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Cerebral Blood Flow-Based Resting State Functional Connectivity of the Human Brain using Optical Diffuse Correlation Spectroscopy
Published on: May 27, 2020
Development and Emergence of Individual Variability in the Functional Connectivity Architecture of the Preterm Human
Yuehua Xu1,2,3, Miao Cao1,2,3, Xuhong Liao1,2,3
1National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.
Abstract:
Individual variability in human brain networks underlies individual differences in cognition and behaviors. However, researchers have not conclusively determined when individual variability patterns of the brain networks emerge and how they develop in the early phase. Here, we employed resting-state functional MRI data and whole-brain functional connectivity analyses in 40 neonates aged around 31-42 postmenstrual weeks to characterize the spatial distribution and development modes of individual variability in the functional network architecture. We observed lower individual variability in primary sensorimotor and visual areas and higher variability in association regions at the third trimester, and these patterns are generally similar to those of adult brains. Different functional systems showed dramatic differences in the development of individual variability, with significant decreases in the sensorimotor network; decreasing trends in the visual, subcortical, and dorsal and ventral attention networks, and limited change in the default mode, frontoparietal and limbic networks. The patterns of individual variability were negatively correlated with the short- to middle-range connection strength/number and this distance constraint was significantly strengthened throughout development. Our findings highlight the development and emergence of individual variability in the functional architecture of the prenatal brain, which may lay network foundations for individual behavioral differences later in life.
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