A dynamic normalization model of temporal attention

• Published in: Nature human behaviour 2021-12, Vol.5 (12), p.1674-1685
• Main Authors: Denison, Rachel N., Carrasco, Marisa, Heeger, David J.
• Format: Article
• Language: English
• Subjects: 631/378/116; 631/477/2811; Attention - physiology; Behavioral Sciences; Biomedical and Life Sciences; Costs; Cues; Experimental Psychology; Humans; Life Sciences; Microeconomics; Models, Neurological; Neurosciences; Normalization; Perceptual sensitivity; Personality and Social Psychology; Photic Stimulation; Protocol; Reaction Time - physiology; Validity; Variance analysis; Visual attention; Visual Perception - physiology; Voluntariness
• ISSN: 2397-3374; 2397-3374
• DOI: 10.1038/s41562-021-01129-1

Vision is dynamic, handling a continuously changing stream of input, yet most models of visual attention are static. Here, we develop a dynamic normalization model of visual temporal attention and constrain it with new psychophysical human data. We manipulated temporal attention—the prioritization of visual information at specific points in time—to a sequence of two stimuli separated by a variable time interval. Voluntary temporal attention improved perceptual sensitivity only over a specific interval range. To explain these data, we modelled voluntary and involuntary attentional gain dynamics. Voluntary gain enhancement took the form of a limited resource over short time intervals, which recovered over time. Taken together, our theoretical and experimental results formalize and generalize the idea of limited attentional resources across space at a single moment to limited resources across time at a single location. Denison and colleagues present a computational account of attention—temporal dynamic normalization—which extends the idea of limited attentional resources across space at a single moment to a formal account of limited resources across time at a single location.