Hyperconnectivity of social brain networks in autism during action-intention judgment.

Deficits in social communication in autism spectrum disorder (ASD) have been documented using neuroimaging techniques such as functional MRI over the past decade. More recently, functional connectivity MRI has revealed altered connectivity in face processing, mentalizing, and mirroring brain networks, networks involved in the social brain in ASD. However, to our knowledge, previous studies have not examined these three networks concurrently. The purpose of the current study was to investigate the functional connectivity of the face processing, mentalizing, and mirroring networks (within each network and across networks) in ASD during an action-intention task in which participants were asked to determine the means and intention of a model's actions. We examined: a) within-network connectivity of each network using an ROI-to-ROI analysis; b) connectivity of each network hub to the rest of the brain using a seed-to-voxel analysis; c) the between-network connectivity of each network hub using ROI-to-ROI analysis; and d) brain-behavior relationships by correlating autism symptoms with brain connectivity. Task-fMRI data were used from 21 participants with ASD and 20 typically developing participants. The ASD group consistently showed significantly greater connectivity between networks and between hub regions to the rest of the brain. Hyperconnectivity in ASD may entail more and widespread resource utilization for accomplishing action-intention judgment.

A Longitudinal Study of Local Gyrification Index in Young Boys With Autism Spectrum Disorder.

Local gyrification index (LGI), a metric quantifying cortical folding, was evaluated in 105 boys with autism spectrum disorder (ASD) and 49 typically developing (TD) boys at 3 and 5 years-of-age. At 3 years-of-age, boys with ASD had reduced gyrification in the fusiform gyrus compared with TD boys. A longitudinal evaluation from 3 to 5 years revealed that while TD boys had stable/decreasing LGI, boys with ASD had increasing LGI in right inferior temporal gyrus, right inferior frontal gyrus, right inferior parietal lobule, and stable LGI in left lingual gyrus. LGI was also examined in a previously defined neurophenotype of boys with ASD and disproportionate megalencephaly. At 3 years-of-age, this subgroup exhibited increased LGI in right dorsomedial prefrontal cortex, cingulate cortex, and paracentral cortex, and left cingulate cortex and superior frontal gyrus relative to TD boys and increased LGI in right paracentral lobule and parahippocampal gyrus, and left precentral gyrus compared with boys with ASD and normal brain size. In summary, this study identified alterations in the pattern and development of LGI during early childhood in ASD. Distinct patterns of alterations in subgroups of boys with ASD suggests that multiple neurophenotypes exist and boys with ASD and disproportionate megalencephaly should be evaluated separately.

What will my child's future hold? phenotypes of intellectual development in 2-8-year-olds with autism spectrum disorder.

We examined phenotypes of autism spectrum disorder (ASD) based on trajectories of intellectual development from early (ages 2-3 ½) to middle (ages 5-8) childhood in a recent clinically ascertained cohort. Participants included 102 children (82 males) initially diagnosed with ASD from the Autism Phenome Project longitudinal sample. Latent class growth analysis was used to identify distinct IQ trajectories. Baseline and developmental course differences among groups were assessed using univariate techniques and repeated measures regression models, respectively. A four class model best represented the data. Using the highest posterior probability, participants were assigned to High Challenges (25.5%), Stable Low (17.6%), Changers (35.3%), and Lesser Challenges (21.6%) groups. The High Challenges and Stable Low groups exhibited persistently low IQ, although, the High Challenges group experienced declines while the Stable Low group's scores remained more constant. Changers showed IQ improvement of > 2 standard deviations. The Lesser Challenges group had IQs in the average range at both times that were about 1 standard deviation higher at T2. In summation, 75% of the participants experienced some relative improvements in intellectual and/or other areas of functioning between ages 2 and 8 years. The Changers group demonstrated the most significant IQ change that was accompanied by adaptive communication improvement and declining externalizing symptoms. Only the Lesser Challenges group showed a significant reduction in ASD symptom severity, such that by age 8, 14% of them no longer met ADOS-2 criteria for ASD. All groups showed reductions in internalizing symptoms. Intervention history was not associated with group status. Autism Res 2018, 11: 121-132. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: We examined how the IQs of children with autism spectrum disorder change between ages 2 and 8, and identified four patterns. Two groups exhibited persistently lower IQs. One group showed IQ increases of greater than 30 points with improved communicate abilities and declining disruptive behaviors. The final group had IQs in the average or better range at both time points, and 14% of them lost their diagnoses. Over half of the children experienced improved intellectual functioning between ages 2 and 8, whereas about 25% showed declines. Findings were not associated with intervention history.

