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Detecting global form: separate processes required for Glass and radial frequency patterns

Overview of attention for article published in Frontiers in Computational Neuroscience, January 2013
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Title
Detecting global form: separate processes required for Glass and radial frequency patterns
Published in
Frontiers in Computational Neuroscience, January 2013
DOI 10.3389/fncom.2013.00053
Pubmed ID
Authors

David R. Badcock, Renita A. Almeida, J. Edwin Dickinson

Abstract

Global processing of form information has been studied extensively using both Glass and radial frequency (RF) patterns. Models, with common early stages, have been proposed for the detection of properties of both pattern types but human performance has not been examined to determine whether the two pattern types interact in the manner this would suggest. The experiments here investigated whether low RF patterns and concentric Glass patterns, which are thought to tap the same level of processing in form-vision, are detected by a common mechanism. Six observers participated in two series of masking experiments. First: sensitivity to the presence of either coherent structure, or contour deformation, was assessed. The computational model predicted that detection of one pattern would be masked by the other. Second: a further experiment examined position coding. The model predicted that localizing the center of form in a Glass pattern would be affected by the presence of an RF pattern: sensitivity to a change of location should be reduced and the apparent location should be drawn toward the center of the masking pattern. However, the results observed in all experiments were inconsistent with the interaction predicted by the models, suggesting that separate neural mechanisms for global processing of signal are required to process these two patterns, and also indicating that the models need to be altered to preclude the interactions that were predicted but not obtained.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 31%
Student > Ph. D. Student 3 19%
Student > Doctoral Student 2 13%
Student > Bachelor 1 6%
Lecturer 1 6%
Other 3 19%
Unknown 1 6%
Readers by discipline Count As %
Psychology 5 31%
Neuroscience 4 25%
Engineering 2 13%
Chemistry 1 6%
Computer Science 1 6%
Other 0 0%
Unknown 3 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 May 2013.
All research outputs
#20,192,189
of 22,709,015 outputs
Outputs from Frontiers in Computational Neuroscience
#1,157
of 1,336 outputs
Outputs of similar age
#248,747
of 280,729 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#105
of 131 outputs
Altmetric has tracked 22,709,015 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,336 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 131 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.