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Fourier power, subjective distance, and object categories all provide plausible models of BOLD responses in scene-selective visual areas

Overview of attention for article published in Frontiers in Computational Neuroscience, November 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

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Title
Fourier power, subjective distance, and object categories all provide plausible models of BOLD responses in scene-selective visual areas
Published in
Frontiers in Computational Neuroscience, November 2015
DOI 10.3389/fncom.2015.00135
Pubmed ID
Authors

Mark D. Lescroart, Dustin E. Stansbury, Jack L. Gallant

Abstract

Perception of natural visual scenes activates several functional areas in the human brain, including the Parahippocampal Place Area (PPA), Retrosplenial Complex (RSC), and the Occipital Place Area (OPA). It is currently unclear what specific scene-related features are represented in these areas. Previous studies have suggested that PPA, RSC, and/or OPA might represent at least three qualitatively different classes of features: (1) 2D features related to Fourier power; (2) 3D spatial features such as the distance to objects in a scene; or (3) abstract features such as the categories of objects in a scene. To determine which of these hypotheses best describes the visual representation in scene-selective areas, we applied voxel-wise modeling (VM) to BOLD fMRI responses elicited by a set of 1386 images of natural scenes. VM provides an efficient method for testing competing hypotheses by comparing predictions of brain activity based on encoding models that instantiate each hypothesis. Here we evaluated three different encoding models that instantiate each of the three hypotheses listed above. We used linear regression to fit each encoding model to the fMRI data recorded from each voxel, and we evaluated each fit model by estimating the amount of variance it predicted in a withheld portion of the data set. We found that voxel-wise models based on Fourier power or the subjective distance to objects in each scene predicted much of the variance predicted by a model based on object categories. Furthermore, the response variance explained by these three models is largely shared, and the individual models explain little unique variance in responses. Based on an evaluation of previous studies and the data we present here, we conclude that there is currently no good basis to favor any one of the three alternative hypotheses about visual representation in scene-selective areas. We offer suggestions for further studies that may help resolve this issue.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 131 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 2 2%
United States 2 2%
Japan 1 <1%
Germany 1 <1%
Unknown 125 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 34 26%
Student > Ph. D. Student 33 25%
Student > Master 12 9%
Professor 8 6%
Student > Postgraduate 8 6%
Other 22 17%
Unknown 14 11%
Readers by discipline Count As %
Neuroscience 43 33%
Psychology 34 26%
Agricultural and Biological Sciences 14 11%
Computer Science 6 5%
Engineering 5 4%
Other 6 5%
Unknown 23 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 29 November 2017.
All research outputs
#5,202,570
of 24,749,767 outputs
Outputs from Frontiers in Computational Neuroscience
#238
of 1,426 outputs
Outputs of similar age
#67,005
of 291,290 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#12
of 36 outputs
Altmetric has tracked 24,749,767 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,426 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one has done well, scoring higher than 83% 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 291,290 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.