White Matter Diffusion of Major Fiber Tracts Implicated in Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder found to have widespread alterations in the function and synchrony of brain regions. These differences may underlie alterations in microstructural organization, such as in white matter pathways. To investigate the diffusion of major white matter tracts, the current study examined multiple indices of white matter diffusion in 42 children and adults with ASD and 44 typically developing (TD) age- and IQ-matched peers using diffusion tensor imaging. Diffusivity measures were compared between groups for the following tracts: bilateral cingulum bundle, corpus callosum, inferior longitudinal fasciculus, superior longitudinal fasciculus, and uncinate fasciculus. Results indicate a significant reduction in fractional anisotropy (FA) for the left superior longitudinal fasciculus (LSLF) in ASD children and adults compared with TD peers. A significant increase in radial diffusivity for ASD participants was also found in the same cluster along the LSLF. In addition, a significant positive correlation emerged for all subjects between FA for the LSLF and age, with FA increasing with age. These findings point to a significant alteration in long-distance white matter connectivity in children and adults with ASD, potentially underscoring the relationship between alterations in white matter diffusion and the ASD phenotype. These results also suggest that the white matter alterations in autism may be subtle and related to the developmental trajectory.

Persistence of megalencephaly in a subgroup of young boys with autism spectrum disorder.

A recurring finding in autism spectrum disorder research is that head and brain growth is disproportionate to body growth in early childhood. Nordahl et al. (2011) demonstrated that this occurs in approximately 15% of boys with autism. While the literature suggests that brain growth normalizes at older ages, this has never been evaluated in a longitudinal study. The current study evaluated head circumference and total cerebral volume in 129 male children with autism and 49 age-matched, typically developing controls. We determined whether 3-year-old boys with brain size disproportionate to height (which we call disproportionate megalencephaly) demonstrated an abnormal trajectory of head growth from birth and whether they maintained an enlarged brain at 5 years of age. Findings were based on longitudinal, structural MRI data collected around 3, 4, and 5 years of age and head circumference data from medical records. At 3 years of age, 19 boys with autism had enlarged brains while 110 had brain sizes in the normal range. Boys with disproportionate megalencephaly had greater total cerebral, gray matter, and white matter volumes from 3-5 years compared to boys with autism and normal sized brains and typically developing boys, but no differences in body size. While head circumference did not differ between groups at birth, it was significantly greater in the disproportionate megalencephaly group by around 2 years. These data suggest that there is a subgroup of boys with autism who have brains disproportionate to body size and that this continues until at least 5 years of age. Autism Res 2016, 9: 1169-1182. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Neuroanatomical and neurofunctional markers of social cognition in autism spectrum disorder.

