Fractionation of social brain circuits in autism spectrum disorders

Connectomics in psychiatric research: advances and applications

Psychiatric disorders disturb higher cognitive functions and severely compromise human health. However, the pathophysiological mechanisms underlying psychiatric disorders are very complex, and understanding these mechanisms remains a great challenge. Currently, many psychiatric disorders are hypothesized to reflect "faulty wiring" or aberrant connectivity in the brains. Imaging connectomics is arising as a promising methodological framework for describing the structural and functional connectivity patterns of the human brain. Recently, alterations of brain networks in the connectome have been reported in various psychiatric disorders, and these alterations may provide biomarkers for disease diagnosis and prognosis for the evaluation of treatment efficacy. Here, we summarize the current achievements in both the structural and functional connectomes in several major psychiatric disorders (eg, schizophrenia, attention-deficit/hyperactivity disorder, and autism) based on multi-modal neuroimaging data. We highlight the current progress in the identification of these alterations and the hypotheses concerning the aberrant brain networks in individuals with psychiatric disorders and discuss the research questions that might contribute to a further mechanistic understanding of these disorders from a connectomic perspective.

Connectivity in Autism: A Review of MRI Connectivity Studies

Autism spectrum disorder (ASD) affects 1 in 50 children between the ages of 6 and 17 years. The etiology of ASD is not precisely known. ASD is an umbrella term, which includes both low- (IQ < 70) and high-functioning (IQ > 70) individuals. A better understanding of the disorder and how it manifests in individual subjects can lead to more effective intervention plans to fulfill the individual's treatment needs.Magnetic resonance imaging (MRI) is a non-invasive investigational tool that can be used to study the ways in which the brain develops or deviates from the typical developmental trajectory. MRI offers insights into the structure, function, and metabolism of the brain. In this article, we review published studies on brain connectivity changes in ASD using either resting state functional MRI or diffusion tensor imaging.The general findings of decreases in white matter integrity and in long-range neural coherence are well known in the ASD literature. Nevertheless, the detailed localization of these findings remains uncertain, and few studies link these changes in connectivity with the behavioral phenotype of the disorder. With the help of data sharing and large-scale analytic efforts, however, the field is advancing toward several convergent themes, including the reduced functional coherence of long-range intra-hemispheric cortico-cortical default mode circuitry, impaired inter-hemispheric regulation, and an associated, perhaps compensatory, increase in local and short-range cortico-subcortical coherence.

Neural targets in the study and treatment of social cognition in autism spectrum disorder

The purpose of this chapter is to present results from recent research on social cognition in autism spectrum disorder (ASD). The clinical phenomenology and neuroanatomical circuitry of ASD are first briefly described. The neuropharmacology of social cognition in animal models of ASD and humans is then addressed. Next, preclinical and clinical research on the neurohormone oxytocin is reviewed. This is followed by a presentation of results from preclinical and clinical studies on the excitatory amino acid glutamate. Finally, the role of neuroinflammation in ASD is addressed from the perspectives of preclinical neuroscience and research involving humans with ASD.

Functional connectivity classification of autism identifies highly predictive brain features but falls short of biomarker standards

Objectives

Autism spectrum disorders (ASD) are diagnosed based on early-manifesting clinical symptoms, including markedly impaired social communication. We assessed the viability of resting-state functional MRI (rs-fMRI) connectivity measures as diagnostic biomarkers for ASD and investigated which connectivity features are predictive of a diagnosis.

Methods

Rs-fMRI scans from 59 high functioning males with ASD and 59 age- and IQ-matched typically developing (TD) males were used to build a series of machine learning classifiers. Classification features were obtained using 3 sets of brain regions. Another set of classifiers was built from participants' scores on behavioral metrics. An additional age and IQ-matched cohort of 178 individuals (89 ASD; 89 TD) from the Autism Brain Imaging Data Exchange (ABIDE) open-access dataset (http://fcon_1000.projects.nitrc.org/indi/abide/) were included for replication.

Results

High classification accuracy was achieved through several rs-fMRI methods (peak accuracy 76.67%). However, classification via behavioral measures consistently surpassed rs-fMRI classifiers (peak accuracy 95.19%). The class probability estimates, P(ASD|fMRI data), from brain-based classifiers significantly correlated with scores on a measure of social functioning, the Social Responsiveness Scale (SRS), as did the most informative features from 2 of the 3 sets of brain-based features. The most informative connections predominantly originated from regions strongly associated with social functioning.

Conclusions

While individuals can be classified as having ASD with statistically significant accuracy from their rs-fMRI scans alone, this method falls short of biomarker standards. Classification methods provided further evidence that ASD functional connectivity is characterized by dysfunction of large-scale functional networks, particularly those involved in social information processing.

