September 2017
Volume 17, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2017
Crowding and binding: Not all feature-dimensions behave equally
Author Affiliations
  • Amit Yashar
    Department of Psychology, New York University, New York, NY, USA
  • Xiuyun Wu
    Department of Psychology, New York University, New York, NY, USA
  • Jiageng Chen
    Department of Psychology, New York University, New York, NY, USA
  • Marisa Carrasco
    Department of Psychology, New York University, New York, NY, USA
    Center for Neural Science, New York University, New York, NY, USA
Journal of Vision August 2017, Vol.17, 374. doi:
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      Amit Yashar, Xiuyun Wu, Jiageng Chen, Marisa Carrasco; Crowding and binding: Not all feature-dimensions behave equally. Journal of Vision 2017;17(10):374.

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

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Background. Crowding refers to the failure to identify a peripheral item in clutter. The nature of crowding and the stage at which it occurs are still debated. Crowding has been proposed as the consequence of averaging of nearby features (mixture model), and switch between target and distractor objects (swapping model). We use a novel quantitative approach to disambiguate these two hypotheses and assess the stage of processing at which crowding occurs by characterizing errors and the interdependency of different feature-dimensions. Methods. Observers (n=14) estimated the orientation and spatial frequency (SF) of a Gabor (Exp.1) or the orientation and color of a "T" (Exp.2) via two separate reports. The target was presented at 7° eccentricity. In the crowding conditions, two distractors flanked the target, each with unique features. We characterized crowding errors with respect to each distractor along the two feature-dimensions. We compared two probabilistic models –mixture and swap– to characterize the error distributions for each feature-dimension independently and with respect to the other dimension. Results. Under crowded conditions, the swapping model performed significantly better than the mixture model for orientation and color estimation errors, indicating switch between target and distractor. However, the mixture model better characterized SF errors, indicating averaging across target and distractors. Regarding interdependency, whereas color and orientation swapped independently from each other, SF and orientation errors correlated; the probability to swap orientation with a given distractor was independent of the direction of the color error, but higher when SF error was toward that distractor. Conclusion. Crowding leads to the swapping of color and orientation but averaging of orientation and SF. Whereas orientation and color crowding are independent, orientation and SF are interdependent. Our results suggest that crowding operates after orientation is bound with SF but before it is bound with color.

Meeting abstract presented at VSS 2017


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