatial frequencies etc.) drive eye movements across the lifespan. Saliency maps, computational models of human visual attention based on these features, are generated using eye movements across a wide range of visual scenes, but validated using only few participants. Generalizations across individuals are generally implied, however. Here, I present gaze data of 8,325 participants to a single image to test for generalization across participants to test for their ability to generalize across participants. Strikingly, models performed well on participants aged 18-35, but poorly for other age groups, with children in particular. Modelling and understanding gaze behavior beyond college-student like samples thus requires an approach which incorporates knowledge on differences in gaze behavior across the lifespan or at least validation on (age)-diverse samples.
Second, I introduce a cost perspective to how we shift our attention. I propose that not all shifts of attention are equally costly – and therefore ‘cheaper’ and more ‘expensive’ options will be weighed against each other. Using pupil dilation, a potent marker of attention in general and the arguably closest physiological correlate to mental effort, we assessed the mental costs associated with planning shifts in covert attention and the costs associated with saccades. We found saccades to be more costly than shifts in covert attention as indexed by stronger pupil dilation during planning. Furthermore, we found cardinal saccades to be significantly less costly than oblique saccades. Likely, these pupil dilations reflect the complexity of motor planning as the decisive driver of these differences in cost rather than the motor execution itself.