Social impairments in autism spectrum disorder (ASD), a hallmark feature of its diagnosis, may underlie specific neural signatures that can aid in differentiating between those with and without ASD. To assess common and consistent patterns of differences in brain responses underlying social cognition in ASD, this study applied an activation likelihood estimation (ALE) meta-analysis to results from 50 neuroimaging studies of social cognition in children and adults with ASD. In addition, the group ALE clusters of activation obtained from this was used as a social brain mask to perform surface-based cortical morphometry (SBM) in an empirical structural MRI dataset collected from 55 ASD and 60 typically developing (TD) control participants. Overall, the ALE meta-analysis revealed consistent differences in activation in the posterior superior temporal sulcus at the temporoparietal junction, middle frontal gyrus, fusiform face area (FFA), inferior frontal gyrus (IFG), amygdala, insula, and cingulate cortex between ASD and TD individuals. SBM analysis showed alterations in the thickness, volume, and surface area in individuals with ASD in STS, insula, and FFA. Increased cortical thickness was found in individuals with ASD, the IFG. The results of this study provide functional and anatomical bases of social cognition abnormalities in ASD by identifying common signatures from a large pool of neuroimaging studies. These findings provide new insights into the quest for a neuroimaging-based marker for ASD. Hum Brain Mapp 37:3957-3978, 2016. © 2016 Wiley Periodicals, Inc.

Biochemistry of the cingulate cortex in autism: An MR spectroscopy study.

Neuroimaging studies have uncovered structural and functional alterations in the cingulate cortex in individuals with autism spectrum disorders (ASD). Such abnormalities may underlie neurochemical imbalance. In order to characterize the neurochemical profile, the current study examined the concentration of brain metabolites in dorsal ACC (dACC) and posterior cingulate cortex (PCC) in high-functioning adults with ASD. Twenty high-functioning adults with ASD and 20 age-and-IQ-matched typically developing (TD) peers participated in this Proton magnetic resonance spectroscopy (1H-MRS) study. LCModel was used in analyzing the spectra to measure the levels of N-Acetyl aspartate (NAA), choline (Cho), creatine (Cr), and glutamate/glutamine (Glx) in dACC and PCC. Groups were compared using means for the ratio of each metabolite to their respective Cr levels as well as on absolute internal-water-referenced measures of each metabolite. There was a significant increase in Cho in PCC for ASD adults, with a marginal increase in dACC. A reduction in NAA/Cr in dACC was found in ASD participants, compared to their TD peers. No significant differences in Glx/Cr or Cho/Cr were found in dACC. There were no statistically significant group differences in the absolute concentration of NAA, Cr, Glx, or NAA/Cr, Cho/Cr, and Glx/Cr in the PCC. Differences in the metabolic properties of dACC compared to PCC were also found. Results of this study provide evidence for possible cellular and metabolic differences in the dACC and PCC in adults with ASD. This may suggest neuronal dysfunction in these regions and may contribute to the neuropathology of ASD. Autism Res 2016, 9: 643-657. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

Multimodal neuroimaging based classification of autism spectrum disorder using anatomical, neurochemical, and white matter correlates.

Neuroimaging techniques, such as fMRI, structural MRI, diffusion tensor imaging (DTI), and proton magnetic resonance spectroscopy (1H-MRS) have uncovered evidence for widespread functional and anatomical brain abnormalities in autism spectrum disorder (ASD) suggesting it to be a system-wide neural systems disorder. Nevertheless, most previous studies have focused on examining one index of neuropathology through a single neuroimaging modality, and seldom using multiple modalities to examine the same cohort of individuals. The current study aims to bring together multiple brain imaging modalities (structural MRI, DTI, and 1H-MRS) to investigate the neural architecture in the same set of individuals (19 high-functioning adults with ASD and 18 typically developing (TD) peers). Morphometry analysis revealed increased cortical thickness in ASD participants, relative to typical controls, across the left cingulate, left pars opercularis of the inferior frontal gyrus, left inferior temporal cortex, and right precuneus, and reduced cortical thickness in right cuneus and right precentral gyrus. ASD adults also had reduced fractional anisotropy (FA) and increased radial diffusivity (RD) for two clusters on the forceps minor of the corpus callosum, revealed by DTI analyses. 1H-MRS results showed a reduction in the N-acetylaspartate/Creatine ratio in dorsal anterior cingulate cortex (dACC) in ASD participants. A decision tree classification analysis across the three modalities resulted in classification accuracy of 91.9% with FA, RD, and cortical thickness as key predictors. Examining the same cohort of adults with ASD and their TD peers, this study found alterations in cortical thickness, white matter (WM) connectivity, and neurochemical concentration in ASD. These findings underscore the potential for multimodal imaging to better inform on the neural characteristics most relevant to the disorder.

