title: Attention Modulates Spatial Precision in Multiple-Object Tracking.
abstract: We present a computational model of multiple-object tracking that makes trial-level predictions about the allocation of visual attention and the effect of this allocation on observers' ability to track multiple objects simultaneously. This model follows the intuition that increased attention to a location increases the spatial resolution of its internal representation. Using a combination of empirical and computational experiments, we demonstrate the existence of a tight coupling between cognitive and perceptual resources in this task: Low-level tracking of objects generates bottom-up predictions of error likelihood, and high-level attention allocation selectively reduces error probabilities in attended locations while increasing it at non-attended locations. Whereas earlier models of multiple-object tracking have predicted the big picture relationship between stimulus complexity and response accuracy, our approach makes accurate predictions of both the macro-scale effect of target number and velocity on tracking difficulty and micro-scale variations in difficulty across individual trials and targets arising from the idiosyncratic within-trial interactions of targets and distractors.
authors.affiliation: Department of Psychology, University of California, San Diego.
authors.forename: Nisheeth
authors.initials: N
authors.lastname: Srivastava
authors.affiliation: Department of Psychology, University of California, San Diego.
authors.forename: Ed
authors.initials: E
authors.lastname: Vul
mesh_terms: D001288:Attention / Q000502:physiology*; D001499:Bayes Theorem; D019336:Cognitive Science / Q000379:methods; D006801:Humans; D000067489:Metacognition / Q000502:physiology; D009039:Motion Perception / Q000502:physiology; D066230:Patient-Specific Modeling; D010775:Photic Stimulation; D013028:Space Perception / Q000502:physiology*; D014796:Visual Perception / Q000502:physiology
keywords: Attention dynamics; Bayesian models of cognition; Computational cognitive science; Metacognition; Multiple-object tracking; Visual cognition