Changes in white matter functional networks across late adulthood

Frontiers in Aging Neuroscience

Neuroscience

Adam W. Anderson¹  Yurui Gao¹  Zhaohua Ding²  Richard D. Lawless³  Lyuan Xu³  Yu Zhao⁴  Kurt G. Schilling⁴  Muwei Li⁴  John C. Gore⁵  Bennett A. Landman⁶ 

[1] Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States;Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States;Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States;Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States;Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, United States;Department of Computer Science, Vanderbilt University, Nashville, TN, United States;Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States;Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, United States;Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States;Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States;Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States;Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States;Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States;Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States;Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States;Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States;Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, United States;

关键词: fMRI;    resting state;    BOLD;    normal aging brain;    white matter (WM);    ICA;   

DOI  :  10.3389/fnagi.2023.1204301

 received in 2023-04-12, accepted in 2023-06-14,  发布年份 2023

来源: Frontiers

【 摘 要 】

IntroductionThe aging brain is characterized by decreases in not only neuronal density but also reductions in myelinated white matter (WM) fibers that provide the essential foundation for communication between cortical regions. Age-related degeneration of WM has been previously characterized by histopathology as well as T2 FLAIR and diffusion MRI. Recent studies have consistently shown that BOLD (blood oxygenation level dependent) effects in WM are robustly detectable, are modulated by neural activities, and thus represent a complementary window into the functional organization of the brain. However, there have been no previous systematic studies of whether or how WM BOLD signals vary with normal aging. We therefore performed a comprehensive quantification of WM BOLD signals across scales to evaluate their potential as indicators of functional changes that arise with aging.MethodsBy using spatial independent component analysis (ICA) of BOLD signals acquired in a resting state, WM voxels were grouped into spatially distinct functional units. The functional connectivities (FCs) within and among those units were measured and their relationships with aging were assessed. On a larger spatial scale, a graph was reconstructed based on the pair-wise connectivities among units, modeling the WM as a complex network and producing a set of graph-theoretical metrics.ResultsThe spectral powers that reflect the intensities of BOLD signals were found to be significantly affected by aging across more than half of the WM units. The functional connectivities (FCs) within and among those units were found to decrease significantly with aging. We observed a widespread reduction of graph-theoretical metrics, suggesting a decrease in the ability to exchange information between remote WM regions with aging.DiscussionOur findings converge to support the notion that WM BOLD signals in specific regions, and their interactions with other regions, have the potential to serve as imaging markers of aging.

【 授权许可】

Unknown   
Copyright © 2023 Li, Gao, Lawless, Xu, Zhao, Schilling, Ding, Anderson, Landman and Gore.