Cerebral blood flow predicts multiple demand network activity and fluid intelligence across the lifespan

Wu, Shuyi; Tyler, Lorraine K.; Henson, Richard; Rowe, James B.; Cam‐CAN,; Tsvetanov, Kamen A.

doi:10.1101/2021.11.10.468042

Cited by 8 publications

(5 citation statements)

References 92 publications

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“…The discrepancy between studies may be in part due to methodological factors when investigating the effects of sleep on brain and cognitive function in healthy aging. First, the relations between sleep quality and the brain, as measured with fMRI, might be affected by age-dependent confounding factors like cerebrovascular reactivity and head motion (Power et al, 2012;Tsvetanov et al, 2015;Geerligs et al, 2017;Lehmann et al, 2017;Wu et al, 2021). While some of these confounds, like neurovascular coupling, can be addressed by more sophisticated modeling (Tsvetanov et al, 2021b), others like head-motion are notoriously difficult to correct (Maknojia et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

The “Neural Shift” of Sleep Quality and Cognitive Aging: A Resting-State MEG Study of Transient Neural Dynamics

Tibon

Tsvetanov

2022

Front. Aging Neurosci.

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Sleep quality changes dramatically from young to old age, but its effects on brain dynamics and cognitive functions are not yet fully understood. We tested the hypothesis that a shift in brain networks dynamics relates to sleep quality and cognitive performance across the lifespan. Network dynamics were assessed using Hidden Markov Models (HMMs) in resting-state MEG data from a large cohort of population-based adults (N = 564, aged 18–88). Using multivariate analyses of brain-sleep profiles and brain-cognition profiles, we found an age-related “neural shift,” expressed as decreased occurrence of “lower-order” brain networks coupled with increased occurrence of “higher-order” networks. This “neural shift” was associated with both increased sleep dysfunction and decreased fluid intelligence, and this relationship was not explained by age, sex or other covariates. These results establish the link between poor sleep quality, as evident in aging, and a behavior-related shift in neural dynamics.

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Section: Introductionmentioning

confidence: 99%

The “Neural Shift” of Sleep Quality and Cognitive Aging: A Resting-State MEG Study of Transient Neural Dynamics

Tibon

Tsvetanov

2022

Front. Aging Neurosci.

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“…ASL is a noninvasive MRI technique used to quantify cerebral blood perfusion by labeling blood water as it flows throughout the brain. Baseline CBF, which relates to cerebrovascular aging (Tsvetanov, Henson, Jones, et al, 2021 ), is important for maintaining cognitive function, while its non‐neuronal contributions to BOLD signals reflect age‐related confound (Wu et al, 2021 ). Another important aspect of cerebrovascular function is the ability to regulate regional blood flow via carbon dioxide‐modulated constriction or dilation of cerebral vessels (Willie et al, 2014 ).…”

Section: Introductionmentioning

confidence: 99%

Multimodal fusion analysis of functional, cerebrovascular and structural neuroimaging in healthy aging subjects

Liu,

Tyler,

Rowe

et al. 2022

Human Brain Mapping

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Brain aging is a complex process that requires a multimodal approach. Neuroimaging can provide insights into brain morphology, functional organization, and vascular dynamics. However, most neuroimaging studies of aging have focused on each imaging modality separately, limiting the understanding of interrelations between processes identified by different modalities and their relevance to cognitive decline in aging. Here, we used a data-driven multimodal approach, linked independent component analysis (ICA), to jointly analyze magnetic resonance imaging (MRI) of grey matter volume, cerebrovascular, and functional network topographies in relation to measures of fluid intelligence. Neuroimaging and cognitive data from the Cambridge Centre for Ageing and Neuroscience study were used, with healthy participants aged 18-88 years (main dataset n = 215 and secondary dataset n = 433). Using linked ICA, functional network activities were characterized in independent components but not captured in the same component as structural and cerebrovascular patterns.Split-sample (n = 108/107) and out-of-sample (n = 433) validation analyses using linked ICA were also performed. Global grey matter volume with regional cerebrovascular changes and the right frontoparietal network activity were correlated with agerelated and individual differences in fluid intelligence. This study presents the insights from linked ICA to bring together measurements from multiple imaging modalities, with independent and additive information. We propose that integrating multiple neuroimaging modalities allows better characterization of brain pattern variability and changes associated with healthy aging.

