Altered Brain Network Function During Attention-Modulated Visual Processing In Multiple Sclerosis

MULTIPLE SCLEROSIS JOURNAL(2021)

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摘要
Background: Multiple sclerosis may damage cognitive performance in several domains, including attention. Although attention network deficits were described during rest, studies that investigate their function during task performance are scarce. Objective: To investigate connectivity within and between task-related networks in multiple sclerosis during a visual attention task as a function of cognitive performance. Methods: A total of 23 relapsing-remitting multiple sclerosis (RRMS) patients and 29 healthy controls underwent task-functional magnetic resonance imaging (fMRI) scans using a visual attention paradigm on a 3T scanner. Scans were analysed using tensor-independent component analysis (TICA). Functional connectivity was calculated within and between components. We assessed cognitive function with the Brief International Cognitive Assessment for MS (BICAMS) battery. Results: TICA extracted components related to visual processing, attention, executive function and the default-mode network. Subject scores of visual/attention-related and executive components were greater in healthy controls (p < 0.032,p < 0.023). Connectivity between visual/attention-related and default-mode components was higher in patients (p < 0.043), correlating with Brief Visuospatial Memory Test-Revised (BVMT-R) scores (R = -0.48,p < 0.036). Patients showed reduced connectivity between the right intraparietal sulcus (rIPS) and frontal eye field (rFEF), and bilateral frontal eye fields (p < 0.012,p < 0.003). Reduced rIPS-rFEF connectivity came with lower Symbol Digit Modalities Test (SDMT)/BVMT-R scores in patients (R = 0.53,p < 0.02,R = 0.46,p < 0.049). Conclusion: Attention-related networks show altered connectivity during task performance in RRMS patients, scaling with cognitive disability.
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关键词
Relapsing-remitting multiple sclerosis, cognitive disability, visuospatial attention, functional MRI, model-free analysis
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