The role of mirroring and mentalizing networks in mediating action intentions in autism.

BACKGROUND: The ability to interpret agents' intent from their actions is a vital skill in successful social interaction. However, individuals with autism spectrum disorders (ASD) have been found to have difficulty in attributing intentions to others. The present study investigated the neural mechanisms of inferring intentions from actions in individuals with ASD. METHODS: Functional magnetic resonance imaging (fMRI) data were acquired from 21 high-functioning young adults with ASD and 22 typically developing (TD) control participants, while making judgments about the means (how an action is performed) and intention (why an action is performed) of a model's actions. RESULTS: Across both groups of participants, the middle and superior temporal cortex, extending to temporoparietal junction, and posterior cingulate cortex, responded significantly to inferring the intent of an action, while inferior parietal lobule and occipital cortices were active for judgments about the means of an action. Participants with ASD had significantly reduced activation in calcarine sulcus and significantly increased activation in left inferior frontal gyrus, compared to TD peers, while attending to the intentions of actions. Also, ASD participants had weaker functional connectivity between frontal and posterior temporal regions while processing intentions. CONCLUSIONS: These results suggest that processing actions and intentions may not be mutually exclusive, with reliance on mirroring and mentalizing mechanisms mediating action understanding. Overall, inferring information about others' actions involves activation of the mirror neuron system and theory-of-mind regions, and this activation (and the synchrony between activated brain regions) appears altered in young adults with ASD.

Surface-based morphometry of the cortical architecture of autism spectrum disorders: volume, thickness, area, and gyrification.

Structural neuroimaging studies of autism spectrum disorder (ASD) have uncovered widespread neuroanatomical abnormalities, which may have a significant impact on brain function, connectivity, and on behavioral symptoms of autism. The findings of previous structural MRI studies have largely been distributed across several brain areas, with limited consistency. The current study examined neuroanatomical abnormalities by comparing surface-based measures of cortical morphology (CT: cortical thickness, CSA: cortical surface area, CV: cortical volume, and GI: gyrification index) in 55 high-functioning children and adults with ASD to 60 age-and-IQ-matched typically developing (TD) peers. A few brain areas, the fusiform gyrus (FG), middle temporal gyrus (MTG), and inferior frontal gyrus (IFG), emerged to be primarily different in their morphology between the two groups. Compared to TD participants, ASD participants had significantly smaller CV in left MTG, reduced CSA in bilateral MTG and FG, reduced GI in left supramarginal gyrus, and significantly increased CT in the pars opercularis of the IFG. As a function of age, ASD participants had significant reductions in: CT in the pars opercularis, CSA of the left rostral middle frontal gyrus, and GI for left supramarginal gyrus. Thus, alterations in cortical morphology in ASD were seen primarily in regions that are considered part of the social brain. Overall, these findings point to: neuroanatomical alterations in social brain areas, developmental differences in neuroanatomy, and the need to study neuroanatomy at multiple levels in order to better characterize the cortical architecture of ASD.

Attribution of emotions to body postures: an independent component analysis study of functional connectivity in autism.

