Age differences in the intrinsic functional connectivity of default network subsystems

Campbell, Karen L.; Grigg, Omer; Saverino, Cristina; Churchill, Nathan W.; Grady, Cheryl L.

doi:10.3389/fnagi.2013.00073

Cited by 106 publications

(113 citation statements)

References 82 publications

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“…Where such outliers co-occurred (never more than 5% of the total volumes) we removed the fMRI volumes and replaced them with values interpolated with cubic splines. As reported by Campbell et al, (2013), this …”

supporting

confidence: 80%

“…As motion has been demonstrated to affect brain activity measures, even after standard correction procedures (e.g. Power et al, 2012), we followed a motion-scrubbing procedure described in Campbell et al, 2013. Briefly, this procedure uses a multivariate technique to identify outliers in both the motion-parameter estimates and fMRI signal itself.…”

Section: Fmri Data Acquisitionmentioning

confidence: 99%

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Timing is everything: Age differences in the cognitive control network are modulated by time of day.

Anderson¹,

Campbell²,

Amer³

et al. 2014

Psychology and Aging

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Current behavioral evidence suggests that attention regulation in humans varies with a circadian arousal rhythm that is influenced by age. However it is not known whether functional BOLD activation also varies with performance across the day in older adults. We used fMRI to compare activity in the control network in older adults tested in the morning and older and younger adults tested in the afternoon. Using a 1-back task with simultaneously presented stimuli (words superimposed on pictures), we show that older adults tested in the morning are not only more able to ignore the unattended stimulus than older adults in the afternoon, but activate similar cognitive control regions to young adults (rostral prefrontal and superior parietal cortex). We conclude that time of day modulates task-related fMRI signal in older adults and that age differences are reduced when older adults are tested at peak times of day. Keywordstime of day; circadian arousal; aging; attention; cognitive control; distraction; implicit memory; control network There are well known circadian fluctuations in cognitive alertness Yoon et al., 1999;Paradee et al., 2005;Blatter and Cajochen, 2007;Murray et al., 2009), fluctuations measurable with paper and pencil inventories highly correlated with physiological arousal (Horne and Ostberg, 1976;Roenneberg et al., 2003;Zavada et al., 2005). Additionally, there are age and individual differences in alertness patterns, such that the majority of older adults are shifted towards morningness, with younger adults falling into neutral and evening type ranges of alertness. Similar effects have also been demonstrated in animal studies which report robust age by synchrony interactions for arousal and memory Hasher, 1999, 2002 CIHR Author Manuscript CIHR Author Manuscript CIHR Author ManuscriptConcerning cognitive functioning, there is a substantial literature showing a synchrony effect (May et al., 1993;May and Hasher, 1998) such that performance, particularly on tasks requiring effortful (top-down) executive control or attention regulation are best performed at one's better times of day (May and Hasher, 1998;May, 1999;Yoon et al., 1999; Hasher et al., 2005;Ramírez et al., 2006Ramírez et al., , 2012Goldstein et al., 2007;Rowe et al., 2009; Hahn et al., 2012;Lehmann et al., 2013).Despite a rich behavioral literature, the influence of circadian rhythms and time of testing is largely unexplored in the neuroimaging literature and what research there is has focused on young adults (e.g. Marek et al., 2010) showing time of day differences in the ability to regulate strong but incorrect responses in the orienting attentional network -a division of the task-positive network that regulates where and when attention is directed in response to external cues (Schmidt et al., 2012).These findings are suggestive for young adults but an open and critical question is the impact of different times of testing for older adults -whose behavioral data shows substantially larger fluctuations, including in regulation of di...

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supporting

confidence: 80%

Section: Fmri Data Acquisitionmentioning

confidence: 99%

Timing is everything: Age differences in the cognitive control network are modulated by time of day.

Anderson¹,

Campbell²,

Amer³

et al. 2014

Psychology and Aging

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“…However, elevated connectivity has been observed for the HC in individuals at genetic risk for AD (23,24) and for elderly with memory complaints (25). Furthermore, a trend toward elevated functional connectivity for the medial temporal lobe (MTL) subsystem was observed in healthy older adults (26). Critically, higher subcortical RSN connectivity was found to correlate negatively with EM performance in an aging sample (27).…”

mentioning

confidence: 99%

Elevated hippocampal resting-state connectivity underlies deficient neurocognitive function in aging

Salami

Pudas

Nyberg

2014

Proc. Natl. Acad. Sci. U.S.A.