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“…Network connectivity is also associated with fluid intelligence ( Cole et al, 2012 ; Barbey, 2018 ; Dubois et al, 2018 ; Hilger et al, 2020 ) and changes with age ( Tsvetanov et al, 2016 ; Bethlehem et al, 2020 ). Lifespan differences in cerebral vascularization may further influence neural function and neurovascular coupling ( West et al, 2019 ; Tsvetanov et al, 2021 ), although blood flow variation explains relatively little covariance between age, BOLD response, and performance on this task ( Wu et al, 2021 ). Future work could usefully address the relative importance of multiple mediators, and the relationships between them ( Hedden et al, 2016 ).…”

Section: Discussionmentioning

confidence: 99%

Neural Contributions to Reduced Fluid Intelligence across the Adult Lifespan

Mitchell

Mousley²,

Shafto³

et al. 2022

J. Neurosci.

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Fluid intelligence, the ability to solve novel, complex problems, declines steeply during healthy human aging. Using fMRI, fluid intelligence has been repeatedly associated with activation of a frontoparietal brain network, and impairment following focal damage to these regions suggests that fluid intelligence depends on their integrity. It is therefore possible that age-related functional differences in frontoparietal activity contribute to the reduction in fluid intelligence. This paper reports on analysis of the Cambridge Center for Ageing and Neuroscience data, a large, population-based cohort of healthy males and females across the adult lifespan. The data support a model in which age-related differences in fluid intelligence are partially mediated by the responsiveness of frontoparietal regions to novel problem-solving. We first replicate a prior finding of such mediation using an independent sample. We then precisely localize the mediating brain regions, and show that mediation is specifically associated with voxels most activated by cognitive demand, but not with voxels suppressed by cognitive demand. We quantify the robustness of this result to potential unmodeled confounders, and estimate the causal direction of the effects. Finally, exploratory analyses suggest that neural mediation of age-related differences in fluid intelligence is moderated by the variety of regular physical activities, more reliably than by their frequency or duration. An additional moderating role of the variety of nonphysical activities emerged when controlling for head motion. A better understanding of the mechanisms that link healthy aging with lower fluid intelligence may suggest strategies for mitigating such decline.SIGNIFICANCE STATEMENTGlobal populations are living longer, driving urgency to understand age-related cognitive declines. Fluid intelligence is of prime importance because it reflects performance across many domains, and declines especially steeply during healthy aging. Despite consensus that fluid intelligence is associated with particular frontoparietal brain regions, little research has investigated suggestions that under-responsiveness of these regions mediates age-related decline. We replicate a recent demonstration of such mediation, showing specific association with brain regions most activated by cognitive demand, and robustness to moderate confounding by unmodeled variables. By showing that this mediation model is moderated by the variety of regular physical activities, more reliably than by their frequency or duration, we identify a potential modifiable lifestyle factor that may help promote successful aging.

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Cerebral blood flow predicts multiple demand network activity and fluid intelligence across the lifespan

Cited by 8 publications

References 92 publications

The “Neural Shift” of Sleep Quality and Cognitive Aging: A Resting-State MEG Study of Transient Neural Dynamics

The “Neural Shift” of Sleep Quality and Cognitive Aging: A Resting-State MEG Study of Transient Neural Dynamics

Multimodal fusion analysis of functional, cerebrovascular and structural neuroimaging in healthy aging subjects

Neural Contributions to Reduced Fluid Intelligence across the Adult Lifespan

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