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Resting-State Network Topology Differentiates Task Signals across the Adult Life Span

Brain network connectivity differs across individuals. For example, older adults exhibit less segregated resting-state subnetworks relative to younger adults (Chan et al., 2014). It has been hypothesized that individual differences in network connectivity impact the recruitment of brain areas during...

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Autores principales: Chan, Micaela Y., Alhazmi, Fahd H., Park, Denise C., Savalia, Neil K., Wig, Gagan S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society for Neuroscience 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5354325/
https://www.ncbi.nlm.nih.gov/pubmed/28174333
http://dx.doi.org/10.1523/JNEUROSCI.2406-16.2017
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author Chan, Micaela Y.
Alhazmi, Fahd H.
Park, Denise C.
Savalia, Neil K.
Wig, Gagan S.
author_facet Chan, Micaela Y.
Alhazmi, Fahd H.
Park, Denise C.
Savalia, Neil K.
Wig, Gagan S.
author_sort Chan, Micaela Y.
collection PubMed
description Brain network connectivity differs across individuals. For example, older adults exhibit less segregated resting-state subnetworks relative to younger adults (Chan et al., 2014). It has been hypothesized that individual differences in network connectivity impact the recruitment of brain areas during task execution. While recent studies have described the spatial overlap between resting-state functional correlation (RSFC) subnetworks and task-evoked activity, it is unclear whether individual variations in the connectivity pattern of a brain area (topology) relates to its activity during task execution. We report data from 238 cognitively normal participants (humans), sampled across the adult life span (20–89 years), to reveal that RSFC-based network organization systematically relates to the recruitment of brain areas across two functionally distinct tasks (visual and semantic). The functional activity of brain areas (network nodes) were characterized according to their patterns of RSFC: nodes with relatively greater connections to nodes in their own functional system (“non-connector” nodes) exhibited greater activity than nodes with relatively greater connections to nodes in other systems (“connector” nodes). This “activation selectivity” was specific to those brain systems that were central to each of the tasks. Increasing age was accompanied by less differentiated network topology and a corresponding reduction in activation selectivity (or differentiation) across relevant network nodes. The results provide evidence that connectional topology of brain areas quantified at rest relates to the functional activity of those areas during task. Based on these findings, we propose a novel network-based theory for previous reports of the “dedifferentiation” in brain activity observed in aging. SIGNIFICANCE STATEMENT Similar to other real-world networks, the organization of brain networks impacts their function. As brain network connectivity patterns differ across individuals, we hypothesized that individual differences in network connectivity would relate to differences in brain activity. Using functional MRI in a group of individuals sampled across the adult life span (20–89 years), we measured correlations at rest and related the functional connectivity patterns to measurements of functional activity during two independent tasks. Brain activity varied in relation to connectivity patterns revealed by large-scale network analysis. This relationship tracked the differences in connectivity patterns accompanied by older age, providing important evidence for a link between the topology of areal connectivity measured at rest and the functional recruitment of these areas during task performance.
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spelling pubmed-53543252017-03-17 Resting-State Network Topology Differentiates Task Signals across the Adult Life Span Chan, Micaela Y. Alhazmi, Fahd H. Park, Denise C. Savalia, Neil K. Wig, Gagan S. J Neurosci Research Articles Brain network connectivity differs across individuals. For example, older adults exhibit less segregated resting-state subnetworks relative to younger adults (Chan et al., 2014). It has been hypothesized that individual differences in network connectivity impact the recruitment of brain areas during task execution. While recent studies have described the spatial overlap between resting-state functional correlation (RSFC) subnetworks and task-evoked activity, it is unclear whether individual variations in the connectivity pattern of a brain area (topology) relates to its activity during task execution. We report data from 238 cognitively normal participants (humans), sampled across the adult life span (20–89 years), to reveal that RSFC-based network organization systematically relates to the recruitment of brain areas across two functionally distinct tasks (visual and semantic). The functional activity of brain areas (network nodes) were characterized according to their patterns of RSFC: nodes with relatively greater connections to nodes in their own functional system (“non-connector” nodes) exhibited greater activity than nodes with relatively greater connections to nodes in other systems (“connector” nodes). This “activation selectivity” was specific to those brain systems that were central to each of the tasks. Increasing age was accompanied by less differentiated network topology and a corresponding reduction in activation selectivity (or differentiation) across relevant network nodes. The results provide evidence that connectional topology of brain areas quantified at rest relates to the functional activity of those areas during task. Based on these findings, we propose a novel network-based theory for previous reports of the “dedifferentiation” in brain activity observed in aging. SIGNIFICANCE STATEMENT Similar to other real-world networks, the organization of brain networks impacts their function. As brain network connectivity patterns differ across individuals, we hypothesized that individual differences in network connectivity would relate to differences in brain activity. Using functional MRI in a group of individuals sampled across the adult life span (20–89 years), we measured correlations at rest and related the functional connectivity patterns to measurements of functional activity during two independent tasks. Brain activity varied in relation to connectivity patterns revealed by large-scale network analysis. This relationship tracked the differences in connectivity patterns accompanied by older age, providing important evidence for a link between the topology of areal connectivity measured at rest and the functional recruitment of these areas during task performance. Society for Neuroscience 2017-03-08 /pmc/articles/PMC5354325/ /pubmed/28174333 http://dx.doi.org/10.1523/JNEUROSCI.2406-16.2017 Text en Copyright © 2017 Chan et al. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.
spellingShingle Research Articles
Chan, Micaela Y.
Alhazmi, Fahd H.
Park, Denise C.
Savalia, Neil K.
Wig, Gagan S.
Resting-State Network Topology Differentiates Task Signals across the Adult Life Span
title Resting-State Network Topology Differentiates Task Signals across the Adult Life Span
title_full Resting-State Network Topology Differentiates Task Signals across the Adult Life Span
title_fullStr Resting-State Network Topology Differentiates Task Signals across the Adult Life Span
title_full_unstemmed Resting-State Network Topology Differentiates Task Signals across the Adult Life Span
title_short Resting-State Network Topology Differentiates Task Signals across the Adult Life Span
title_sort resting-state network topology differentiates task signals across the adult life span
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5354325/
https://www.ncbi.nlm.nih.gov/pubmed/28174333
http://dx.doi.org/10.1523/JNEUROSCI.2406-16.2017
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