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We distinguish rs-fMRI scans from ASD and TD individuals with high accuracy.

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ASD versus TD classification using behavioral metrics was much more accurate.

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Highly predictive brain features largely originated from the canonical social brain.

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High performing brain features also correlated with individual symptom severity.

Cerebro-cerebellar connectivity is increased in primary lateral sclerosis

Increased functional connectivity in resting state networks was found in several studies of patients with motor neuron disorders, although diffusion tensor imaging studies consistently show loss of white matter integrity. To understand the relationship between structural connectivity and functional connectivity, we examined the structural connections between regions with altered functional connectivity in patients with primary lateral sclerosis (PLS), a long-lived motor neuron disease. Connectivity matrices were constructed from resting state fMRI in 16 PLS patients to identify areas of differing connectivity between patients and healthy controls. Probabilistic fiber tracking was used to examine structural connections between regions of differing connectivity. PLS patients had 12 regions with increased functional connectivity compared to controls, with a predominance of cerebro-cerebellar connections. Increased functional connectivity was strongest between the cerebellum and cortical motor areas and between the cerebellum and frontal and temporal cortex. Fiber tracking detected no difference in connections between regions with increased functional connectivity. We conclude that functional connectivity changes are not strongly based in structural connectivity. Increased functional connectivity may be caused by common inputs, or by reduced selectivity of cortical activation, which could result from loss of intracortical inhibition when cortical afferents are intact.

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Functional connectivity is increased in primary lateral sclerosis.

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Functional connections with the cerebellum were prominent.

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Cortico-cerebellar connectivity correlated with clinical measures.

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No corresponding changes occurred in structural connectivity.

Altered white matter connectivity as a neural substrate for social impairment in Autism Spectrum Disorder

BACKGROUND

Autism Spectrum Disorder (ASD) symptoms have been hypothesized to result from altered brain connectivity. The 'disconnectivity' hypothesis has been used to explain characteristic impairments in socio-emotional function, observed clinically in ASD. Here, we review the evidence for impaired white matter connectivity as a neural substrate for socio-emotional dysfunction in ASD. A review of diffusion tensor imaging (DTI) studies, and focused discussion of relevant post-mortem, structural, and functional neuroimaging studies, is provided.

METHODS

Studies were identified using a sensitive search strategy in MEDLINE, Embase and PsycINFO article databases using the OvidSP database interface. Search terms included database subject headings for the concepts of pervasive developmental disorders, and DTI. Seventy-two published DTI studies examining white matter microstructure in ASD were reviewed. A comprehensive discussion of DTI studies that examined white matter tracts linking socio-emotional structures is presented.

RESULTS

Several DTI studies reported microstructural differences indicative of developmental alterations in white matter organization, and potentially myelination, in ASD. Altered structure within long-range white matter tracts linking socio-emotional processing regions was implicated. While alterations of the uncinate fasciculus and frontal and temporal thalamic projections have been associated with social symptoms in ASD, few studies examined association of tract microstructure with core impairment in this disorder.

CONCLUSIONS

The uncinate fasciculus and frontal and temporal thalamic projections mediate limbic connectivity and integrate structures responsible for complex socio-emotional functioning. Impaired development of limbic connectivity may represent one neural substrate contributing to ASD social impairments. Future efforts to further elucidate the nature of atypical white matter development, and its relationship to core symptoms, may offer new insights into etiological mechanisms contributing to ASD impairments and uncover novel opportunities for targeted intervention.

Autism spectrum disorder, but not amygdala lesions, impairs social attention in visual search

People with autism spectrum disorders (ASD) have pervasive impairments in social interactions, a diagnostic component that may have its roots in atypical social motivation and attention. One of the brain structures implicated in the social abnormalities seen in ASD is the amygdala. To further characterize the impairment of people with ASD in social attention, and to explore the possible role of the amygdala, we employed a series of visual search tasks with both social (faces and people with different postures, emotions, ages, and genders) and non-social stimuli (e.g., electronics, food, and utensils). We first conducted trial-wise analyses of fixation properties and elucidated visual search mechanisms. We found that an attentional mechanism of initial orientation could explain the detection advantage of non-social targets. We then zoomed into fixation-wise analyses. We defined target-relevant effects as the difference in the percentage of fixations that fell on target-congruent vs. target-incongruent items in the array. In Experiment 1, we tested 8 high-functioning adults with ASD, 3 adults with focal bilateral amygdala lesions, and 19 controls. Controls rapidly oriented to target-congruent items and showed a strong and sustained preference for fixating them. Strikingly, people with ASD oriented significantly less and more slowly to target-congruent items, an attentional deficit especially with social targets. By contrast, patients with amygdala lesions performed indistinguishably from controls. In Experiment 2, we recruited a different sample of 13 people with ASD and 8 healthy controls, and tested them on the same search arrays but with all array items equalized for low-level saliency. The results replicated those of Experiment 1. In Experiment 3, we recruited 13 people with ASD, 8 healthy controls, 3 amygdala lesion patients and another group of 11 controls and tested them on a simpler array. Here our group effect for ASD strongly diminished and all four subject groups showed similar target-relevant effects. These findings argue for an attentional deficit in ASD that is disproportionate for social stimuli, cannot be explained by low-level visual properties of the stimuli, and is more severe with high-load top-down task demands. Furthermore, this deficit appears to be independent of the amygdala, and not evident from general social bias independent of the target-directed search.

