A computational model of visual stability and change detection during eye movements in real-world scenes

Visual cognition and change detection critically depend on attention and gaze. A central question is the exact involvement of attention in change detection. This paper proposes a detailed computational model to illuminate the nature of visual stability and change detection during eye movements. Consistent with experimental findings the model predicts that change detection at the saccade endpoint is relatively easy. According to our model the planning of an eye movement provides an enhanced sensory processing of an object at the saccade target. This facilitates the memorization of that object. A comparison of the memorized target template with the representation after saccade allows for change detection. We hypothesize that the spatial reentry signal that emerges from planning an eye movement could be a crucial neural basis of visual stability.