Brain functional networks in syndromic and non-syndromic autism: a graph theoretical study of EEG connectivity

Abstract

BackgroundGraph theory has been recently introduced to characterize complex brain networks, making it highly suitable to investigate altered connectivity in neurologic disorders. A current model proposes autism spectrum disorder (ASD) as a developmental disconnection syndrome, supported by converging evidence in both non-syndromic and syndromic ASD. However, the effects of abnormal connectivity on network properties have not been well studied, particularly in syndromic ASD. To close this gap, brain functional networks of electroencephalographic (EEG) connectivity were studied through graph measures in patients with Tuberous Sclerosis Complex (TSC), a disorder with a high prevalence of ASD, as well as in patients with non-syndromic ASD.MethodsEEG data were collected from TSC patients with ASD (n = 14) and without ASD (n = 29), from patients with non-syndromic ASD (n = 16), and from controls (n = 46). First, EEG connectivity was characterized by the mean coherence, the ratio of inter- over intra-hemispheric coherence and the ratio of long- over short-range coherence. Next, graph measures of the functional networks were computed and a resilience analysis was conducted. To distinguish effects related to ASD from those related to TSC, a two-way analysis of covariance (ANCOVA) was applied, using age as a covariate.ResultsAnalysis of network properties revealed differences specific to TSC and ASD, and these differences were very consistent across subgroups. In TSC, both with and without a concurrent diagnosis of ASD, mean coherence, global efficiency, and clustering coefficient were decreased and the average path length was increased. These findings indicate an altered network topology. In ASD, both with and without a concurrent diagnosis of TSC, decreased long- over short-range coherence and markedly increased network resilience were found.ConclusionsThe altered network topology in TSC represents a functional correlate of structural abnormalities and may play a role in the pathogenesis of neurological deficits. The increased resilience in ASD may reflect an excessively degenerate network with local overconnection and decreased functional specialization. This joint study of TSC and ASD networks provides a unique window to common neurobiological mechanisms in autism.

Symptom profiles of autism spectrum disorder in tuberous sclerosis complex

“…Using EEG, common alterations in network topology have been found in TSC/ASD and nsASD, marked by reduced long-over short-range coherence in individuals across a wide age range (infancy through to young adulthood). 26 At the behavioral level, there is a higher degree of convergence between parent-reported ASD symptomatology in children (at approximately 10 years of age) with TSC and nsASD than other high-risk groups (such as Down syndrome and Klinefelter syndrome). 27 Our findings extend this line of research to show item-level convergence based on direct observation in social communication deficits between TSC/ ASD and nsASD within the first 3 years of life.…”

ASD Validity

“…If syndromic ASD symptoms do not result from an independent ASD-specific brain impairment, then ASD diagnostic symptoms in syndromic ASD must result from widely varied brain impairments. Peters et al (2013) and Tye and Bolton (2013) argued for an independent unique ASD brain impairment in syndromic ASD. Peters et al (2013) asserted that in syndromic ASD with tuberous sclerosis complex (TSC), the TSC brain tubers and TSC malorganization of the brain caused TSC symptoms, but that brain underconnectivity was independently and uniquely causal for ASD alone.…”

Epilepsy and Autism

“…As in the imaging reports, the resulting evidence is conflicting and inconsistent. Twenty-one studies in the last decade have been published; 11 evaluated resting state (Murias et al 2007;Coben et al 2008;Barttfeld et al 2011;Bosl et al 2011;Duffy and Als 2012;Mathewson et al 2012;Sheikhani et al 2012;Leveille and Hannagan 2013;Peters et al 2013;Machado et al 2015), eight were task related (Isler et al 2010;Lazarev et al 2010;Catarino et al 2013;Garcia Dominguez et al 2013;Carson et al 2014;Orekhova et al 2014;Righi et al 2014;Lazarev et al 2015;Machado et al 2015); one obtained during non-rapid eye movement (NREM) sleep (Lazar et al 2010) and one obtained during rapid eye movement (REM) sleep (Leveille et al 2010). It is not possible to directly compare these studies as the acquisition paradigm, the age of the subjects, Figure 3.…”