Decreased Functional Connectivity by Aging Is Associated with Cognitive Decline

Onoda, Keiichi; Ishihara, Masaki; Yamaguchi, Shûhei

doi:10.1162/jocn_a_00269

Cited by 292 publications

(300 citation statements)

References 61 publications

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“…In contrast, during EM and SM trials, the aIFO seeds were functionally connected with premotor and temporal areas. It is not clear what type of mechanism this pattern reflects, but it may indicate that different search processes are engaged when participants struggle to retrieve a non-personal memory.We found no evidence for age differences in the strength of functional connectivity within the core SLN, either during the incorrect trials or in the estimate of intrinsic functional connectivity, although a number of studies have reported such age differences (Allen et al, 2011; Geerligs et al, in press;He et al, 2014;Meier et al, 2012;Onoda et al, 2012;Tomasi and Volkow, 2012). Although we did not find age differences in the primary pattern of connectivity within the SLN, we did see reductions in the strength of connectivity between the aIFO seeds and regions outside the SLN, as well as a lack of task-specificity in the pattern of connectivity across the three memory conditions in older adults.…”

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confidence: 69%

“…Age differences in functional connectivity have been examined extensively for the default network (e.g., Andrews-Hanna et al, 2007;Damoiseaux et al, 2008;Grady et al, 2012), and to some extent for other brain networks (Allen et al, 2011;Campbell et al, 2012;Onoda et al, 2012;Rieckmann et al, 2011;Thomas et al, 2013;Tomasi and Volkow, 2012;Voss et al, 2010). Weaker functional connectivity has been reported specifically within the SLN or in SLN nodes in older adults (Allen et al, 2011;Geerligs et al, in press;He et al, 2014;Meier et al, 2012;Onoda et al, 2012;Tomasi and Volkow, 2012), leading us to predict age-related reductions in SLN functional connectivity in our results, although connectivity within the striatum, a node of the SLN, has been shown to increase with age (Allen et al, 2011;Tomasi and Volkow, 2012;Wang et al, 2012). However, most of these earlier studies examined resting-state functional connectivity, and it is unclear whether similar age reductions would be found during our tasks, on which there were no age differences in overall accuracy or response times (St-Laurent et al, 2011).…”

Section: The Current Studymentioning

confidence: 99%

“…These analyses were done to examine whether the regions active for incorrect responses also showed correlated activity, i.e., could be considered an integrated network of regions, and whether there were any age differences in functional connectivity. As seeds we chose the right and left aIFO as representative nodes of the SLN (Onoda et al, 2012;Seeley et al, 2007), and because these regions were more active for incorrect than for correct responses (see Figure 2). For these analyses, both young and older groups were entered, so that age differences could be assessed.…”

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confidence: 99%

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Age differences in brain activity related to unsuccessful declarative memory retrieval

2015

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Although memory recall is known to be reduced with normal aging, little is known about the patterns of brain activity that accompany these recall failures. By assessing faulty memory, we can identify the brain regions engaged during retrieval attempts in the absence of successful memory and determine the impact of aging on this functional activity. We used functional magnetic resonance imaging to examine age differences in brain activity associated with memory failure in three memory retrieval tasks: autobiographical (AM), episodic (EM) and semantic (SM). Compared to successful memory retrieval, both age groups showed more activity when they failed to recall a memory in regions consistent with the salience network (SLN), a brain network also associated with non-memory errors. Both groups also showed strong functional coupling among SLN regions during incorrect trials and in intrinsic patterns of functional connectivity. In comparison to young adults, older adults demonstrated (1) less activity within the SLN during unsuccessful AM trials; (2) weaker intrinsic functional connectivity between SLN nodes and dorsolateral prefrontal cortex; and (3) less differentiation of SLN functional connectivity during incorrect trials across memory conditions. These results suggest that the SLN is engaged during recall failures, as it is for non-memory errors, which may be because errors in general have particular salience for adapting behavior. In older adults, the dedifferentiation of functional connectivity within the SLN across memory conditions and the reduction of functional coupling between it and prefrontal cortex may indicate poorer internetwork communication and less flexible use of cognitive control processes, either while retrieval is attempted or when monitoring takes place after retrieval has failed. Keywords fMRI; aging; episodic memory; salience network; frontal lobe IntroductionA number of studies have provided extensive evidence of the neural circuitry that supports memory retrieval (e.g., Cabeza and Nyberg, 2000;Spaniol et al., 2009 CIHR Author Manuscript CIHR Author Manuscript CIHR Author Manuscript2008), as well as evidence of how aging influences this circuitry (e.g., Cabeza et al., 2005;Grady, 2012;Rajah and D'Esposito, 2005). However, most research has investigated how the brain supports successful memory performance (Addis and McAndrews, 2006;Brewer et al., 1998;Morcom et al., 2003;Wagner et al., 1998), and limited attention has been paid to brain networks involved in faulty memory retrieval, most notably faulty long-term memory recall. A number of processes may be engaged during recall, including goal setting, memory search, accessing (hopefully correct) stored memories, and evaluating retrieval success (Henson et al., 1999;Moscovitch, 1992;Rugg et al., 2002). The assessment of faulty memory retrieval can be used to identify brain regions whose activity reflects processes engaged when retrieval fails. Such processes can include cognitive control processes involved regardless of retrieval succes...

