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Model Cortical Association Fields Account for the Time Course and Dependence on Target Complexity of Human Contour Perception

Overview of attention for article published in PLoS Computational Biology, October 2011
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

blogs
2 blogs
twitter
6 X users
googleplus
1 Google+ user

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
47 Mendeley
citeulike
1 CiteULike
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Title
Model Cortical Association Fields Account for the Time Course and Dependence on Target Complexity of Human Contour Perception
Published in
PLoS Computational Biology, October 2011
DOI 10.1371/journal.pcbi.1002162
Pubmed ID
Authors

Vadas Gintautas, Michael I. Ham, Benjamin Kunsberg, Shawn Barr, Steven P. Brumby, Craig Rasmussen, John S. George, Ilya Nemenman, Luís M. A. Bettencourt, Garret T. Kenyon

Abstract

Can lateral connectivity in the primary visual cortex account for the time dependence and intrinsic task difficulty of human contour detection? To answer this question, we created a synthetic image set that prevents sole reliance on either low-level visual features or high-level context for the detection of target objects. Rendered images consist of smoothly varying, globally aligned contour fragments (amoebas) distributed among groups of randomly rotated fragments (clutter). The time course and accuracy of amoeba detection by humans was measured using a two-alternative forced choice protocol with self-reported confidence and variable image presentation time (20-200 ms), followed by an image mask optimized so as to interrupt visual processing. Measured psychometric functions were well fit by sigmoidal functions with exponential time constants of 30-91 ms, depending on amoeba complexity. Key aspects of the psychophysical experiments were accounted for by a computational network model, in which simulated responses across retinotopic arrays of orientation-selective elements were modulated by cortical association fields, represented as multiplicative kernels computed from the differences in pairwise edge statistics between target and distractor images. Comparing the experimental and the computational results suggests that each iteration of the lateral interactions takes at least [Formula: see text] ms of cortical processing time. Our results provide evidence that cortical association fields between orientation selective elements in early visual areas can account for important temporal and task-dependent aspects of the psychometric curves characterizing human contour perception, with the remaining discrepancies postulated to arise from the influence of higher cortical areas.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 9%
United Kingdom 2 4%
Mexico 1 2%
Portugal 1 2%
Unknown 39 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 30%
Researcher 8 17%
Professor 4 9%
Student > Master 4 9%
Student > Postgraduate 3 6%
Other 8 17%
Unknown 6 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 34%
Neuroscience 6 13%
Computer Science 5 11%
Psychology 3 6%
Physics and Astronomy 2 4%
Other 9 19%
Unknown 6 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 31 January 2012.
All research outputs
#1,970,821
of 25,394,764 outputs
Outputs from PLoS Computational Biology
#1,753
of 8,964 outputs
Outputs of similar age
#9,589
of 145,977 outputs
Outputs of similar age from PLoS Computational Biology
#20
of 127 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,964 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has done well, scoring higher than 80% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 145,977 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 127 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.