Dynamic functional connectivity profile of the salience network across the life span

Snyder, William E.; Uddin, Lucina Q.; Nomi, Jason S.

doi:10.1002/hbm.25581

Cited by 35 publications

(22 citation statements)

References 65 publications

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“…Additionally, although this relationship did not reach statistical significance, the pattern suggests that older adults with greater connectivity within the salience network appear to perform better on the inhibitory control task (Stroop interference). Our results support previous findings ( Onoda et al, 2012 ; Das et al, 2021 ; Snyder et al, 2021 ). These results also support the meta-analysis results ( Rey-Mermet and Gade, 2017 ), which calls into question the inhibition deficit hypothesis, as we did not find a significant correlation between age and Stroop performance.…”

Section: Discussionsupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

“…Two recent studies provide evidence that extensive reorganization within and between the salience network and other neurocognitive networks is associated with age ( Das et al, 2021 ; Snyder et al, 2021 ). These results suggest that functional connectivity between the salience network and other neurocognitive networks evolve throughout the life span ( Snyder et al, 2021 ). Given that the dACC is a key node of the salience network ( Seeley et al, 2007 ) and is critically involved in inhibitory control, the dACC may play a significant role in inhibitory control deficits related to aging.…”

Section: Introductionmentioning

confidence: 99%

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Functional Brain Connectivity and Inhibitory Control in Older Adults: A Preliminary Study

Brewster

Pasqualini

Martin

2022

Front. Aging Neurosci.

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According to the inhibition deficit hypothesis, the ability to inhibit unwanted or irrelevant thoughts and behaviors decreases with age, which can have a significant impact on cognitive and emotional processing. However, studies examining inhibition and age have shown mixed results, with some studies finding a decrease in inhibitory control as individuals age, while others have found no relationship. The goal of this proof-of-concept study was to examine the underlying neural mechanisms that may explain why some older adults are better than others at inhibitory control by investigating the relationship between resting-state functional connectivity (rsFC) of the salience network, a network critical for detecting and focusing attention toward relevant stimuli while ignoring irrelevant information in the environment, and a behavioral measure of inhibitory control (Stroop Task interference score) in a sample of 65 healthy older individuals (ages 65+). Results revealed no direct effect of age on Stroop performance; however, there was an indirect effect of age on Stroop performance through rsFC. These results suggest that rsFC of the salience network may be an important factor to consider when it comes to understanding individual differences in inhibitory control behavior among older adults.

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Section: Discussionsupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Functional Brain Connectivity and Inhibitory Control in Older Adults: A Preliminary Study

Brewster

Pasqualini

Martin

2022

Front. Aging Neurosci.

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“…The second cortical cluster in our graph analysis potentially corresponds to the cortical regions of the salience network (ACC, frontoinsular cortex and subcortical structures). 75 Altered intrinsic connectivity in the salience network was described in patients with childhood absence epilepsy. 49 Integrity of the salience network is associated with DMN function.…”

Section: Discussionmentioning

confidence: 99%

Identifying the neural network for neuromodulation in epilepsy through connectomics and graphs

Vetkas

Germann

Elias

et al. 2022

Brain Communications

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Deep brain stimulation is a treatment option for patients with drug-resistant epilepsy. The precise mechanism of neuromodulation in epilepsy is unknown and biomarkers are needed for optimizing treatment. The aim of this study was to describe the neural network associated with deep brain stimulation targets for epilepsy and to explore its potential application as a novel biomarker for neuromodulation. Using seed-to-voxel functional connectivity maps, weighted by seizure outcomes, brain areas associated with stimulation were identified in normative resting state functional scans of 1000 individuals. To pinpoint specific regions in the normative epilepsy deep brain stimulation network, we examined overlapping areas of functional connectivity between the anterior thalamic nucleus, centromedian thalamic nucleus, hippocampus, and less studied epilepsy deep brain stimulation targets. Graph network analysis was used to describe the relationship between regions in the identified network. Furthermore, we examined the associations of the epilepsy deep brain stimulation network with disease pathophysiology, canonical resting state networks and findings from a systematic review of resting state functional MRI studies in epilepsy deep brain stimulation patients. Cortical nodes identified in the normative epilepsy deep brain stimulation network were in the anterior and posterior cingulate, medial frontal and sensorimotor cortices, frontal operculum and bilateral insulae. Subcortical nodes of the network were in the basal ganglia, mesencephalon, basal forebrain, and cerebellum. anterior thalamic nucleus was identified as a central hub in the network with the highest betweenness and closeness values, while centromedian thalamic nucleus and hippocampus showed average centrality values. The caudate nucleus and mammillothalamic tract also displayed high centrality values. The anterior cingulate cortex was identified as an important cortical hub associated with the effect of deep brain stimulation in epilepsy. The neural network of deep brain stimulation targets shared hubs with known epileptic networks and brain regions involved in seizure propagation and generalization. Two cortical clusters identified in the epilepsy deep brain stimulation network included regions corresponding to resting state networks, mainly the default mode and salience networks. Our results were concordant with findings from a systematic review of resting state functional MRI studies in patients with deep brain stimulation for epilepsy. Our findings suggest that the various epilepsy deep brain stimulation targets share a common cortico-subcortical network, which might in part underpin the antiseizure effects of stimulation. Interindividual differences in this network functional connectivity could potentially be used as biomarkers in selection of patients, stimulation parameters, and neuromodulation targets.

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“…Four resting-state functional networks were selected to achieve a relatively balanced number of inputs between functional and non-functional imaging measurements. The DMN, SN, right and left FPN were selected, which are higher-order functional networks known to be associated with age and cognitive change including fluid intelligence (Buckner, Andrews-Hanna, & Schacter, 2008; Corbetta & Shulman, 2002; Samu et al, 2017; Snyder, Uddin, & Nomi, 2021; Tibon et al, 2021).…”

Section: Methodsmentioning

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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Dynamic functional connectivity profile of the salience network across the life span

Cited by 35 publications

References 65 publications

Functional Brain Connectivity and Inhibitory Control in Older Adults: A Preliminary Study

Functional Brain Connectivity and Inhibitory Control in Older Adults: A Preliminary Study

Identifying the neural network for neuromodulation in epilepsy through connectomics and graphs

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

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