July 2013
Volume 13, Issue 9
Vision Sciences Society Annual Meeting Abstract  |   July 2013
Parallel extraction of summary information across multi-element arrays
Author Affiliations
  • Jan Balaguer
    Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, UK
  • Andrei Gorea
    CNRS UMR 8158, Laboratoire Psychologie de la Perception, 75006 Paris, France
  • Elizabeth Michael
    Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, UK
  • Christopher Summerfield
    Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, UK
Journal of Vision July 2013, Vol.13, 1359. doi:https://doi.org/10.1167/13.9.1359
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      Jan Balaguer, Andrei Gorea, Elizabeth Michael, Christopher Summerfield; Parallel extraction of summary information across multi-element arrays. Journal of Vision 2013;13(9):1359. https://doi.org/10.1167/13.9.1359.

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      © ARVO (1962-2015); The Authors (2016-present)

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Observers are capable of making rapid and accurate judgments of the summary information in an array composed of multiple elements. Whilst some theories have argued that this suggests that the visual system is capable of automatic extraction of statistical information from a visual scene, others have suggested that serial strategies may play a role. To test whether perceptual averaging occurs in parallel or in series, we asked observers to judge the average feature (shape or colour) in a centrally-presented visual array with a variable number of elements (‘squircles’, i.e. shapes that varied continuously from shape to circle). As reported previously, we found that the variance (heterogeneity) of the array slowed responding and increased error rates, but set size (2, 4 or 8 items) had no influence on performance. Reasoning that it might be possible to average in parallel across information on a single dimension (e.g. shape or colour) but not a conjunction of two dimensions, we devised a new averaging task in which the decision value was continuously signalled by the conjunction of two dimensions, with more red/square or blue/circle items belonging to one category and more blue/square or red/circle items belonging to the other. Surprisingly, for these stimuli we found no influence of the array variability and an inverse set-size effect, with better performance for larger arrays. This latter finding cannot be due to increased precision for larger set sizes (or less variable arrays) because in both experiments elements were pseudosampled to ensure a fixed mean value. Together, these findings suggest that averaging of both one- and two-dimensional information can be conducted in parallel, supporting models suggesting that observers automatically extract summary information from visual scenes.

Meeting abstract presented at VSS 2013


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