The longitudinal relationship between BOLD signal variability changes and white matter maturation during early childhood

NeuroImage

Andrea B. Protzner¹  Amirhossein Ghaderi²  Jess E. Reynolds³  Hongye Wang⁴  Xiangyu Long⁴  Catherine Lebel⁵ 

[1] Alberta Children's Hospital Research Institute, Calgary, AB, Canada;Corresponding author.;Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada;Department of Psychology, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada;Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada;

关键词: BOLD signal variability;    White matter;    Longitudinal;    Early childhood;    Structure-function relationship;    Brain development;   

DOI  :  

来源: DOAJ

【 摘 要 】

Intra-individual transient temporal fluctuations in brain signal, as measured by fMRI blood oxygenation level dependent (BOLD) variability, is increasingly considered an important signal rather than measurement noise. Evidence from computational and cognitive neuroscience suggests that signal variability is a good proxy-measure of brain functional integrity and information processing capacity. Here, we sought to explore across-participant and longitudinal relationships between BOLD variability, age, and white matter structure in early childhood. We measured standard deviation of BOLD signal, total white matter volume, global fractional anisotropy (FA) and mean diffusivity (MD) during passive movie viewing in a sample of healthy children (aged 2–8 years; N = 83). We investigated how age and white matter development related to changes in BOLD variability both across- and within-participants. Our across-participant analyses using behavioural partial least squares (bPLS) revealed that the influence of age and white matter maturation on BOLD variability was highly interrelated. BOLD variability increased in widespread frontal, temporal and parietal regions, and decreased in the hippocampus and parahippocampal gyrus with age and white matter development. Our longitudinal analyses using linear mixed effects modelling revealed significant associations between BOLD variability, age and white matter microstructure. Analyses using artificial neural networks demonstrated that BOLD variability and white matter micro and macro-structure at earlier ages were strong predictors of BOLD variability at later ages. By characterizing the across-participant and longitudinal features of the association between BOLD variability and white matter micro- and macrostructure in early childhood, our results provide a novel perspective to understand structure-function relationships in the developing brain.

【 授权许可】

Unknown