Mixture-modeling approach reveals global and local processes in visual crowding

Mikel Jimenez, Ruth Kimchi, Amit Yashar

Research output: Contribution to journalArticlepeer-review


Crowding refers to the inability to recognize objects in clutter, setting a fundamental limit on various perceptual tasks such as reading and facial recognition. While prevailing models suggest that crowding is a unitary phenomenon occurring at an early level of processing, recent studies have shown that crowding might also occur at higher levels of representation. Here we investigated whether local and global crowding interference co-occurs within the same display. To do so, we tested the distinctive contribution of local flanker features and global configurations of the flankers on the pattern of crowding errors. Observers (n = 27) estimated the orientation of a target when presented alone or surrounded by flankers. Flankers were grouped into a global configuration, forming an illusory rectangle when aligned or a rectangular configuration when misaligned. We analyzed the error distributions by fitting probabilistic mixture models. Results showed that participants often misreported the orientation of a flanker instead of that of the target. Interestingly, in some trials the orientation of the global configuration was misreported. These results suggest that crowding occurs simultaneously across multiple levels of visual processing and crucially depends on the spatial configuration of the stimulus. Our results pose a challenge to models of crowding with an early single pooling stage and might be better explained by models which incorporate the possibility of multilevel crowding and account for complex target-flanker interactions.

Original languageEnglish
Article number6726
Pages (from-to)6726
JournalScientific Reports
Issue number1
StatePublished - 25 Apr 2022

Bibliographical note

Publisher Copyright:
© 2022, The Author(s).


  • Crowding
  • Facial Recognition
  • Humans
  • Illusions
  • Visual Fields
  • Visual Perception


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