title: Recent developments in a computational theory of visual attention (TVA).
abstract: This article reviews the foundations of the theory of visual attention (TVA) and describes recent developments in the theory. TVA is based on the principle of biased competition: All possible visual categorizations ascribing features to objects compete (race) to become encoded into visual short-term memory before it is filled up. Each of the possible categorizations is supported by sensory evidence, but the competition is biased by multiplication with attentional weights (high weights on important objects) and perceptual biases (toward use of important categories). The way sensory evidence and attentional biases interact is specified in the rate and weight equations of TVA, so TVA represents a mathematical formalization of the biased competition principle. In addition to describing TVA as a psychological theory, we present the neural interpretation of TVA, NTVA.
authors.affiliation: University of Copenhagen, Denmark. Electronic address: bundesen@psy.ku.dk.
authors.forename: Claus
authors.initials: C
authors.lastname: Bundesen
authors.affiliation: University of Copenhagen, Denmark.
authors.forename: Signe
authors.initials: S
authors.lastname: Vangkilde
authors.affiliation: University of Copenhagen, Denmark.
authors.forename: Anders
authors.initials: A
authors.lastname: Petersen
mesh_terms: D001288:Attention / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D008570:Memory, Short-Term / Q000502:physiology*; D009483:Neuropsychological Tests; D011582:Psychological Theory; D014796:Visual Perception / Q000502:physiology*
keywords: TVA; Visual attention