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Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks

Overview of attention for article published in Frontiers in Human Neuroscience, March 2018
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Title
Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks
Published in
Frontiers in Human Neuroscience, March 2018
DOI 10.3389/fnhum.2018.00089
Pubmed ID
Authors

Adriana L. Ruiz-Rizzo, Julia Neitzel, Hermann J. Müller, Christian Sorg, Kathrin Finke

Abstract

Separable visual attention functions are assumed to rely on distinct but interacting neural mechanisms. Bundesen's "theory of visual attention" (TVA) allows the mathematical estimation of independent parameters that characterize individuals' visual attentional capacity (i.e., visual processing speed and visual short-term memory storage capacity) and selectivity functions (i.e., top-down control and spatial laterality). However, it is unclear whether these parameters distinctively map onto different brain networks obtained from intrinsic functional connectivity, which organizes slowly fluctuating ongoing brain activity. In our study, 31 demographically homogeneous healthy young participants performed whole- and partial-report tasks and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Report accuracy was modeled using TVA to estimate, individually, the four TVA parameters. Networks encompassing cortical areas relevant for visual attention were derived from independent component analysis of rs-fMRI data: visual, executive control, right and left frontoparietal, and ventral and dorsal attention networks. Two TVA parameters were mapped on particular functional networks. First, participants with higher (vs. lower) visual processing speed showed lower functional connectivity within the ventral attention network. Second, participants with more (vs. less) efficient top-down control showed higher functional connectivity within the dorsal attention network and lower functional connectivity within the visual network. Additionally, higher performance was associated with higher functional connectivity between networks: specifically, between the ventral attention and right frontoparietal networks for visual processing speed, and between the visual and executive control networks for top-down control. The higher inter-network functional connectivity was related to lower intra-network connectivity. These results demonstrate that separable visual attention parameters that are assumed to constitute relatively stable traits correspond distinctly to the functional connectivity both within and between particular functional networks. This implies that individual differences in basic attention functions are represented by differences in the coherence of slowly fluctuating brain activity.

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The data shown below were collected from the profiles of 7 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 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 22%
Student > Master 8 16%
Student > Ph. D. Student 7 14%
Student > Bachelor 4 8%
Student > Doctoral Student 2 4%
Other 4 8%
Unknown 13 27%
Readers by discipline Count As %
Neuroscience 15 31%
Psychology 11 22%
Medicine and Dentistry 3 6%
Social Sciences 1 2%
Biochemistry, Genetics and Molecular Biology 1 2%
Other 1 2%
Unknown 17 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 27 June 2022.
All research outputs
#6,356,438
of 22,757,090 outputs
Outputs from Frontiers in Human Neuroscience
#2,691
of 7,138 outputs
Outputs of similar age
#114,448
of 331,837 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#63
of 149 outputs
Altmetric has tracked 22,757,090 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 7,138 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.5. This one has gotten more attention than average, scoring higher than 61% 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 331,837 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 149 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 57% of its contemporaries.