Aging and cerebrovascular health: Structural, functional, cognitive, and methodological implications

Fabiani, Monica; Gratton, Gabriele

doi:10.1111/psyp.13842

Cited by 7 publications

(4 citation statements)

References 69 publications

(53 reference statements)

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“…It suggests that variability of brain patterns in healthy aging subjects is better characterized by multiple independent components dominated by one of the structural, cerebrovascular, or functional network measurements but not captured in a single component reflecting all of these signals. This is contrary to our hypothesis that concordant changes on functional, structural, and cerebrovascular activities would be observed, as it is a common view that age‐related changes in vasculature, brain anatomy and brain function are a complex interplay that affects cognition (Fabiani et al, 2021 ; Zimmerman et al, 2021 ). Previous studies have also reported a correlation between brain functional and structural connectivity in healthy subjects (Horn et al, 2014 ; Vázquez‐Rodríguez et al, 2019 ).…”

Section: Discussioncontrasting

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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Section: Discussioncontrasting

confidence: 99%

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

Liu,

Tyler,

Rowe

et al. 2022

Human Brain Mapping

View full text Add to dashboard Cite

show abstract

“…It suggests that variability of brain patterns in healthy ageing subjects is better characterized by multiple independent components dominated by one of the structural, cerebrovascular or functional network measurements, but not captured in a single component reflecting all of these signals. This is contrary to our hypothesis that concordant changes on functional, structural and cerebrovascular activities would be observed, as it is a common view that age-related changes in vasculature, brain anatomy and brain function are a complex interplay that affects cognition (Fabiani, Rypma, & Gratton, 2021; Zimmerman et al, 2021). Previous studies have also reported a correlation between brain functional and structural connectivity in healthy subjects (Horn, Ostwald, Reisert, & Blankenburg, 2014; Vazquez-Rodriguez et al, 2019).…”

Section: Discussioncontrasting

confidence: 99%

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

Liu

Tyler

Rowe

et al. 2021

Preprint

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Cognitive ageing is a complex process which requires multimodal approach. Neuroimaging can provide insights into brain morphology, functional organization and vascular dynamics. However, most neuroimaging studies of ageing have focused on each imaging modality separately, limiting the understanding of interrelations between processes identified by different modalities and the interpretation of neural correlates of cognitive decline in ageing. Here, we used linked independent component analysis as a data-driven multimodal approach to jointly analyze magnetic resonance imaging of grey matter density, cerebrovascular, and functional network topographies. Neuroimaging and behavioural data (n = 215) from the Cambridge Centre for Ageing and Neuroscience study were used, containing healthy subjects aged 18 to 88. In the output components, fusion was found between structural and cerebrovascular topographies in multiple components with cognitive-relevance across the lifespan. A component reflecting global atrophy with regional cerebrovascular changes and a component reflecting right frontoparietal network activity were correlated with fluid intelligence over and above age and gender. No meaningful fusion between functional network topography and structural or cerebrovascular signals was observed. We propose that integrating multiple neuroimaging modalities allows to better characterize brain pattern variability and to differentiate brain changes in healthy ageing.

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“…This suggests that individuals contributing less to changes in cognitive scores from baseline to two years exhibit a stronger association between functional and structural data in the developing brain. These findings align with recent studies that have reported age-related changes in vasculature, brain anatomy, and brain function collectively contributing to complex interactions that influence cognitive alterations [56, 57].…”

Section: Discussionsupporting

confidence: 91%

Analysis of Longitudinal Change Patterns in Developing Brain Using Functional and Structural Magnetic Resonance Imaging via Multimodal Fusion

Saha,

et al. 2024

Preprint

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Functional and structural magnetic resonance imaging (fMRI and sMRI) are complementary approaches that can be used to study longitudinal brain changes in adolescents. Each individual modality offers distinct insights into the brain. Each individual modality may overlook crucial aspects of brain analysis. By combining them, we can uncover hidden brain connections and gain a more comprehensive understanding. In previous work, we identified multivariate patterns of change in whole-brain function during adolescence. In this work, we focus on linking functional change patterns (FCPs) to brain structure. We introduce two approaches and applied them to data from the Adolescent Brain and Cognitive Development (ABCD) dataset. First, we evaluate voxelwise sMRI-FCP coupling to identify structural patterns linked to our previously identified FCPs. Our approach revealed multiple interesting patterns in functional network connectivity (FNC) and gray matter volume (GMV) data that were linked to subject level variation. FCP components 2 and 4 exhibit extensive associations between their loadings and voxel-wise GMV data. Secondly, we leveraged a symmetric multimodal fusion technique called multiset canonical correlation analysis (mCCA) + joint independent component analysis (jICA). Using this approach, we identify structured FCPs such as one showing increased connectivity between visual and sensorimotor domains and decreased connectivity between sensorimotor and cognitive control domains, linked to structural change patterns (SCPs) including alterations in the bilateral sensorimotor cortex. Interestingly, females exhibit stronger coupling between brain functional and structural changes than males, highlighting sex-related differences. The combined results from both asymmetric and symmetric multimodal fusion methods underscore the intricate sex-specific nuances in neural dynamics. By utilizing two complementary multimodal approaches, our study enhances our understanding of the dynamic nature of brain connectivity and structure during the adolescent period, shedding light on the nuanced processes underlying adolescent brain development.

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Aging and cerebrovascular health: Structural, functional, cognitive, and methodological implications

Cited by 7 publications

References 69 publications

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

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

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

Analysis of Longitudinal Change Patterns in Developing Brain Using Functional and Structural Magnetic Resonance Imaging via Multimodal Fusion

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