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  Low-level image statistics in natural scenes influence perceptual decision-making

Seijdel, N., Jahfari, S., Groen, I. I. A., & Scholte, H. S. (2020). Low-level image statistics in natural scenes influence perceptual decision-making. Scientific Reports, 10: 10573. doi:10.1038/s41598-020-67661-8.

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© The Author(s) 2020 This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
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Seijdel, Noor1, Author              
Jahfari, Sara, Author
Groen, Iris I. A. , Author
Scholte, H. Steven, Author
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1University of Amsterdam, Amsterdam, The Netherlands, ou_persistent22              

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 Abstract: A fundamental component of interacting with our environment is gathering and interpretation of sensory information. When investigating how perceptual information influences decision-making, most researchers have relied on manipulated or unnatural information as perceptual input, resulting in findings that may not generalize to real-world scenes. Unlike simplified, artificial stimuli, real-world scenes contain low-level regularities that are informative about the structural complexity, which the brain could exploit. In this study, participants performed an animal detection task on low, medium or high complexity scenes as determined by two biologically plausible natural scene statistics, contrast energy (CE) or spatial coherence (SC). In experiment 1, stimuli were sampled such that CE and SC both influenced scene complexity. Diffusion modelling showed that the speed of information processing was affected by low-level scene complexity. Experiment 2a/b refined these observations by showing how isolated manipulation of SC resulted in weaker but comparable effects, with an additional change in response boundary, whereas manipulation of only CE had no effect. Overall, performance was best for scenes with intermediate complexity. Our systematic definition quantifies how natural scene complexity interacts with decision-making. We speculate that CE and SC serve as an indication to adjust perceptual decision-making based on the complexity of the input.

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Language(s): eng - English
 Dates: 2020-06-29
 Publication Status: Published online
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 Rev. Type: Peer
 Identifiers: DOI: 10.1038/s41598-020-67661-8
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Title: Scientific Reports
  Abbreviation : Sci. Rep.
Source Genre: Journal
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Publ. Info: London, UK : Nature Publishing Group
Pages: - Volume / Issue: 10 Sequence Number: 10573 Start / End Page: - Identifier: ISSN: 2045-2322
CoNE: https://pure.mpg.de/cone/journals/resource/2045-2322