Autism spectrum disorder (ASD) has been associated with various sensory atypicalities across multiple domains. Interoception, the ability to detect and attend to internal bodily sensations, has been found to moderate the experience of body ownership, a known difference in ASD that may affect social function. However, interoception has not been empirically examined in ASD. In the current study, 45 children (21 with ASD and 24 controls) ages 8 to 17 years completed a heartbeat perception paradigm as a measure of interoceptive ability. A subset of these children also completed the rubber hand illusion task, a multisensory paradigm probing the malleability of perceived body ownership. Although the heartbeat perception paradigm yielded comparable interoceptive awareness (IA) overall across both groups, children with ASD were superior at mentally tracking their heartbeats over longer intervals, suggesting increased sustained attention to internal cues in ASD. In addition, IA was negatively correlated with rubber hand illusion susceptibility in both groups, supporting a previously demonstrated inverse relationship between internal awareness and one's ability to incorporate external stimuli into one's perception of self. We propose a tradeoff between attention to internal cues and attention to external cues, whereby attentional resources are disproportionately allocated to internal, rather than external, sensory cues in ASD.
There is ample evidence of atypical functional connectivity (FC) in autism spectrum disorders (ASDs). However, transient relationships between neural networks cannot be captured by conventional static FC analyses. Dynamic FC (dFC) approaches have been used to identify repeating, transient connectivity patterns (“states”), revealing spatiotemporal network properties not observable in static FC. Recent studies have found atypical dFC in ASDs, but questions remain about the nature of group differences in transient connectivity, and the degree to which states persist or change over time. This study aimed to: (a) describe and relate static and dynamic FC in typical development and ASDs, (b) describe group differences in transient states and compare them with static FC patterns, and (c) examine temporal stability and flexibility between identified states. Resting‐state functional magnetic resonance imaging (fMRI) data were collected from 62 ASD and 57 typically developing (TD) children and adolescents. Whole‐brain, data‐driven regions of interest were derived from group independent component analysis. Sliding window analysis and k‐means clustering were used to explore dFC and identify transient states. Across all regions, static overconnnectivity and increased variability over time in ASDs predominated. Furthermore, significant patterns of group differences emerged in two transient states that were not observed in the static FC matrix, with group differences in one state primarily involving sensory and motor networks, and in the other involving higher‐order cognition networks. Default mode network segregation was significantly reduced in ASDs in both states. Results highlight that dynamic approaches may reveal more nuanced transient patterns of atypical FC in ASDs.
ObjectiveNo drug is yet approved to treat the core symptoms of autism spectrum disorder (ASD). Low‐dose suramin was effective in the maternal immune activation and Fragile X mouse models of ASD. The Suramin Autism Treatment‐1 (SAT‐1) trial was a double‐blind, placebo‐controlled, translational pilot study to examine the safety and activity of low‐dose suramin in children with ASD.MethodsTen male subjects with ASD, ages 5–14 years, were matched by age, IQ, and autism severity into five pairs, then randomized to receive a single, intravenous infusion of suramin (20 mg/kg) or saline. The primary outcomes were ADOS‐2 comparison scores and Expressive One‐Word Picture Vocabulary Test (EOWPVT). Secondary outcomes were the aberrant behavior checklist, autism treatment evaluation checklist, repetitive behavior questionnaire, and clinical global impression questionnaire.ResultsBlood levels of suramin were 12 ± 1.5 μmol/L (mean ± SD) at 2 days and 1.5 ± 0.5 μmol/L after 6 weeks. The terminal half‐life was 14.7 ± 0.7 days. A self‐limited, asymptomatic rash was seen, but there were no serious adverse events. ADOS‐2 comparison scores improved by −1.6 ± 0.55 points (n = 5; 95% CI = −2.3 to −0.9; Cohen's d = 2.9; P = 0.0028) in the suramin group and did not change in the placebo group. EOWPVT scores did not change. Secondary outcomes also showed improvements in language, social interaction, and decreased restricted or repetitive behaviors.InterpretationThe safety and activity of low‐dose suramin showed promise as a novel approach to treatment of ASD in this small study.
Atypical functional connectivity has been implicated in autism spectrum disorders (ASDs). However, the literature to date has been largely inconsistent, with mixed and conflicting reports of hypo- and hyper-connectivity. These discrepancies are partly due to differences between various neuroimaging modalities. Functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and magnetoencephalography (MEG) measure distinct indices of functional connectivity (e.g., blood-oxygenation level-dependent [BOLD] signal vs. electrical activity). Furthermore, each method has unique benefits and disadvantages with respect to spatial and temporal resolution, vulnerability to specific artifacts, and practical implementation. Thus far, functional connectivity research on ASDs has remained almost exclusively unimodal; therefore, interpreting findings across modalities remains a challenge. Multimodal integration of fMRI, EEG, and MEG data is critical in resolving discrepancies in the literature, and working toward a unifying framework for interpreting past and future findings. This review aims to provide a theoretical foundation for future multimodal research on ASDs. First, we will discuss the merits and shortcomings of several popular theories in ASD functional connectivity research, using examples from the literature to date. Next, the neurophysiological relationships between imaging modalities, including their relationship with invasive neural recordings, will be reviewed. Finally, methodological approaches to multimodal data integration will be presented, and their future application to ASDs will be discussed. Analyses relating transient patterns of neural activity ("states") are particularly promising. This strategy provides a comparable measure across modalities, captures complex spatiotemporal patterns, and is a natural extension of recent dynamic fMRI research in ASDs. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 78: 456-473, 2018.
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