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Foveal analysis and peripheral selection during active visual sampling

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)E291-E299
Number of pages9
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number2
Early online date2 Jan 2014
DateAccepted/In press - 19 Nov 2013
DateE-pub ahead of print - 2 Jan 2014
DatePublished (current) - 14 Jan 2014


Human vision is an active process in which information is sampled during brief periods of stable fixation in between gaze shifts. Foveal analysis serves to identify the currently fixated object and has to be coordinated with a peripheral selection process of the next fixation location. Models of visual search and scene perception typically focus on the latter, without considering foveal processing requirements. We developed a dual-task noise classification technique that enables identification of the information uptake for foveal analysis and peripheral selection within a single fixation. Human observers had to use foveal vision to extract visual feature information (orientation) from different locations for a psychophysical comparison. The selection of to-be-fixated locations was guided by a different feature (luminance contrast). We inserted noise in both visual features and identified the uptake of information by looking at correlations between the noise at different points in time and behavior. Our data show that foveal analysis and peripheral selection proceeded completely in parallel. Peripheral processing stopped some time before the onset of an eye movement, but foveal analysis continued during this period. Variations in the difficulty of foveal processing did not influence the uptake of peripheral information and the efficacy of peripheral selection, suggesting that foveal analysis and peripheral selection operated independently. These results provide important theoretical constraints on how to model target selection in conjunction with foveal object identification: in parallel and independently.

    Structured keywords

  • Cognitive Science
  • Visual Perception

    Research areas

  • eye movement control, perceptual decision-making, attention, classification image

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