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confidence: 69%

Section: The Current Studymentioning

confidence: 99%

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confidence: 99%

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Age differences in brain activity related to unsuccessful declarative memory retrieval

2015

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“…However, the energy probabilities of the visual network declined, while the energy probabilities of the default, frontoparietal, and limbic networks decreased further. This result may be consistent with the further enhanced heterogeneity of whole-brain functional subsystems [60][61][62][63][64][65]. The values of EP in the brain regions of the frontoparietal network increased slightly.…”

Section: The Orderness Variability Of Functional Subsystems With Agesupporting

confidence: 82%

Lifespan Development of the Human Brain Revealed by Large-Scale Network Eigen-Entropy

Fan

Zeng

Shen

et al. 2017

Entropy

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Abstract:Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying functional connectivity patterns of the developing and aging brain. Normal brain development is characterized by continuous and significant network evolution through infancy, childhood, and adolescence, following specific maturational patterns. Normal aging is related to some resting state brain networks disruption, which are associated with certain cognitive decline. It is a big challenge to design an integral metric to track connectome evolution patterns across the lifespan, which is to understand the principles of network organization in the human brain. In this study, we first defined a brain network eigen-entropy (NEE) based on the energy probability (EP) of each brain node. Next, we used the NEE to characterize the lifespan orderness trajectory of the whole-brain functional connectivity of 173 healthy individuals ranging in age from 7 to 85 years. The results revealed that during the lifespan, the whole-brain NEE exhibited a significant non-linear decrease and that the EP distribution shifted from concentration to wide dispersion, implying orderness enhancement of functional connectome over age. Furthermore, brain regions with significant EP changes from the flourishing (7-20 years) to the youth period (23-38 years) were mainly located in the right prefrontal cortex and basal ganglia, and were involved in emotion regulation and executive function in coordination with the action of the sensory system, implying that self-awareness and voluntary control performance significantly changed during neurodevelopment. However, the changes from the youth period to middle age (40-59 years) were located in the mesial temporal lobe and caudate, which are associated with long-term memory, implying that the memory of the human brain begins to decline with age during this period. Overall, the findings suggested that the human connectome shifted from a relatively anatomical driven state to an orderly organized state with lower entropy.

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“…These three neural networks are central to cognition, as they are engaged in a large number of functions, and their disruption has been associated with a variety of clinical syndromes, such as schizophrenia, traumatic brain injury, and Alzheimer's disease (Manoliu et al, 2014;Sharp et al, 2014;Zhou et al, 2010). In addition, evidence suggests that the disruption of the dynamic coordination of these large-scale networks constitutes one of the main causes of cognitive decline associated with ageing (Andrews-Hanna et al, 2007;Sambataro et al, 2010), as shown by reduced neural activity in the DMN and SN at rest (Allen et al, 2011;Onoda et al, 2012) and RESTING STATE NETWORKS IN THE AGEING BRAIN 4 increased activity in the FPN of older adults during visual tasks .…”

Section: Introductionmentioning

confidence: 99%

Aging and large-scale functional networks: White matter integrity, gray matter volume, and functional connectivity in the resting state

et al. 2015

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Healthy ageing is accompanied by neurobiological changes that affect the brain's functional organization and the individual's cognitive abilities. The aim of this study was to investigate the effect of global age-related differences in the cortical white and gray matter on neural activity in three key large-scale networks. We used functionalstructural covariance network analysis to assess resting state activity in the default mode network (DMN), the fronto-parietal network (FPN), and the salience network show that, in the direct comparison of resting state activity, young but not older adults reliably engage the SN and FPN in addition to the DMN, suggesting that older adults recruit these networks less consistently. Second, our results demonstrate that agerelated decline in white matter integrity and gray matter volume is associated with activity in prefrontal nodes of the SN and FPN, possibly reflecting compensatory mechanisms. We suggest that age-related differences in gray and white matter properties differentially affect the ability of the brain to engage and coordinate largescale functional networks that are central to efficient cognitive functioning.

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Decreased Functional Connectivity by Aging Is Associated with Cognitive Decline

Cited by 292 publications

References 61 publications

Age differences in brain activity related to unsuccessful declarative memory retrieval

Age differences in brain activity related to unsuccessful declarative memory retrieval

Lifespan Development of the Human Brain Revealed by Large-Scale Network Eigen-Entropy

Aging and large-scale functional networks: White matter integrity, gray matter volume, and functional connectivity in the resting state

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