While MRI studies may offer

While MRI studies may offer anatomical insight about connectivity in autism, they lack temporal resolution. EEG and magnetoencephalography (MEG) studies provide a means of evaluating this parameter of functional connectivity. These coherence studies generally analyze the phase shift and amplitude ratio between two signals over time where consistency of the relationship, on a frequency by frequency basis, is interpreted as high coherence or evidence for functional connectivity. A number of studies have compared EEG coherence findings between ASD and typically developing control populations (Cantor et al., 1986; Murias et al., 2007; Coben et al., 2008; Lazarev et al., 2010; Isler et al., 2010; Barttfeld et al., 2011; Leveille et al., 2010; Duffy and Als, 2012). Similar to the MRI studies, there have been mixed results with some children with ASD demonstrating reduced coherences (Khan et al., 2013; Coben et al., 2008), while others have shown increases in coherences (Murias et al., 2007; Orekhova et al., 2014; Dominguez et al., 2013) or mixed patterns (Barttfeld et al., 2011; Leveille et al., 2010; Duffy and Als, 2012).
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Discussion Whereas EEG coherence is a measure of the consistency of phase differences over space and computes “phase synchrony” or “phase stability” between spatially distant generators, phase lag represents the phase difference between EEG signals. On a frequency-by-frequency basis, EEG spectral coherence represents the consistency of the phase difference between two EEG signals when compared over time whereas phase lag measures the actual differences in phase. In practice, high coherence values are taken as a measure of strong connectivity between the purchase RG7112 regions that produce the compared EEG signals (Srinivasan et al., 2007). The role of sleep in the proper maturation of the developing brain is an area of current intense interest, with the contribution of state-specific processes to synaptic refinement just beginning to be understood. The vast majority of ASD coherence studies are not performed during sleep, and taken as a whole, show very mixed results. Some of the waking evaluations used EEG or magnetoencephalography (Coben et al., 2008) and demonstrated reduced coherences (Khan et al., 2013; Coben et al., 2008), with other studies reporting increases (Murias et al., 2007; Orekhova et al., 2014; Dominguez et al., 2013) or mixed patterns (Barttfeld et al., 2011; Duffy and Als, 2012). In the MRI literature, the consistent pattern emerging across several studies is that while intrinsic functional connectivity in adolescents and adults with autism is generally reduced compared with age-matched controls, functional connectivity in younger children with ASD appears to be increased (Uddin et al., 2013; Nomi and Uddin, 2015). Kitzbichler et al. took an elegant approach to the apparent discrepancies of over-connectivity versus under-connectivity in a study of ASD versus control (ages 6–21years), examining both MEG and MRI in the resting state in each subject. The authors concluded that the true relationship is more complicated with the major differences being mediated by both region and frequency examined (Kitzbichler et al., 2015). Our current study adds to the complexity surrounding the search for electrophysiologic biomarker signatures of aberrant neurodevelopment by positing that in addition to age, bandwidth and region, brain state matters enormously to any measurements of differences in coherence in the developing brain. Sleep is a protected time for brain maturation and changes that are detected only during sleep may provide an early window affording valuable information about the rapid and dynamic changes that must take place to build normal functional relationships. The two major factors that drove the nature of connectivity abnormalities in ASD were the mediating frequency band and whether the network included frontal nodes. These factors determined whether clustering and integration were increased or decreased in cortical resting state networks in ASD.