Abstract

Fetal alcohol spectrum disorder (FASD) is a significant public health problem that is associated with a broad range of physical, neurocognitive, and behavioral effects resulting from prenatal alcohol exposure (PAE). Magnetic resonance imaging (MRI) has been an important tool for advancing our knowledge of abnormal brain structure and function in individuals with FASD. However, whereas only a small number of studies have applied graph theory-based network analysis to resting-state functional MRI (fMRI) data in individuals with FASD additional research in this area is needed. Resting-state fMRI data were collected from adolescent and young adult participants (ages 12-22) with fetal alcohol syndrome (FAS) or alcohol-related neurodevelopmental disorder (ARND) and neurotypically developing controls (CNTRL) from previous studies. Group independent components analysis (gICA) was applied to fMRI data to extract components representing functional brain networks. Functional network connectivity (FNC), measured by Pearson correlation of the average independent component (IC) time series, was analyzed under a graph theory framework to compare network modularity, the average clustering coefficient, characteristic path length, and global efficiency between groups. Cognitive intelligence, measured by the Wechsler Abbreviated Scale of Intelligence (WASI), was compared and correlated to global network measures. Group comparisons revealed significant differences in the average clustering coefficient, characteristic path length, and global efficiency. Modularity was not significantly different between groups. The FAS and ARND groups scored significantly lower than the CNTRL group on Full Scale IQ (FS-IQ) and the Vocabulary subtest, but not the Matrix Reasoning subtest. No significant associations between intelligence and graph theory measures were detected. Our results partially agree with previous studies examining global graph theory metrics in children and adolescents with FASD and suggest that the exposure to alcohol during prenatal development leads to disruptions in aspects of functional network segregation and integration.

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