Ageing and the resting state: is cognition obsolete?

Campbell, Karen L.; Schacter, Daniel L.

doi:10.1080/23273798.2016.1227858

Cited by 48 publications

(42 citation statements)

References 98 publications

(108 reference statements)

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“…Reliable age-related differences have been observed across a number of neuroimaging modalities (Campbell and Schacter, 2017). On the basis of these and other studies reporting agerelated differences in microstates (i.e., Koenig et al, 2002;Tomescu et al, 2018), we also expected to find substantial age group differences in microstate dynamics.…”

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confidence: 67%

“…One important goal of this work is to determine whether intrinsic activity of coordinated brain networks can provide reliable predictors of psychological differences among people in healthy and clinical populations (Dubois and Adolphs, 2016). Aging and disease-related changes in cognitive function are presumed to manifest in structural and functional differences among brain networks (Campbell and Schacter, 2017). Understanding the scale and scope to which intrinsic brain network organization can encode stable, trait-like differences in motivation, affect, and cognition, long argued by personality theorists (e.g.…”

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confidence: 99%

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Within and Between-person Correlates of the Temporal Dynamics of Resting EEG Microstates

Zanesco

King

Skwara

et al. 2019

Preprint

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Microstates reflect transient brain states resulting from the activity of synchronously active brain networks that predominate in the broadband EEG time series. Despite increasing interest in understanding how the functional organization of the brain varies across individuals, or the extent to which its spatiotemporal dynamics are state dependent, comparatively little research has examined within and between-person correlates of microstate temporal parameters in healthy populations. In the present study, neuroelectric activity recorded during eyes-closed rest and during simple visual fixation was segmented into a time series of transient microstate intervals. It was found that five data-driven microstate configurations explained the preponderance of topographic variance in the EEG time series of the 374 recordings (from 187 participants) included in the study. We observed that the temporal dynamics of microstates varied within individuals to a greater degree than they differed between persons, with within-person factors explaining a large portion of the variance in mean microstate duration and occurrence rate.Nevertheless, several individual differences were found to predict the temporal dynamics of microstates. Of these, age and gender were the most reliable. These findings suggest that not only do the rich temporal dynamics of whole-brain neuronal networks vary considerably withinindividuals, but that microstates appear to differentiate persons based on trait individual differences. The current findings suggest that rather than focusing exclusively on between-person differences in microstates as measures of brain function, researchers should turn their attention towards understanding the factors contributing to within-person variation.

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confidence: 67%

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confidence: 99%

Within and Between-person Correlates of the Temporal Dynamics of Resting EEG Microstates

Zanesco

King

Skwara

et al. 2019

Preprint

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“…There have been criticisms that "resting state" is a poorly understood and uncontrolled set of mental operations that can vary considerably across participants (Buckner, Krienen, & Yeo, 2013;Campbell & Schacter, 2017) which implies that this may have little clinical value.…”

Section: Discussionmentioning

confidence: 99%

Language network measures at rest indicate individual differences in naming decline after anterior temporal lobe resection

Audrain

Barnett

McAndrews

2018

Human Brain Mapping

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While anterior temporal lobe (ATL) resection is an effective treatment for temporal lobe epilepsy, surgery on the dominant hemisphere is associated with variable decline in confrontation naming. Accurate prediction of naming impairment is critical to inform clinical decision making, and while there has been some degree of success using task-based functional MRI (fMRI) paradigms, there remains a growing interest in the predictive utility of resting-state connectivity as it allows for relatively shorter scans with low task demands. Our objective was to assess the relationship between measures of preoperative resting-state connectivity and postoperative naming change in patients following left ATL resection. We compared the resting language network connectivity of each patient to a normative healthy control template using a novel measure called "matrix similarity," and found that patients with more abnormal global language-network connectivity-particularly of regions spared from surgery-showed greater postoperative naming decline than those with normative patterns of connectivity. When we interrogated the degree centrality of to-be-resected regions in a more targeted approach of the pathological temporal lobe, we found that greater functional integration of those regions with the rest of the language network at rest was related to greater decline in naming following surgery. Finally, we found that matrix similarity was a better predictor of postoperative outcome than degree within to-be-resected regions, network clustering, modularity, and language task fMRI laterality. We provide some of the first evidence that using this novel measure, a relatively short preoperative resting scan can be exploited to inform naming ability following ATL resection.

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“…The functional role of modules is especially important in the study of cognitive aging because of preliminary evidence, predominantly from resting-state functional connectivity analyses, indicating that with increased age, modules become less segregated and that this decreased segregation may have cognitive consequences (Betzel et al, 2014; Cao et al, 2014; Chan et al, 2014; Onoda and Yamaguchi, 2013; Song et al, 2014). However, since resting-state functional connectivity may not correspond to task-based connectivity (Campbell and Schacter, 2016; Cohen and D’Esposito, 2016; Davis et al, 2016), these studies do not inform how the modular topology of the brain adapts to cognitive demands of the environment. Task-based functional connectivity analyses, therefore, are necessary.…”

Section: 0 Introductionmentioning

confidence: 99%

Functional modular architecture underlying attentional control in aging

et al. 2017

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Previous research suggests that age-related differences in attention reflect the interaction of top-down and bottom-up processes, but the cognitive and neural mechanisms underlying this interaction remain an active area of research. Here, within a sample of community-dwelling adults 19–78 years of age, we used diffusion reaction time (RT) modeling and multivariate functional connectivity to investigate the behavioral components and whole-brain functional networks, respectively, underlying bottom-up and top-down attentional processes during conjunction visual search. During functional MRI scanning, participants completed a conjunction visual search task in which each display contained one item that was larger than the other items (i.e., a size singleton) but was not informative regarding target identity. This design allowed us to examine in the RT components and functional network measures the influence of (a) additional bottom-up guidance when the target served as the size singleton, relative to when the distractor served as the size singleton (i.e., size singleton effect) and (b) top-down processes during target detection (i.e., target detection effect; target present vs. absent trials). We found that the size singleton effect (i.e., increased bottom-up guidance) was associated with RT components related to decision and nondecision processes, but these effects did not vary with age. Also, a modularity analysis revealed that frontoparietal module connectivity was important for both the size singleton and target detection effects, but this module became central to the networks through different mechanisms for each effect. Lastly, participants 42 years of age and older, in service of the target detection effect, relied more on between-frontoparietal module connections. Our results further elucidate mechanisms through which frontoparietal regions support attentional control and how these mechanisms vary in relation to adult age.

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Ageing and the resting state: is cognition obsolete?

Cited by 48 publications

References 98 publications

Within and Between-person Correlates of the Temporal Dynamics of Resting EEG Microstates

Within and Between-person Correlates of the Temporal Dynamics of Resting EEG Microstates

Language network measures at rest indicate individual differences in naming decline after anterior temporal lobe resection

Functional modular architecture underlying attentional control in aging

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