September 2017
Volume 17, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2017
Artificially-generated scenes demonstrate the importance of global scene properties for scene perception
Author Affiliations
  • Mavuso Mzozoyana
    Department of Psychology, Wright State University
  • Matthew Lowe
    Department of Psychology, University of Toronto Scarborough
    Department of Psychology, University of Toronto St. George
  • Iris Groen
    Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health
  • Jonathan Cant
    Department of Psychology, University of Toronto Scarborough
  • Assaf Harel
    Department of Psychology, Wright State University
Journal of Vision August 2017, Vol.17, 312. doi:10.1167/17.10.312
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      Mavuso Mzozoyana, Matthew Lowe, Iris Groen, Jonathan Cant, Assaf Harel; Artificially-generated scenes demonstrate the importance of global scene properties for scene perception. Journal of Vision 2017;17(10):312. doi: 10.1167/17.10.312.

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

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Abstract

A recent surge of behavioral, neuroimaging, and electrophysiological studies highlights the significance of global scene properties, such as spatial boundary and naturalness, for scene perception and categorization. The stimuli used in these studies are oftentimes real-world naturalistic scene images, which while essential for maintaining ecological validity, also pose a real challenge for interpretation. Specifically, since real-world scenes vary dramatically in physical stimulus properties (e.g. color) and range of semantic categories they span, it is difficult to isolate the unique role that global scene properties play in scene processing. To overcome this challenge, the present study used a set of computer-generated scene stimuli (Lowe at al., 2016) that were designed to control for two global scene properties (spatial boundary and naturalness) while minimizing and controlling for other sources of scene information, such as color and semantic category. The set comprised of 576 individual grayscale scene exemplars spanning 12 spatial layouts and 12 textures for each combination of naturalness (manmade/natural) and spatial boundary (open/closed). We presented these artificial scenes to participants while their Event-Related Potentials (ERPs) were recorded. We aimed to establish whether the artificial scenes would generate similar electrophysiological signatures of naturalness and spatial boundary previously obtained using real-world scene images (Harel et al., 2016). Strikingly, we found that similar to previous work, the peak amplitude of the P2 ERP component was sensitive to both the spatial boundary and naturalness of the scenes despite vast differences between the stimuli. In addition, we also found earlier effects of spatial boundary and naturalness, expressed as a modulation of the amplitude of the P1 and N1 components. These results suggest that naturalness and spatial boundary have a robust influence on the nature of scene processing. This influence is independent of scene category and color, and might be observed earlier than previously thought.

Meeting abstract presented at VSS 2017

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