The ability to interpret others' body language is a vital skill that helps us infer their thoughts and emotions. However, individuals with autism spectrum disorder (ASD) have been found to have difficulty in understanding the meaning of people's body language, perhaps leading to an overarching deficit in processing emotions. The current fMRI study investigates the functional connectivity underlying emotion and action judgment in the context of processing body language in high-functioning adolescents and young adults with autism, using an independent components analysis (ICA) of the fMRI time series. While there were no reliable group differences in brain activity, the ICA revealed significant involvement of occipital and parietal regions in processing body actions; and inferior frontal gyrus, superior medial prefrontal cortex, and occipital cortex in body expressions of emotions. In a between-group analysis, participants with autism, relative to typical controls, demonstrated significantly reduced temporal coherence in left ventral premotor cortex and right superior parietal lobule while processing emotions. Participants with ASD, on the other hand, showed increased temporal coherence in left fusiform gyrus while inferring emotions from body postures. Finally, a positive predictive relationship was found between empathizing ability and the brain areas underlying emotion processing in ASD participants. These results underscore the differential role of frontal and parietal brain regions in processing emotional body language in autism.

Functional brain networks and white matter underlying theory-of-mind in autism.

Human beings constantly engage in attributing causal explanations to one's own and to others' actions, and theory-of-mind (ToM) is critical in making such inferences. Although children learn causal attribution early in development, children with autism spectrum disorders (ASDs) are known to have impairments in the development of intentional causality. This functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) study investigated the neural correlates of physical and intentional causal attribution in people with ASDs. In the fMRI scanner, 15 adolescents and adults with ASDs and 15 age- and IQ-matched typically developing peers made causal judgments about comic strips presented randomly in an event-related design. All participants showed robust activation in bilateral posterior superior temporal sulcus at the temporo-parietal junction (TPJ) in response to intentional causality. Participants with ASDs showed lower activation in TPJ, right inferior frontal gyrus and left premotor cortex. Significantly weaker functional connectivity was also found in the ASD group between TPJ and motor areas during intentional causality. DTI data revealed significantly reduced fractional anisotropy in ASD participants in white matter underlying the temporal lobe. In addition to underscoring the role of TPJ in ToM, this study found an interaction between motor simulation and mentalizing systems in intentional causal attribution and its possible discord in autism.

Identification of neural connectivity signatures of autism using machine learning.

Alterations in interregional neural connectivity have been suggested as a signature of the pathobiology of autism. There have been many reports of functional and anatomical connectivity being altered while individuals with autism are engaged in complex cognitive and social tasks. Although disrupted instantaneous correlation between cortical regions observed from functional MRI is considered to be an explanatory model for autism, the causal influence of a brain area on another (effective connectivity) is a vital link missing in these studies. The current study focuses on addressing this in an fMRI study of Theory-of-Mind (ToM) in 15 high-functioning adolescents and adults with autism and 15 typically developing control participants. Participants viewed a series of comic strip vignettes in the MRI scanner and were asked to choose the most logical end to the story from three alternatives, separately for trials involving physical and intentional causality. The mean time series, extracted from 18 activated regions of interest, were processed using a multivariate autoregressive model (MVAR) to obtain the causality matrices for each of the 30 participants. These causal connectivity weights, along with assessment scores, functional connectivity values, and fractional anisotropy obtained from DTI data for each participant, were submitted to a recursive cluster elimination based support vector machine classifier to determine the accuracy with which the classifier can predict a novel participant's group membership (autism or control). We found a maximum classification accuracy of 95.9% with 19 features which had the highest discriminative ability between the groups. All of the 19 features were effective connectivity paths, indicating that causal information may be critical in discriminating between autism and control groups. These effective connectivity paths were also found to be significantly greater in controls as compared to ASD participants and consisted predominantly of outputs from the fusiform face area and middle temporal gyrus indicating impaired connectivity in ASD participants, particularly in the social brain areas. These findings collectively point toward the fact that alterations in causal connectivity in the brain in ASD could serve as a potential non-invasive neuroimaging signature for autism.

Disrupted cortical connectivity theory as an explanatory model for autism spectrum disorders.

