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Detecting Unidentified Changes

Overview of attention for article published in PLOS ONE, January 2014
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Title
Detecting Unidentified Changes
Published in
PLOS ONE, January 2014
DOI 10.1371/journal.pone.0084490
Pubmed ID
Authors

Piers D. L. Howe, Margaret E. Webb

Abstract

Does becoming aware of a change to a purely visual stimulus necessarily cause the observer to be able to identify or localise the change or can change detection occur in the absence of identification or localisation? Several theories of visual awareness stress that we are aware of more than just the few objects to which we attend. In particular, it is clear that to some extent we are also aware of the global properties of the scene, such as the mean luminance or the distribution of spatial frequencies. It follows that we may be able to detect a change to a visual scene by detecting a change to one or more of these global properties. However, detecting a change to global property may not supply us with enough information to accurately identify or localise which object in the scene has been changed. Thus, it may be possible to reliably detect the occurrence of changes without being able to identify or localise what has changed. Previous attempts to show that this can occur with natural images have produced mixed results. Here we use a novel analysis technique to provide additional evidence that changes can be detected in natural images without also being identified or localised. It is likely that this occurs by the observers monitoring the global properties of the scene.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
France 1 2%
Australia 1 2%
United Kingdom 1 2%
United States 1 2%
Unknown 47 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 23%
Student > Ph. D. Student 10 19%
Student > Bachelor 10 19%
Student > Master 6 12%
Professor 2 4%
Other 9 17%
Unknown 3 6%
Readers by discipline Count As %
Psychology 29 56%
Agricultural and Biological Sciences 4 8%
Physics and Astronomy 2 4%
Social Sciences 2 4%
Computer Science 2 4%
Other 9 17%
Unknown 4 8%