decoding lifespan changes of the human brain using resting-state functional connectivity mri解码寿命变化的人类大脑使用静息状态的功能连接磁共振成像.pdfVIP

Decoding Lifespan Changes of the Human Brain Using Resting-State Functional Connectivity MRI Lubin Wang, Longfei Su, Hui Shen, Dewen Hu* College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan, China Abstract The development of large-scale functional brain networks is a complex, lifelong process that can be investigated using resting-state functional connectivity MRI (rs-fcMRI). In this study, we aimed to decode the developmental dynamics of the whole-brain functional network in seven decades (8–79 years) of the human lifespan. We first used parametric curve fitting to examine linear and nonlinear age effect on the resting human brain, and then combined manifold learning and support vector machine methods to predict individuals’ ‘‘brain ages’’ from rs-fcMRI data. We found that age-related changes in interregional functional connectivity exhibited spatially and temporally specific patterns. During brain development from childhood to senescence, functional connections tended to linearly increase in the emotion system and decrease in the sensorimotor system; while quadratic trajectories were observed in functional connections related to higher-order cognitive functions. The complex patterns of age effect on the whole-brain functional network could be effectively represented by a low-dimensional, nonlinear manifold embedded in the functional connectivity space, which uncovered the inherent structure of brain maturation and aging. Regression of manifold coordinates with age further showed that the manifold representation extracted sufficient information from rs-fcMRI data to make prediction about individual brains’ functional development levels. Our study not only gives insights into the neural substrates that underlie behavioral and cognitive chan