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Distinct neural networks for target feature versus dimension changes in visual search, as revealed by EEG and fMRI

Overview of attention for article published in NeuroImage, September 2014
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Title
Distinct neural networks for target feature versus dimension changes in visual search, as revealed by EEG and fMRI
Published in
NeuroImage, September 2014
DOI 10.1016/j.neuroimage.2014.08.058
Pubmed ID
Authors

Stefanie I. Becker, Anna Grubert, Paul E. Dux

Abstract

In visual search, responses are slowed, from one trial to the next, both when the target dimension changes (e.g., from a color target to a size target) and when the target feature changes (e.g., from a red target to a green target) relative to being repeated across trials. The present study examined whether such feature and dimension switch costs can be attributed to the same underlying mechanism(s). Contrary to this contention, an EEG study showed that feature changes influenced visual selection of the target (i.e., delayed N2pc onset), whereas dimension changes influenced the later process of response selection (i.e., delayed s-LRP onset). An fMRI study provided convergent evidence for the two-system view: Compared with repetitions, feature changes led to increased activation in the occipital cortex, and superior and inferior parietal lobules, which have been implicated in spatial attention. By contrast, dimension changes led to activation of a fronto-posterior network that is primarily linked with response selection (i.e., pre-motor cortex, supplementary motor area and frontal areas). Taken together, the results suggest that feature and dimension switch costs are based on different processes. Specifically, whereas target feature changes delay attention shifts to the target, target dimension changes interfere with later response selection operations.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Netherlands 1 2%
United States 1 2%
Unknown 56 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 20%
Student > Master 9 15%
Researcher 9 15%
Student > Doctoral Student 8 14%
Professor 5 8%
Other 6 10%
Unknown 10 17%
Readers by discipline Count As %
Psychology 22 37%
Neuroscience 12 20%
Engineering 5 8%
Medicine and Dentistry 5 8%
Decision Sciences 2 3%
Other 3 5%
Unknown 10 17%
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 09 September 2014.
All research outputs
#20,655,488
of 25,373,627 outputs
Outputs from NeuroImage
#10,823
of 12,204 outputs
Outputs of similar age
#182,931
of 250,095 outputs
Outputs of similar age from NeuroImage
#126
of 151 outputs
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