Visual causes versus correlates of attentional selection in dynamic scenes.

What are the visual causes, rather than mere correlates, of attentional selection and how do they compare to each other during natural vision? To address these questions, we first strung together semantically unrelated dynamic scenes into MTV-style video clips, and performed eye tracking experiments with human observers. We then quantified predictions of saccade target selection based on seven bottom-up models, including intensity variance, orientation contrast, intensity contrast, color contrast, flicker contrast, motion contrast, and integrated saliency. On average, all tested models predicted saccade target selection well above chance. Dynamic models were particularly predictive of saccades that were most likely bottom-up driven-initiated shortly after scene onsets, leading to maximal inter-observer similarity. Static models showed mixed results in these circumstances, with intensity variance and orientation contrast featuring particularly weak prediction accuracy (lower than their own average, and approximately 4 times lower than dynamic models). These results indicate that dynamic visual cues play a dominant causal role in attracting attention. In comparison, some static visual cues play a weaker causal role, while other static cues are not causal at all, and may instead reflect top-down causes.