168

170

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The brain is not idle during rest. Functional MRI (fMRI) studies have identified several resting-state networks, including the default mode network (DMN), which contains a set of cortical regions that interact with a hippocampus (HC) subsystem. Age-related alterations in the functional architecture of the DMN and HC may influence memory functions and possibly constitute a sensitive biomarker of forthcoming memory deficits. However, the exact form of DMN-HC alterations in aging and concomitant memory deficits is largely unknown. Here, using both task and resting data from 339 participants (25-80 y old), we have demonstrated agerelated decrements in resting-state functional connectivity across most parts of the DMN, except for the HC network for which agerelated elevation of connectivity between left and right HC was found along with attenuated HC-cortical connectivity. Elevated HC connectivity at rest, which was partly accounted for by age-related decline in white matter integrity of the fornix, was associated with lower cross-sectional episodic memory performance and declining longitudinal memory performance over 20 y. Additionally, elevated HC connectivity at rest was associated with reduced HC neural recruitment and HC-cortical connectivity during active memory encoding, which suggests that strong HC connectivity restricts the degree to which the HC interacts with other brain regions during active memory processing revealed by task fMRI. Collectively, our findings suggest a model in which age-related disruption in cortico-hippocampal functional connectivity leads to a more functionally isolated HC at rest, which translates into aberrant hippocampal decoupling and deficits during mnemonic processing.hippocampus | DMN | resting state | episodic memory | aging T he brain is not idle at rest (1). Rather, intrinsic neuronal signaling, which manifests as spontaneous fluctuations in the blood oxygen level-dependent (BOLD) functional MRI (fMRI) signal, is ubiquitous in the human brain and consumes a substantial portion of the brain's energy (2). Coherent spontaneous activity has been revealed in a hierarchy of networks that span large-scale functional circuits in the brain (3-6). These resting-state networks (RSNs) show moderate-to-high test-retest reliability (7) and replicability (8), and some have been found in the monkey (9) and infant (10) brain. In the adult human brain, RSNs include sensory motor, visual, attention, and mnemonic networks, as well as the default mode network (DMN). There is evidence that the DMN entails interacting subsystems and hubs that are implicated in episodic memory (11-13). One major hub encompasses the posterior cingulate cortex and the retrosplenial cortex. Other hubs include the lateral parietal cortex and the medial prefrontal cortex. In addition, a hippocampus (HC) subsystem is distinct from, yet interrelated with, the major cortical DMN hubs (12,14).The functional architecture of the DMN and other RSNs is affected by different conditions, such as Alzheimer's disease (AD), Parkinson...

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“…The function of this averaging process was to further minimize temporal noise (Grigg & Grady, 2010). Previous research has shown that such 10-s long blocks are adequate for performing seed-based connectivity analyses (Campbell et al, 2013;Grigg & Grady, 2010). In all the reported analyses, the significance of each LV was determined using a permutation test with 500 permutations (McIntosh & Lobaugh, 2004).…”

mentioning

confidence: 99%

Inter-individual differences in the experience of negative emotion predict variations in functional brain architecture

Petrican¹,

Saverino

Rosenbaum

et al. 2015

NeuroImage

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Current evidence suggests that two spatially distinct neuroanatomical networks, the dorsal attention network (DAN) and the default mode network (DMN), support externally and internally oriented cognition, respectively, and are functionally regulated by a third, frontoparietal control network (FPC). Interactions among these networks contribute to normal variations in cognitive functioning and to the aberrant affective profiles present in certain clinical conditions, such as major depression. Nevertheless, their links to non-clinical variations in affective functioning are still poorly understood. To address this issue, we used fMRI to measure the intrinsic functional interactions among these networks in a sample of predominantly younger women (N = 162) from the Human Connectome Project. Consistent with the previously documented dichotomous motivational orientations (i.e., withdrawal versus approach) associated with sadness versus anger, we hypothesized that greater sadness would predict greater DMN (rather than DAN) functional dominance, whereas greater anger would predict the opposite. Overall, there was evidence of greater DAN (rather than DMN) functional dominance, but this pattern was modulated by current experience of specific negative emotions, as well as subclinical depressive and anxiety symptoms. Thus, greater levels of currently experienced sadness and subclinical depression independently predicted weaker DAN functional dominance (i.e., weaker DAN-FPC functional connectivity), likely reflecting reduced goal-directed attention towards the external perceptual environment. Complementarily, greater levels of currently experienced anger and subclinical anxiety predicted greater DAN functional dominance (i.e., greater DAN-FPC functional connectivity and, for anxiety only, also weaker DMN-FPC coupling). Our findings suggest that distinct affective states Negative mood states foster internally oriented attention and perceptual decoupling from the here-and-now (Smallwood, O'Connor, Sudbery, & Obonsawin, 2007;Smallwood, Fitzgerald, Miles, & Phillips, 2009). Nevertheless, the neural signature and unique contribution of distinct negative emotions to this effect of mood on engagement with the external world have not been identified despite their significance to both normal and pathological variations in emotional functioning. To address this issue, the present research capitalized on existing evidence that the human brain is organized into dissociable anatomical networks (Fox & Raichle, 2007), which provide a latent functional architecture that is readily recruited during goal-directed cognition (Laird et al., 2011;Smith et al., 2009). Importantly, recent investigations have documented the key role that these intrinsic functional networks play in supporting not only cognitive, but also affective processes (i.e., emotion experience and perception, cf. Touroutoglou, Lindquist, Dickerson, & Barrett, in press), including those observed during experimentally induced variations in mood states (e.g., sadness, Harri...

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Age differences in the intrinsic functional connectivity of default network subsystems

Cited by 106 publications

References 82 publications

Timing is everything: Age differences in the cognitive control network are modulated by time of day.

Timing is everything: Age differences in the cognitive control network are modulated by time of day.

Elevated hippocampal resting-state connectivity underlies deficient neurocognitive function in aging

Inter-individual differences in the experience of negative emotion predict variations in functional brain architecture

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