title: Resting State Functional Connectivity MRI among Spectral MEG Current Sources in Children on the Autism Spectrum.
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 t-tests were used as regions of interest (ROIs) for the fMRI functional connectivity analysis. Pairwise BOLD signal correlations were obtained between each pair of these ROIs for each frequency band. Each pairwise correlation was compared between the ASD and TD groups using t-tests. We also constrained these pairwise correlations to known network structures, resulting in a follow-up set of correlation matrices specific to each network we considered. Frequency-specific MEG sources had distinct patterns of fMRI resting state functional connectivity in the ASD group, but perhaps the most significant was a finding of hypoconnectivity between many sources of low and high gamma activity. These novel findings suggest that in ASD there are differences in functionally defined networks as shown in previous fMRI studies, as well as between sets of regions defined by magnetoencephalographic neural oscillatory activity.
authors.affiliation: Cognitive Science, University of California San DiegoLa Jolla, CA, USA; Neurosciences, University of California San DiegoLa Jolla, CA, USA.
authors.forename: Michael
authors.initials: M
authors.lastname: Datko
authors.affiliation: Cognitive Science, University of California San Diego La Jolla, CA, USA.
authors.forename: Robert
authors.initials: R
authors.lastname: Gougelet
authors.affiliation: Department of Radiology, University of California San Diego La Jolla, CA, USA.
authors.forename: Ming-Xiong
authors.initials: MX
authors.lastname: Huang
authors.affiliation: Cognitive Science, University of California San DiegoLa Jolla, CA, USA; Neurosciences, University of California San DiegoLa Jolla, CA, USA.
authors.forename: Jaime A
authors.initials: JA
authors.lastname: Pineda
keywords: autism; fMRI; functional connectivity; magnetoencephalography; multimodal