Age differences in the functional interactions among the default, frontoparietal control, and dorsal attention networks

Grady, Cheryl L.; Sarraf, Saman; Saverino, Cristina; Campbell, Karen L.

doi:10.1016/j.neurobiolaging.2016.02.020

Cited by 313 publications

(331 citation statements)

References 106 publications

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“…Similar patterns of network differentiation with age have been reported in a more circumscribed set of brain networks, including the default, dorsal attention and frontal parietal control networks both during task and at rest [122,123]. Specific changes include reduced anticorrelations between dorsal attention and default networks and increased network interactions across all three networks, consistent with a network dedifferentiation account.…”

Section: Changes In Functional Brain Networksupporting

confidence: 69%

“…Age-related changes include reduced suppression [112,116,117] and decreased within-network connectivity during both task [110,113,118] and rest [108,109,119,120]. Recent evidence also suggests that the default network is more functionally connected to other brain networks in aging [113,114,[119][120][121][122] and this connectivity is poorly modulated by task context [96,97,[122][123][124].…”

Section: Changes In Functional Brain Networkmentioning

confidence: 99%

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Structure and function of the aging brain

Spreng¹,

Turner²

2018

Preprint

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In this opening section of the Aging Brain we set the stage for the contributions that follow by providing a broad overview of the latest advances in our understanding of how the brain changes, both structurally and functionally, across the adult lifespan. We leave domain-specific aspects of brain aging to the subsequent chapters, where contributors will provide more targeted accounts of brain change germane to their particular focus on the aging brain. Here we review the extant, and rapidly expanding literature to provide a brief overview and introduction to structural and functional change that occur with typical brain aging. We begin the chapter by looking back, to review some of the early discoveries about how the brain changes across the adult lifespan. We close the chapter by looking forward, towards new discoveries that challenge our core assumptions about the inevitability or irreversibility of age-related brain changes. These sections serve as bookends for the core of the chapter where we review the latest research advances that continue to uncover the mysteries of the aging brain. Spreng, R.N., Turner, G.R. (2019, forthcoming) Structure and function of the aging brain. In G Samanez-Larkin (Ed.) The aging brain. Washington DC: American Psychological Association.

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Section: Changes In Functional Brain Networksupporting

confidence: 69%

Section: Changes In Functional Brain Networkmentioning

confidence: 99%

Structure and function of the aging brain

Spreng¹,

Turner²

2018

Preprint

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“…Additionally, reductions in task-related default network suppression and altered FC have been observed with advancing age (Andrews-Hanna et al, 2007; Damoiseaux et al, 2008; Grady et al, 2010; Hafkemeijer, van der Grond, & Rombouts, 2012; Sala-Llonch et al, 2012; Sambataro et al, 2010; Stevens, Hasher, Chiew, & Grady, 2008; Turner & Spreng, 2015). These findings complement whole brain resting-state FC (RSFC) observations of a dedifferentiation of network connectivity with age, with increases in RSFC between large-scale brain systems in older adults (Betzel et al, 2014; Chan, Park, Savalia, Petersen, & Wig, 2014; Geerligs, Renken, Saliasi, Maurits, & Lorist, 2015; Grady, Sarraf, Saverino, & Campbell, 2016; Meunier, Achard, Morcom, & Bullmore, 2009; Onoda & Yamaguchi, 2013). It is unclear, however, if the robust pattern of anticorrelated activity between the default and dorsal attention networks is preserved into older adulthood.…”

Section: Introductionsupporting

confidence: 70%

“…Chan et al (2014) observed increased correlations between default and dorsal attention networks as one feature of a larger pattern of reduced network segregation in older adulthood (see also, Grady et al, 2016). However age-related changes in anticorrelation between networks were not investigated in this study.…”

Section: Introductionmentioning

confidence: 90%

Attenuated anticorrelation between the default and dorsal attention networks with aging: evidence from task and rest

Spreng

Stevens

Viviano

et al. 2016

Neurobiology of Aging

211

166

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Anticorrelation between the default and dorsal attention networks is a central feature of human functional brain organization. Hallmarks of aging include impaired default network modulation and declining medial temporal lobe (MTL) function. However, it remains unclear if this anticorrelation is preserved into older adulthood during task performance, or how this is related to the intrinsic architecture of the brain. We hypothesized that older adults would show reduced within- and increased between-network functional connectivity (FC) across the default and dorsal attention networks. To test this hypothesis, we examined the effects of aging on task-related and intrinsic FC using fMRI during an autobiographical planning task known to engage the default network and during rest, respectively, with young (n=72) and older (n=79) participants. The task-related FC analysis revealed reduced anticorrelation with aging. At rest, there was a robust double dissociation, with older adults showing a pattern of reduced within-network FC, but increased between-network FC, across both networks, relative to young adults. Moreover, older adults showed reduced intrinsic resting-state FC of the MTL with both networks suggesting a fractionation of the MTL memory system in healthy aging. These findings demonstrate age-related dedifferentiation among these competitive large-scale networks during both task and rest, consistent with the idea that age-related changes are associated with a breakdown in the intrinsic functional architecture within and among large-scale brain networks.

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“…The unique feature of graph-theoretical analysis, compared with the more traditional univariate neuroimaging approaches, is that it can directly test the differences in topological parameters of the brain network such as small-worldness, modularity, highly connected regions (hubs), and regional network parameters. [32]. Hosseini et al has developed a GAT: Graph Analysis Toolbox available at: https://www.nitrc.org/projects/gat/.…”

mentioning

confidence: 99%