Poster Session: In search of Attention Restoration: does the statistical stability of natural images support enhanced visual cognition? Article Swipe
Shoaib Nabil
,
John Maule
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1167/jov.25.5.43
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1167/jov.25.5.43
Stable visual ensemble statistics can support performance on a visual search task (e.g. Corbett and Melcher, 2014). Such results may indicate improvements in the efficiency of visual cognition in response to a more predictable environment. Observations of improved cognition when immersed in nature (e.g. Berman et al., 2008) have been related to concepts of perceptual fluency and Attention Restoration. We investigated whether the statistical stability of natural scenes could be the underlying mechanism supporting enhancements in visual cognition related to natural images. In experiment 1, we replicated the first study from Corbett and Melcher (2014), showing that sequences of trials with a stable mean size of Gabor elements results in enhanced visual search for an orientation singleton target, compared to sequences with an unstable mean size. In experiment 2, we embedded visual search targets within a set of natural scene images. We leveraged existing variation in the image statistics between images to present sequences where the slope of the Fourier amplitude spectrum was relatively stable (gradually increasing/decreasing) or unstable (randomly ordered). The results have implications for our understanding of the effect of the visual environment on visuo-cognitive functions and the extraction of image statistics by the visual system. We discuss the likely role for eye movements in sampling natural scenes.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1167/jov.25.5.43
- OA Status
- gold
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4409360155
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4409360155Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1167/jov.25.5.43Digital Object Identifier
- Title
-
Poster Session: In search of Attention Restoration: does the statistical stability of natural images support enhanced visual cognition?Work title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-04-01Full publication date if available
- Authors
-
Shoaib Nabil, John MauleList of authors in order
- Landing page
-
https://doi.org/10.1167/jov.25.5.43Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1167/jov.25.5.43Direct OA link when available
- Concepts
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Session (web analytics), Natural (archaeology), Cognition, Stability (learning theory), Psychology, Cognitive psychology, Computer science, Visual search, Neuroscience, Machine learning, Geography, World Wide Web, ArchaeologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.size. | 125 |
| abstract_inverted_index.slope | 156 |
| abstract_inverted_index.study | 89 |
| abstract_inverted_index.where | 154 |
| abstract_inverted_index.2014). | 16 |
| abstract_inverted_index.Berman | 44 |
| abstract_inverted_index.Stable | 0 |
| abstract_inverted_index.effect | 180 |
| abstract_inverted_index.images | 150 |
| abstract_inverted_index.likely | 201 |
| abstract_inverted_index.nature | 42 |
| abstract_inverted_index.scenes | 67 |
| abstract_inverted_index.search | 10, 112, 132 |
| abstract_inverted_index.stable | 102, 164 |
| abstract_inverted_index.trials | 99 |
| abstract_inverted_index.visual | 1, 9, 26, 76, 111, 131, 183, 196 |
| abstract_inverted_index.within | 134 |
| abstract_inverted_index.(2014), | 94 |
| abstract_inverted_index.Corbett | 13, 91 |
| abstract_inverted_index.Fourier | 159 |
| abstract_inverted_index.Melcher | 93 |
| abstract_inverted_index.between | 149 |
| abstract_inverted_index.discuss | 199 |
| abstract_inverted_index.fluency | 55 |
| abstract_inverted_index.images. | 81, 140 |
| abstract_inverted_index.natural | 66, 80, 138, 208 |
| abstract_inverted_index.present | 152 |
| abstract_inverted_index.related | 50, 78 |
| abstract_inverted_index.results | 18, 108, 172 |
| abstract_inverted_index.scenes. | 209 |
| abstract_inverted_index.showing | 95 |
| abstract_inverted_index.support | 5 |
| abstract_inverted_index.system. | 197 |
| abstract_inverted_index.target, | 117 |
| abstract_inverted_index.targets | 133 |
| abstract_inverted_index.whether | 61 |
| abstract_inverted_index.Melcher, | 15 |
| abstract_inverted_index.compared | 118 |
| abstract_inverted_index.concepts | 52 |
| abstract_inverted_index.elements | 107 |
| abstract_inverted_index.embedded | 130 |
| abstract_inverted_index.enhanced | 110 |
| abstract_inverted_index.ensemble | 2 |
| abstract_inverted_index.existing | 143 |
| abstract_inverted_index.immersed | 40 |
| abstract_inverted_index.improved | 37 |
| abstract_inverted_index.indicate | 20 |
| abstract_inverted_index.response | 29 |
| abstract_inverted_index.sampling | 207 |
| abstract_inverted_index.spectrum | 161 |
| abstract_inverted_index.unstable | 123, 168 |
| abstract_inverted_index.(randomly | 169 |
| abstract_inverted_index.Attention | 57 |
| abstract_inverted_index.amplitude | 160 |
| abstract_inverted_index.cognition | 27, 38, 77 |
| abstract_inverted_index.functions | 187 |
| abstract_inverted_index.leveraged | 142 |
| abstract_inverted_index.mechanism | 72 |
| abstract_inverted_index.movements | 205 |
| abstract_inverted_index.ordered). | 170 |
| abstract_inverted_index.sequences | 97, 120, 153 |
| abstract_inverted_index.singleton | 116 |
| abstract_inverted_index.stability | 64 |
| abstract_inverted_index.variation | 144 |
| abstract_inverted_index.(gradually | 165 |
| abstract_inverted_index.efficiency | 24 |
| abstract_inverted_index.experiment | 83, 127 |
| abstract_inverted_index.extraction | 190 |
| abstract_inverted_index.perceptual | 54 |
| abstract_inverted_index.relatively | 163 |
| abstract_inverted_index.replicated | 86 |
| abstract_inverted_index.statistics | 3, 148, 193 |
| abstract_inverted_index.supporting | 73 |
| abstract_inverted_index.underlying | 71 |
| abstract_inverted_index.environment | 184 |
| abstract_inverted_index.orientation | 115 |
| abstract_inverted_index.performance | 6 |
| abstract_inverted_index.predictable | 33 |
| abstract_inverted_index.statistical | 63 |
| abstract_inverted_index.Observations | 35 |
| abstract_inverted_index.Restoration. | 58 |
| abstract_inverted_index.enhancements | 74 |
| abstract_inverted_index.environment. | 34 |
| abstract_inverted_index.implications | 174 |
| abstract_inverted_index.improvements | 21 |
| abstract_inverted_index.investigated | 60 |
| abstract_inverted_index.understanding | 177 |
| abstract_inverted_index.visuo-cognitive | 186 |
| abstract_inverted_index.increasing/decreasing) | 166 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/13 |
| sustainable_development_goals[0].score | 0.46000000834465027 |
| sustainable_development_goals[0].display_name | Climate action |
| citation_normalized_percentile.value | 0.12771718 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |