Convergent Findings of Altered Functional and Structural Brain Connectivity in Individuals with High Functioning Autism: A Multimodal MRI Study

Institute of Clinical Radiology, Ludwig-Maximilians University Munich, Munich, Germany.
PLoS ONE (Impact Factor: 3.23). 06/2013; 8(6):e67329. DOI: 10.1371/journal.pone.0067329
Source: PubMed


Brain tissue changes in autism spectrum disorders seem to be rather subtle and widespread than anatomically distinct. Therefore a multimodal, whole brain imaging technique appears to be an appropriate approach to investigate whether alterations in white and gray matter integrity relate to consistent changes in functional resting state connectivity in individuals with high functioning autism (HFA). We applied diffusion tensor imaging (DTI), voxel-based morphometry (VBM) and resting state functional connectivity magnetic resonance imaging (fcMRI) to assess differences in brain structure and function between 12 individuals with HFA (mean age 35.5, SD 11.4, 9 male) and 12 healthy controls (mean age 33.3, SD 9.0, 8 male). Psychological measures of empathy and emotionality were obtained and correlated with the most significant DTI, VBM and fcMRI findings. We found three regions of convergent structural and functional differences between HFA participants and controls. The right temporo-parietal junction area and the left frontal lobe showed decreased fractional anisotropy (FA) values along with decreased functional connectivity and a trend towards decreased gray matter volume. The bilateral superior temporal gyrus displayed significantly decreased functional connectivity that was accompanied by the strongest trend of gray matter volume decrease in the temporal lobe of HFA individuals. FA decrease in the right temporo-parietal region was correlated with psychological measurements of decreased emotionality. In conclusion, our results indicate common sites of structural and functional alterations in higher order association cortex areas and may therefore provide multimodal imaging support to the long-standing hypothesis of autism as a disorder of impaired higher-order multisensory integration.

Download full-text


Available from: Daniel Keeser
    • "Thus rTPJ might help to differentiate self and other perspectives during ToM but also during imitation. In the case of ASD, structural and functional abnormalities of rTPJ have been linked to social cognition deficits (Castelli et al. 2002; David et al. 2014; Kana et al. 2012; Lombardo et al. 2011; Mueller et al. 2013; Pitskel et al. 2011; Washington et al. 2013). Conversely, recent research suggests that self-other distinction in the emotional domain may be subserved by brain regions that are part of the temporo-parietal cortex, but slightly more anterior to TPJ, namely the right supramarginal gyrus (rSMG). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Autism spectrum disorder (ASD) shows deficits in self-other distinction during theory of mind (ToM). Here we investigated whether ASD patients also show difficulties in self-other distinction during empathy and if potential deficits are linked to dysfunctional resting-state connectivity patterns. In a first study, ASD patients and controls performed an emotional egocentricity paradigm and a ToM task. In the second study, resting-state connectivity of right temporo-parietal junction and right supramarginal gyrus (rSMG) were analysed using a large-scale fMRI data set. ASD patients exhibited deficient ToM but normal emotional egocentricity, which was paralleled by reduced connectivity of regions of the ToM network and unimpaired rSMG network connectivity. These results suggest spared self-other distinction during empathy and an intact rSMG network in ASD.
    No preview · Article · Oct 2015 · Journal of Autism and Developmental Disorders
  • Source
    • "r et al., 2010;Pavuluri et al., 2009;Peterson et al., 2009;Tomasi & Volkow, 2012;Uddin et al., 2008) and ASD (Cherkassky et al., 2006;von dem Hagen et al., 2012;Monk et al., 2009;Weng et al., 2010;Dinstein et al., 2011;Rudie et al., 2012;Assaf et al., 2010;Ebisch et al., 2010;Gotts et al., 2012;Anderson et al. 2011;Kennedy and Courchesne, 2008;Mueller et. 2013). However, increased connectivity has also been identified in both disorders (Monk et al., 2009;Tien et al., 2006;Tomasi & Volkow, 2012;Supekar et al., 2013;Keown et al., 2013;Uddin et al., 2013;Lynch et al., 2013;Washington et al., 2013). Again, direct comparison of the two disorders has been limited so it is unclear in what ways t"
    [Show abstract] [Hide abstract]
    ABSTRACT: Attention-deficit/hyperactive disorder (ADHD) and autism spectrum disorders (ASD) are two of the most common and vexing neurodevelopmental disorders among children. Although the two disorders share many behavioral and neuropsychological characteristics, most MRI studies examine only one of the disorders at a time. Using graph theory combined with structural and functional connectivity, we examined the large-scale network organization among three groups of children: a group with ADHD (8–12 years, n = 20), a group with ASD (7–13 years, n = 16), and typically developing controls (TD) (8–12 years, n = 20). We apply the concept of the rich-club organization, whereby central, highly connected hub regions are also highly connected to themselves. We examine the brain into two different network domains: (1) inside a rich-club network phenomena and (2) outside a rich-club network phenomena. The ASD and ADHD groups had markedly different patterns of rich club and non rich-club connections in both functional and structural data. The ASD group exhibited higher connectivity in structural and functional networks but only inside the rich-club networks. These findings were replicated using the autism brain imaging data exchange dataset with ASD (n = 85) and TD (n = 101). The ADHD group exhibited a lower generalized fractional anisotropy and functional connectivity inside the rich-club networks, but a higher number of axonal fibers and correlation coefficient values outside the rich club. Despite some shared biological features and frequent comorbity, these data suggest ADHD and ASD exhibit distinct large-scale connectivity patterns in middle childhood. Hum Brain Mapp, 2014. © 2014 Wiley Periodicals, Inc.
    Full-text · Article · Aug 2014 · Human Brain Mapping
  • Source
    • "Establishing anatomical connectivity bases to alterations in functional connectivity in autism has been less explored (Just et al. 2007; Kana et al. 2006), although such relationships have been reported in typical population (Greicius et al. 2009). A few recent studies have examined connectivity in ASD using simultaneous DTI and fcMRI (Delmonte et al. 2013; Deshpande et al. 2013; Kana et al. 2012; Mueller et al. 2013; Nair et al. 2013). These studies provide two levels of investigation , although sometimes finding no significant direct relationship between the two. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Autism is a neurodevelopmental disorder that has been associated with atypical brain functioning. Functional connectivity MRI (fcMRI) studies examining neural networks in autism have seen an exponential rise over the last decade. Such investigations have led to the characterization of autism as a distributed neural systems disorder. Studies have found widespread cortical underconnectivity, local overconnectivity, and mixed results suggesting disrupted brain connectivity as a potential neural signature of autism. In this review, we summarize the findings of previous fcMRI studies in autism with a detailed examination of their methodology, in order to better understand its potential and to delineate the pitfalls. We also address how a multimodal neuroimaging approach (incorporating different measures of brain connectivity) may help characterize the complex neurobiology of autism at a global level. Finally, we also address the potential of neuroimaging-based markers in assisting neuropsychological assessment of autism. The quest for a neural marker for autism is still ongoing, yet new findings suggest that aberrant brain connectivity may be a promising candidate.
    Full-text · Article · Feb 2014 · Neuropsychology Review
Show more

Similar Publications