Relationship Between Neural Coherence and Social Functioning in Autism Spectrum Disorder

Saturday, May 16, 2015: 11:30 AM-1:30 PM
Imperial Ballroom (Grand America Hotel)
T. M. Andersen1, C. Swick1, A. M. Flores1, K. Lengu1, R. Goodcase1, K. McFarlane1, S. M. Bowyer2 and R. Lajiness-O'Neill1, (1)Psychology, Eastern Michigan University, Ypsilanti, MI, (2)Neurology, Henry Ford Hospital, Detroit, MI
Background: Autism spectrum disorders (ASD) are characterized by atypical social functioning, communication, and restricted/repetitive behaviors. With increasing prevalence (1 in 68), it is imperative to clarify etiological mechanisms and identify biomarkers underlying ASD that may lead to earlier diagnosis. Disruptions in neural synchrony may be a primary neurophysiological mechanism underlying aberrant connectivity that could contribute to the core symptoms of ASD, particularly altered social functioning.  

Objectives: This study investigated relationships between neural synchrony (i.e., synchronous brain oscillations) at rest and social functioning.

Methods: Twelve ASD (Age: M = 8.9; SD= 1.0) and 13 neurotypical (NT) children (Age: M = 9.3; SD = 1.3) underwent magnetoencephalography (MEG) during resting state. Cortical activity was recorded using a 148 channel whole head MEG system (4D Neuroimaging, Magnes WH2500). Synchronization of neuronal activity was quantified by calculating coherence (0 to 1) (i.e. connectivity) between cortical sites from MEG imaged brain activations. Power spectra for activity at all active sites were calculated to quantify differences in alpha (8-14 Hz), beta (15-30 Hz), and gamma power (30-80 Hz). For each frequency, a t-test was computed to assess group differences in coherence for each pair of brain regions (N=1431). Kendall Tau correlations were computed to explore relationships between coherence and social functioning and measured by the Social Responsiveness Scale. 

Results: Decreased coherence between Default Mode Network (DMN) regions (medial prefrontal, cingulate, and parietal cortices) was noted in ASD. Alpha band: In ASD, higher coherence between cingulate and right precentral (t = -.62, p = .006), postcentral (t = -.59, p = .008) regions was related to greater social awareness. In NT, higher coherence between right orbitofrontal regions and right (t = .50, p = .03) and left gyrus rectus (t = .47, p = .04) as well as left angular gyrus was related to overall social difficulties. For both groups, higher coherence between left caudate and other cortical regions was related to more atypical behaviors.  Gamma band: In ASD, higher coherence between left temporo-parieto-occipital and right temporal and frontal regions, particularly orbitofrontal, was related to lower social awareness. Increased connectivity between right parietal (angular) regions and fronto-temporal regions was related to increased atypical behaviors.  

Conclusions: This study aims to illuminate differences in neural synchrony and altered patterns of connectivity that could serve as a potential biomarker for ASD. Analyses indicate that enhanced alpha power and connectivity between regions of the DMN are related to higher social awareness in ASD. In both groups, increased alpha and gamma power and connectivity between orbitofrontal regions and posterior cortical regions appears to confer risk for social difficulties. Likewise, higher connectivity between the striatum and other cortical regions confers risk for atypicality.  These findings suggest an emerging pattern of altered cortical connectivity in regions of the DMN that are related to aberrant social functioning and aberrant connectivity between the basal ganglia that is related to atypical behaviors; both core deficits in ASD.  Finally, the results reveal the utility of MEG to quantify altered neural coherence and to detect potential biomarkers of ASD.