AUTHOR=Datko Michael , Gougelet Robert , Huang Ming-Xiong , Pineda Jaime A. TITLE=Resting State Functional Connectivity MRI among Spectral MEG Current Sources in Children on the Autism Spectrum JOURNAL=Frontiers in Neuroscience VOLUME=10 YEAR=2016 URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2016.00258 DOI=10.3389/fnins.2016.00258 ISSN=1662-453X ABSTRACT=
Social and communicative impairments are among the core symptoms of autism spectrum disorders (ASD), and a great deal of evidence supports the notion that these impairments are associated with aberrant functioning and connectivity of various cortical networks. The present study explored the links between sources of MEG amplitude in various frequency bands and functional connectivity MRI in the resting state. The goal of combining these modalities was to use sources of neural oscillatory activity, measured with MEG, as functionally relevant seed regions for a more traditional pairwise fMRI connectivity analysis. We performed a seed-based connectivity analysis on resting state fMRI data, using seed regions derived from frequency-specific amplitude sources in resting state MEG data in the same nine subjects with ASD (10–17 years of age). We then compared fMRI connectivity among these MEG-source-derived regions between participants with autism and typically developing, age-matched controls. We used a source modeling technique designed for MEG data to detect significant amplitude sources in six frequency bands: delta (2–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (12–30 Hz), low gamma (30–60 Hz), and high gamma (60–120 Hz). MEG-derived source maps for each participant were co-registered in standard MNI space, and group-level source maps were obtained for each frequency. For each frequency band, the 10 largest clusters resulting from these