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Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks

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 proces...

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Autores principales: Ruiz-Rizzo, Adriana L., Neitzel, Julia, Müller, Hermann J., Sorg, Christian, Finke, Kathrin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5890144/
https://www.ncbi.nlm.nih.gov/pubmed/29662444
http://dx.doi.org/10.3389/fnhum.2018.00089
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author Ruiz-Rizzo, Adriana L.
Neitzel, Julia
Müller, Hermann J.
Sorg, Christian
Finke, Kathrin
author_facet Ruiz-Rizzo, Adriana L.
Neitzel, Julia
Müller, Hermann J.
Sorg, Christian
Finke, Kathrin
author_sort Ruiz-Rizzo, Adriana L.
collection PubMed
description 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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spelling pubmed-58901442018-04-16 Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks Ruiz-Rizzo, Adriana L. Neitzel, Julia Müller, Hermann J. Sorg, Christian Finke, Kathrin Front Hum Neurosci Neuroscience 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. Frontiers Media S.A. 2018-03-12 /pmc/articles/PMC5890144/ /pubmed/29662444 http://dx.doi.org/10.3389/fnhum.2018.00089 Text en Copyright © 2018 Ruiz-Rizzo, Neitzel, Müller, Sorg and Finke. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Ruiz-Rizzo, Adriana L.
Neitzel, Julia
Müller, Hermann J.
Sorg, Christian
Finke, Kathrin
Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks
title Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks
title_full Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks
title_fullStr Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks
title_full_unstemmed Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks
title_short Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks
title_sort distinctive correspondence between separable visual attention functions and intrinsic brain networks
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5890144/
https://www.ncbi.nlm.nih.gov/pubmed/29662444
http://dx.doi.org/10.3389/fnhum.2018.00089
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