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

Abstract

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.

Transient attention equally reduces visual crowding in radial and tangential axes

“…Recent studies have shown that crowding can occur at various levels of visual processing (e.g., Jimenez, Kimchi, & Yashar, 2022 ; Manassi & Whitney, 2018 ). For example, in addition to basic features, crowding can occur during the processing of complex stimuli, such as abstract shapes ( Kimchi & Pirkner, 2015 ; Pirkner & Kimchi, 2017 ), everyday objects ( Wallace & Tjan, 2011 ), faces ( Farzin, Rivera, & Whitney, 2009 ; Louie, Bressler, & Whitney, 2007 ; Martelli, Majaj, & Pelli, 2005 ), or words ( Martelli et al, 2005 ).…”

“…For example, in addition to basic features, crowding can occur during the processing of complex stimuli, such as abstract shapes ( Kimchi & Pirkner, 2015 ; Pirkner & Kimchi, 2017 ), everyday objects ( Wallace & Tjan, 2011 ), faces ( Farzin, Rivera, & Whitney, 2009 ; Louie, Bressler, & Whitney, 2007 ; Martelli, Majaj, & Pelli, 2005 ), or words ( Martelli et al, 2005 ). Moreover, stimulus grouping and stimulus configuration can modulate crowding effects (e.g., Banks & White, 1984 ; Jimenez et al, 2022 ; Livne & Sagi, 2007 ; Malania, Herzog, & Westheimer, 2007 ). For example, recently, Jimenez et al (2022 ) showed that grouping into a global configuration that forms an illusory shape interacted with the crowding of local features, suggesting that crowding co-occurs across multiple levels of visual processing.…”

“…Moreover, stimulus grouping and stimulus configuration can modulate crowding effects (e.g., Banks & White, 1984 ; Jimenez et al, 2022 ; Livne & Sagi, 2007 ; Malania, Herzog, & Westheimer, 2007 ). For example, recently, Jimenez et al (2022 ) showed that grouping into a global configuration that forms an illusory shape interacted with the crowding of local features, suggesting that crowding co-occurs across multiple levels of visual processing. However, the underlying processes of crowding are still unknown.…”

The role of spatial attention in crowding and feature binding

“…Finally, the effect of locus of attention may vary across the different types of crowding errors. Investigations of the pattern of crowding errors have revealed that crowding often leads to the misreporting of a flanker as the target ( Ester, Klee, & Awh, 2014 ; Freeman, Chakravarthi, & Pelli, 2012 ; Harrison & Bex, 2015 ; Jimenez, Kimchi, & Yashar, 2022 ; Strasburger & Malania, 2013 ; Yashar et al, 2019 ). However, the effect of crowding on the perception of orientation, color, spatial frequency (SF), and motion is distinctive ( Greenwood & Parsons, 2020 ; Yashar et al, 2019 ).…”

Temporal crowding with central vision reveals the fragility of visual representations.

“…Because Experiments 1, 2, and 4 were conducted online, Experiment 3 was conducted as a lab validation under fully controlled conditions. The estimation errors were analyzed with the two-misreport mixture model (Jimenez et al, 2022; Kewan-Khalayly & Yashar, 2022; Shechter & Yashar, 2021; Yashar et al, 2019; see Mixture-Model Analysis section below). The main questions tested here were whether temporal crowding will emerge under foveal presentation (i.e., whether we will find a significant effect of SOA on some or all the parameters extracted with the mixture-modeling approach), and if so whether the pattern of results will be similar to that observed at the periphery.…”