Recent developments in a computational theory of visual attention (TVA)

• We present and analyze a computational theory of visual attention (TVA).
• We explain recent developments in the theory concerning temporal attention.
• The theory compares favorably with other theories of attention in vision.

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.