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2 result(s) for "Bochet Aurélie"
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Early alterations of large-scale brain networks temporal dynamics in young children with autism
Autism spectrum disorders (ASD) are associated with disruption of large-scale brain network. Recently, we found that directed functional connectivity alterations of social brain networks are a core component of atypical brain development at early developmental stages in ASD. Here, we investigated the spatio-temporal dynamics of whole-brain neuronal networks at a subsecond scale in 113 toddlers and preschoolers (66 with ASD) using an EEG microstate approach. We first determined the predominant microstates using established clustering methods. We identified five predominant microstate (labeled as microstate classes A–E) with significant differences in the temporal dynamics of microstate class B between the groups in terms of increased appearance and prolonged duration. Using Markov chains, we found differences in the dynamic syntax between several maps in toddlers and preschoolers with ASD compared to their TD peers. Finally, exploratory analysis of brain–behavioral relationships within the ASD group suggested that the temporal dynamics of some maps were related to conditions comorbid to ASD during early developmental stages.To assess the association between Autism spectrum disorders (ASD) and the potential disruption of large-scale brain networks, Bochet, Sperdin et al investigated spatiotemporal dynamics of whole-brain neuronal networks in 113 toddlers and preschoolers (66 with ASD) using an EEG microstate approach. They found differences in the dynamic syntax between several maps in toddlers and pre-schoolers with ASD compared to their TD peers.
Early alterations of large-scale brain networks temporal dynamics in young children with autism
ABSTRACT Disruption of large-scale brain networks is associated with autism spectrum disorders (ASD). Recently, we found that directed functional connectivity alterations of social brain networks are a core component of atypical brain development at early developmental stages in ASD (Sperdin et al., 2018). Here, we investigated the spatio-temporal dynamics of whole-brain neuronal networks at a subsecond scale in 90 toddlers and preschoolers (47 with ASD) using an EEG microstate approach. Results revealed the presence of five microstate classes that best described the entire dataset (labeled as microstate classes A-E). Microstate class C related to the Default Mode Network (DMN) occurred less in children with ASD. Analysis of brain-behavioural relationships within the ASD group suggested that a compensatory mechanism from microstate C was associated with less severe symptoms and better adaptive skills. These results demonstrate that the temporal properties of some specific EEG microstates are altered in ASD at early developmental stages. Competing Interest Statement The authors have declared no competing interest.