A growing functional connectivity MRI (fcMRI) and diffusion tensor imaging (DTI) literature suggests that cognitive, sociocommunicative, and sensorimotor impairments in autism spectrum disorders (ASD) are associated with impaired brain network connectivity. However few ASD studies to date have combined measures of functional and anatomical connectivity. Even more importantly, there are no studies combining these with measures of dynamic processing, as provided by magnetoencephalography (MEG). We propose to use fcMRI, DTI, and MEG for a comprehensive investigation of connectivity in ASD, selecting a task paradigm to identify a visual, lexico-semantic, executive, and motor (VLSEM) circuit for an exemplary set of network nodes. Data from sixty adolescents with ASD and 60 matched typically developing (TD) participants will be acquired to pursue four specific aims: (1) To identify nodes of a VLSEM circuit using fMRI during lexical-semantic decision and to examine the functional connectivity within this circuit and between nodes and the remaining brain. (2) To examine the dynamic, spatiotemporal characteristics of the VLSEM circuit, using MEG in time-domain and time-frequency analyses including phase-locked co-oscillation in several frequency bands. (3) To examine the anatomical integrity of connections within the VLSEM circuit using probabilistic DTI tractography, and to test for links between fcMRI, MEG, and DTI measures. (4) To examine the relation of functional and anatomical connectivity as well as dynamic processing with diagnostic and neuropsychological measures in the ASD group. The study will contribute multimodal imaging evidence for an improved and comprehensive understanding of brain network abnormalities in ASD. Such evidence will be particularly important for the identification of biomarkers of ASD, including those which may distinguish biological subtypes of the disorder. The contribution to the search for biomarkers will have public health benefit because such biomarkers will be crucial for the identification of genetic and other causes of ASD needed for targeted treatment.
This project will use several MRI and MEG techniques for an in-depth investigation into abnormalities of brain network connectivity in autism spectrum disorder. Evidence from this study will contribute towards finding brain biomarkers needed to identify genetic and other causes of ASD and to develop targeted treatments.
