Fractionation of social brain circuits in autism spectrum disorders

Section on Cognitive Neuropsychology, Laboratory of Brain and Cognition, National Institute of Mental Health (NIMH), National Institutes of Health, Bethesda, MD 20892, USA. .
Brain (Impact Factor: 9.2). 07/2012; 135(Pt 9):2711-25. DOI: 10.1093/brain/aws160
Source: PubMed


Autism spectrum disorders are developmental disorders characterized by impairments in social and communication abilities and repetitive behaviours. Converging neuroscientific evidence has suggested that the neuropathology of autism spectrum disorders is widely distributed, involving impaired connectivity throughout the brain. Here, we evaluate the hypothesis that decreased connectivity in high-functioning adolescents with an autism spectrum disorder relative to typically developing adolescents is concentrated within domain-specific circuits that are specialized for social processing. Using a novel whole-brain connectivity approach in functional magnetic resonance imaging, we found that not only are decreases in connectivity most pronounced between regions of the social brain but also they are selective to connections between limbic-related brain regions involved in affective aspects of social processing from other parts of the social brain that support language and sensorimotor processes. This selective pattern was independently obtained for correlations with measures of social symptom severity, implying a fractionation of the social brain in autism spectrum disorders at the level of whole circuits.

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Available from: Stephen J. Gotts, Oct 02, 2015
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    • "Finally, for each voxel in this mask, we performed acrosssubject correlation analyses between its functional connectivity (z score) with the seed(s) and the participant's CAR measures. This approach is adopted from previous studies examining neural networks (Gotts et al., 2012; Wei et al., 2012; Liang et al., 2013) to find a CARrelated network. Similarly, the participants' cortisol level before the scan and sleep quality were regressed out from the correlation analysis. "
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    ABSTRACT: Cortisol awakening response (CAR) is the cortisol secretory activity in the first 30-60 minutes immediately after awakening in the morning. Alterations in CAR as a trait have been associated with changes in the brain structure and function. CAR also fluctuates over days. Little, however, is known about the relationship between CAR as a state and brain activity. Using resting-state functional magnetic resonance imaging (fMRI), we investigated whether the CAR predicts intrinsic functional connectivity (FC) of the brain in the afternoon of the same day. Data from forty-nine healthy participants were analyzed. Salivary cortisol levels were assessed immediately after awakening and 15, 30 and 60 minutes after awakening, and resting-state fMRI data were obtained in the afternoon. Global FC strength (FCS) of each voxel was computed to provide a whole-brain characterization of intrinsic functional architecture. Correlation analysis was used to examine whether CAR predicts the intrinsic FC of core brain networks. We observed that the CAR was positively correlated with the FCS of the medial prefrontal cortex (mPFC). Further analysis revealed that higher CAR predicted stronger positive mPFC connectivity with regions in the default mode network. Our findings suggest that the HPA activity after awakening in the early morning may predict intrinsic functional connectivity of mPFC at rest in the afternoon of the same day. Copyright © 2015. Published by Elsevier Inc.
    NeuroImage 08/2015; 122. DOI:10.1016/j.neuroimage.2015.08.016 · 6.36 Impact Factor
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    • "To test for robustness of the significant regions identified by the previous analyses using the whole data set, we performed a halfsplit reliability analysis in the time domain. In other words, for each subject, we split the full-time functional MRI signals into two equal time series, the first half and the second half (Gotts et al., 2012). MA was recalculated and then analysed separately for both data sets with identical methods. "
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    ABSTRACT: Whole-brain voxel-based unbiased resting state functional connectivity was analysed in 418 subjects with autism and 509 matched typically developing individuals. We identified a key system in the middle temporal gyrus/superior temporal sulcus region that has reduced cortical functional connectivity (and increased with the medial thalamus), which is implicated in face expression processing involved in social behaviour. This system has reduced functional connectivity with the ventromedial prefrontal cortex, which is implicated in emotion and social communication. The middle temporal gyrus system is also implicated in theory of mind processing. We also identified in autism a second key system in the precuneus/superior parietal lobule region with reduced functional connectivity, which is implicated in spatial functions including of oneself, and of the spatial environment. It is proposed that these two types of functionality, face expression-related, and of one's self and the environment, are important components of the computations involved in theory of mind, whether of oneself or of others, and that reduced connectivity within and between these regions may make a major contribution to the symptoms of autism. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain.
    Brain 03/2015; 138(5). DOI:10.1093/brain/awv051 · 9.20 Impact Factor
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    • "These experiments found hypo-connectivity within the temporal–parietal junction in a theory of mind task (Kana et al., 2009), the limbic system in a face perception task (Kleinhans et al., 2008), between the frontal and parietal regions in a working memory task (Koshino et al., 2005), and between the frontal, parietal and occipital regions in a cognitive control task (Solomon et al., 2009). However, later task-based fMRI studies found hyper-connectivity in connections involving the posterior superior temporal sulcus in visual search tasks (Shih et al., 2011), the medial temporal lobe in face perception tasks (Welchew et al., 2005), within the left hemisphere in a source recognition task (Noonan et al., 2009), between the inferior frontal gyrus, and between the inferior parietal lobule and the superior temporal sulcus in exploring whole-brain connectivity have included subjects with a wide range of ages, allowing for the possibility that a certain age group was driving the functional connectivity findings in the results (Assaf et al., 2010; Gotts et al., 2012). Therefore, an important gap in the literature concerns the principled examination of functional connectivity alterations in ASD across different developmental stages. "
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    ABSTRACT: Background: Disrupted cortical connectivity is thought to underlie the complex cognitive and behavior profile observed in individuals with autism spectrum disorder (ASD). Previous neuroimaging research has identified patterns of both functional hypo- and hyper-connectivity in individuals with ASD. A recent theory attempting to reconcile conflicting results in the literature proposes that hyper-connectivity of brain networks may be more characteristic of young children with ASD, while hypo-connectivity may be more prevalent in adolescents and adults with the disorder when compared to typical development (TD) (Uddin etal., 2013). Previous work has examined only young children, mixed groups of children and adolescents, or adult cohorts in separate studies, leaving open the question of developmental influences on functional brain connectivity in ASD. Methods: The current study tests this developmental hypothesis by examining within- and between-network resting state functional connectivity in a large sample of 26 children, 28 adolescents, and 18 adults with ASD and age- and IQ-matchedTD individuals for the first time using an entirely data-driven approach. Independent component analyses (ICA) and dual regression was applied to data from three age cohorts to examine the effects of participant age on patterns of within-networkwhole-brain functional connectivity in individuals with ASD compared with TD individuals. Between-network connectivity differences were examined for each age cohort by comparing correlations between ICA components across groups. Results: We find that in the youngest cohort (age 11 and under), children with ASD exhibit hyper-connectivity within large-scale brain networks as well as decreased between-network connectivity compared with age-matchedTD children. In contrast, adolescents with ASD (age 11-18) do not differ from TD adolescents in within-network connectivity, yet show decreased between-network connectivity compared with TD adolescents. Adults with ASD show no within- or between-network differences in functional network connectivity compared with neurotypical age-matched individuals. Conclusions: Characterizing within- and between-network functional connectivity in age-stratified cohorts of individuals with ASD and TD individuals demonstrates that functional connectivity atypicalities in the disorder are not uniform across the lifespan. These results demonstrate how explicitly characterizing participant age and adopting a developmental perspective can lead to a more nuanced understanding of atypicalities of functional brain connectivity in autism.
    Clinical neuroimaging 03/2015; 110. DOI:10.1016/j.nicl.2015.02.024 · 2.53 Impact Factor
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