Brand, John O. and Johnson, Aaron P. (2014) Attention to local and global levels of hierarchical Navon figures affects rapid scene categorization. Frontiers in Perception Science, 5 (1274). pp. 1-19.
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Official URL: http://dx.doi.org/10.3389/fpsyg.2014.01274
Abstract
In four experiments, we investigated how attention to local and global levels of hierarchical Navon figures affected the selection of diagnostic spatial scale information used in scene categorization. We explored this issue by asking observers to classify hybrid images (i.e., images that contain low spatial frequency (LSF) content of one image, and high spatial frequency (HSF) content from a second image) immediately following global and local Navon tasks. Hybrid images can be classified according to either their LSF, or HSF content; thus, making them ideal for investigating diagnostic spatial scale preference. Although observers were sensitive to both spatial scales (Experiment 1), they overwhelmingly preferred to classify hybrids based on LSF content (Experiment 2). In Experiment 3, we demonstrated that LSF based hybrid categorization was faster following global Navon tasks, suggesting that LSF processing associated with global Navon tasks primed the selection of LSFs in hybrid images. In Experiment 4, replicating Experiment 3 but suppressing the LSF information in Navon letters by contrast balancing the stimuli examined this hypothesis. Similar to Experiment 3, observers preferred to classify hybrids based on LSF content; however and in contrast, LSF based hybrid categorization was slower following global than local Navon tasks.
Divisions: | Concordia University > Faculty of Arts and Science > Psychology |
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Item Type: | Article |
Refereed: | Yes |
Authors: | Brand, John O. and Johnson, Aaron P. |
Journal or Publication: | Frontiers in Perception Science |
Date: | December 2014 |
Funders: |
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Digital Object Identifier (DOI): | 10.3389/fpsyg.2014.01274 |
ID Code: | 979723 |
Deposited By: | AARON JOHNSON |
Deposited On: | 10 Mar 2015 15:01 |
Last Modified: | 18 Jan 2018 17:49 |
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