Recent findings of neurological functioning in autism spectrum disorder (ASD) point to altered brain connectivity as a key feature of its pathophysiology. The cortical underconnectivity theory of ASD (Just et al., 2004) provides an integrated framework for addressing these new findings. This theory suggests that weaker functional connections among brain areas in those with ASD hamper their ability to accomplish complex cognitive and social tasks successfully. We will discuss this theory, but will modify the term underconnectivity to 'disrupted cortical connectivity' to capture patterns of both under- and over-connectivity in the brain. In this paper, we will review the existing literature on ASD to marshal supporting evidence for hypotheses formulated on the disrupted cortical connectivity theory. These hypotheses are: 1) underconnectivity in ASD is manifested mainly in long-distance cortical as well as subcortical connections rather than in short-distance cortical connections; 2) underconnectivity in ASD is manifested only in complex cognitive and social functions and not in low-level sensory and perceptual tasks; 3) functional underconnectivity in ASD may be the result of underlying anatomical abnormalities, such as problems in the integrity of white matter; 4) the ASD brain adapts to underconnectivity through compensatory strategies such as overconnectivity mainly in frontal and in posterior brain areas. This may be manifested as deficits in tasks that require frontal-parietal integration. While overconnectivity can be tested by examining the cortical minicolumn organization, long-distance underconnectivity can be tested by cognitively demanding tasks; and 5) functional underconnectivity in brain areas in ASD will be seen not only during complex tasks but also during task-free resting states. We will also discuss some empirical predictions that can be tested in future studies, such as: 1) how disrupted connectivity relates to cognitive impairments in skills such as Theory-of-Mind, cognitive flexibility, and information processing; and 2) how connection abnormalities relate to, and may determine, behavioral symptoms hallmarked by the triad of Impairments in ASD. Furthermore, we will relate the disrupted cortical connectivity model to existing cognitive and neural models of ASD.

Probing the brain in autism using FMRI and diffusion tensor imaging.

Newly emerging theories suggest that the brain does not function as a cohesive unit in autism, and this discordance is reflected in the behavioral symptoms displayed by individuals with autism. While structural neuroimaging findings have provided some insights into brain abnormalities in autism, the consistency of such findings is questionable. Functional neuroimaging, on the other hand, has been more fruitful in this regard because autism is a disorder of dynamic processing and allows examination of communication between cortical networks, which appears to be where the underlying problem occurs in autism. Functional connectivity is defined as the temporal correlation of spatially separate neurological events. Findings from a number of recent fMRI studies have supported the idea that there is weaker coordination between different parts of the brain that should be working together to accomplish complex social or language problems. One of the mysteries of autism is the coexistence of deficits in several domains along with relatively intact, sometimes enhanced, abilities. Such complex manifestation of autism calls for a global and comprehensive examination of the disorder at the neural level. A compelling recent account of the brain functioning in autism, the cortical underconnectivity theory, provides an integrating framework for the neurobiological bases of autism. The cortical underconnectivity theory of autism suggests that any language, social, or psychological function that is dependent on the integration of multiple brain regions is susceptible to disruption as the processing demand increases. In autism, the underfunctioning of integrative circuitry in the brain may cause widespread underconnectivity. In other words, people with autism may interpret information in a piecemeal fashion at the expense of the whole. Since cortical underconnectivity among brain regions, especially the frontal cortex and more posterior areas, has now been relatively well established, we can begin to further understand brain connectivity as a critical component of autism symptomatology. A logical next step in this direction is to examine the anatomical connections that may mediate the functional connections mentioned above. Diffusion Tensor Imaging (DTI) is a relatively novel neuroimaging technique that helps probe the diffusion of water in the brain to infer the integrity of white matter fibers. In this technique, water diffusion in the brain is examined in several directions using diffusion gradients. While functional connectivity provides information about the synchronization of brain activation across different brain areas during a task or during rest, DTI helps in understanding the underlying axonal organization which may facilitate the cross-talk among brain areas. This paper will describe these techniques as valuable tools in understanding the brain in autism and the challenges involved in this line of research.