Brain resting‐state networks in adolescents with high‐functioning autism: Analysis of spatial connectivity and temporal neurodynamics

Abstract

IntroductionAutism spectrum disorder (ASD) is mainly characterized by functional and communication impairments as well as restrictive and repetitive behavior. The leading hypothesis for the neural basis of autism postulates globally abnormal brain connectivity, which can be assessed using functional magnetic resonance imaging (fMRI). Even in the absence of a task, the brain exhibits a high degree of functional connectivity, known as intrinsic, or resting‐state, connectivity. Global default connectivity in individuals with autism versus controls is not well characterized, especially for a high‐functioning young population. The aim of this study is to test whether high‐functioning adolescents with ASD (HFA) have an abnormal resting‐state functional connectivity.Materials and MethodsWe performed spatial and temporal analyses on resting‐state networks (RSNs) in 13 HFA adolescents and 13 IQ‐ and age‐matched controls. For the spatial analysis, we used probabilistic independent component analysis (ICA) and a permutation statistical method to reveal the RSN differences between the groups. For the temporal analysis, we applied Granger causality to find differences in temporal neurodynamics.ResultsControls and HFA display very similar patterns and strengths of resting‐state connectivity. We do not find any significant differences between HFA adolescents and controls in the spatial resting‐state connectivity. However, in the temporal dynamics of this connectivity, we did find differences in the causal effect properties of RSNs originating in temporal and prefrontal cortices.ConclusionThe results show a difference between HFA and controls in the temporal neurodynamics from the ventral attention network to the salience‐executive network: a pathway involving cognitive, executive, and emotion‐related cortices. We hypothesized that this weaker dynamic pathway is due to a subtle trigger challenging the cognitive state prior to the resting state.

Children With Autism Produce a Unique Pattern of EEG Microstates During an Eyes Closed Resting-State Condition

“…One study found fewer rapid transitions between brain networks in ASD compared to TD ( Watanabe and Rees, 2017 ). Studies by Bernas et al, 2018 and Damiani et al, 2018 have confirmed the abnormal temporal structure of the resting-state SN in ASD ( Bernas et al, 2018 ; Damiani et al, 2018 ). Although these studies have shed light on the temporal dynamics of brain network activity in ASD, they have been limited by the time resolution of the BOLD fMRI signal.…”

Altered Functional Connectivity in Children With Low-Function Autism Spectrum Disorders

“…Independent component analysis (ICA) is a blind source separation technique that has been widely used to identify and quantify distribution area modes or spatial networks of related activities (Braden et al, 2017; Bernas et al, 2018; Bi et al, 2018). Additionally, it plays an important role in decomposing mixed data into independent components (ICs).…”

Aberrant activation within auditory network is associated with psychiatric comorbidities in interictal migraineurs without aura

“…ICA is a data-driven analytical method to explore these independent component networks and their associated time series during the resting state. This method does not need a priori measurement signals and is independent of seed selection, which makes the resting-state analysis suitable and reproducible [6]. Prior studies discovered aberrant functional connectivity within intrinsic networks in the migraine-free period, such as visual network, default mode network and executive control network [7][8][9].…”