|Titre :||Brain functional networks in syndromic and non-syndromic autism: a graph theoretical study of EEG connectivity (2013)|
|Auteurs :||Maxime TAQUET ; Jurriaan PETERS|
|Type de document :||Article : Texte imprimé et/ou numérique|
|Dans :||Biomedcentral Medicine (N° ind, 2013)|
|Article en page(s) :||16 p.|
|Index. décimale :||AUT.21 (Etiologie biomédicale)|
[Thesaurus CRA] -Candidat > AUTISTE
[Thesaurus CRA] AUTISME
[Thesaurus CRA] CERVEAU
[Thesaurus CRA] FONCTION CEREBRALE
[Thesaurus CRA] IMAGERIE MEDICALE
[Thesaurus CRA] NEUROSCIENCES
[Thesaurus CRA] SCLEROSE TUBEREUSE DE BOURNEVILLE
Background: Graph 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 nonsyndromic 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.
Methods: EEG 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.
Results: Analysis 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.
Conclusions: The 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.[résumé éditeur]
|En ligne :||http://www.biomedcentral.com/1741-7015/11/54|