Network mechanisms underlying core behavioral features in Fragile X Syndrome

Project Summary Fragile X Syndrome (FXS), a rare monogenic neurodevelopmental disorder caused by a trinucleotide expansion of the Fmr1 gene on the X chromosome. FXS is the most common inherited form of intellectual disability (ID) and monogenic cause of autism spectrum disorder (ASD), characterized by sensory

hypersensitivities, executive dysfunction, learning difficulties, and social anxiety. Individuals with FXS also exhibit increased functional connectivity (FC) abnormalities observed using electroencephalography (EEG) related to cognitive impairments and behavioral features of FXS, with a high degree of heterogeneity (despite being

monogenic). Limited work has addressed these FC disruptions in frontoparietal, and temporal networks with no studies directly assessing FC disruptions during a cognitive task. I hypothesize specific network connectivity dynamics within frontoparietal and temporal regions in FXS will effectively parse higher-order behavioral features

of FXS from ID, with frontoparietal FC disruption related to the “control network” being more associated with both ID and cognitive control (including cognitive/behavioral flexibility) and temporal “salience network” FC more associated with other FXS features, particularly sensory hypersensitivity and anxiety. The long-term goal of this

proposal is to characterize functional disruptions in networks underlying ID and cognitive function as separate from behavioral features of FXS to identify targets for intervention while using a cognitive task and address heterogeneity in neural network performance underlying features core to FXS (e.g., hyperactivity, sensory

processing difficulties, anxiety). Experiments proposed in Aim 1 will use robust FC measures through a source analysis to parse ID from other features of FXS to evaluate the effectiveness of using microstates as a proxy and to explore the triple network hypothesis in FXS by assessing FC during a cognitive task. Aim 2 will utilize

data-driven methods to identify variable combinations from EEG to meaningfully distinguishing FXS from individuals with developmental delay (DD), and parse cognitive ability/ID (defined by NIH Toolbox for ID and nonverbal IQ) from other FXS features (i.e., anxiety, hyperactivity, sensory hypersensitivities). The proposed

project will have broad implications for ongoing efforts to evaluate neurophysiology in FXS and the development of effective biomarkers for therapeutic applications, particularly taking the novel approach of addressing FC during a cognitive task.