Loss of Wdfy3 in mice alters cerebral cortical neurogenesis reflecting aspects of the autism pathology

Autism spectrum disorders (ASDs) are complex and heterogeneous developmental disabilities affecting an ever-increasing number of children worldwide. The diverse manifestations and complex, largely genetic aetiology of ASDs pose a major challenge to the identification of unifying neuropathological features. Here we describe the neurodevelopmental defects in mice that carry deleterious alleles of the Wdfy3 gene, recently recognized as causative in ASDs. Loss of Wdfy3 leads to a regionally enlarged cerebral cortex resembling early brain overgrowth described in many children on the autism spectrum. In addition, affected mouse mutants display migration defects of cortical projection neurons, a recognized cause of epilepsy, which is significantly comorbid with autism. Our analysis of affected mouse mutants defines an important role for Wdfy3 in regulating neural progenitor divisions and neural migration in the developing brain. Furthermore, Wdfy3 is essential for cerebral expansion and functional organization while its loss-of-function results in pathological changes characteristic of ASDs.

Loss of mTOR-dependent macroautophagy causes autistic-like synaptic pruning deficits

Developmental alterations of excitatory synapses are implicated in autism spectrum disorders (ASDs). Here, we report increased dendritic spine density with reduced developmental spine pruning in layer V pyramidal neurons in postmortem ASD temporal lobe. These spine deficits correlate with hyperactivated mTOR and impaired autophagy. In Tsc2 ± ASD mice where mTOR is constitutively overactive, we observed postnatal spine pruning defects, blockade of autophagy, and ASD-like social behaviors. The mTOR inhibitor rapamycin corrected ASD-like behaviors and spine pruning defects in Tsc2 ± mice, but not in Atg7(CKO) neuronal autophagy-deficient mice or Tsc2 ± :Atg7(CKO) double mutants. Neuronal autophagy furthermore enabled spine elimination with no effects on spine formation. Our findings suggest that mTOR-regulated autophagy is required for developmental spine pruning, and activation of neuronal autophagy corrects synaptic pathology and social behavior deficits in ASD models with hyperactivated mTOR.

Structural and functional connectivity of the human brain in autism spectrum disorders and attention-deficit/hyperactivity disorder: A rich club-organization study

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.

A direct amygdala-motor pathway for emotional displays to influence action: A diffusion tensor imaging study

An important evolutionary function of emotions is to prime individuals for action. Although functional neuroimaging has provided evidence for such a relationship, little is known about the anatomical substrates allowing the limbic system to influence cortical motor-related areas. Using diffusion-weighted magnetic resonance imaging and probabilistic tractography on a cohort of 40 participants, we provide evidence of a structural connection between the amygdala and motor-related areas (lateral and medial precentral, motor cingulate and primary motor cortices, and postcentral gyrus) in humans. We then compare this connection with the connections of the amygdala with emotion-related brain areas (superior temporal sulcus, fusiform gyrus, orbitofrontal cortex, and lateral inferior frontal gyrus) and determine which amygdala nuclei are at the origin of these projections. Beyond the well-known subcortical influences over automatic and stereotypical emotional behaviors, a direct amygdala-motor pathway might provide a mechanism by which the amygdala can influence more complex motor behaviors.

Individual differences in intrinsic brain connectivity predict decision strategy

When humans are provided with ample time to make a decision, individual differences in strategy emerge. Using an adaptation of a well-studied decision making paradigm, motion direction discrimination, we probed the neural basis of individual differences in strategy. We tested whether strategies emerged from moment-to-moment reconfiguration of functional brain networks involved in decision making with task-evoked functional MRI (fMRI) and whether intrinsic properties of functional brain networks, measured at rest with functional connectivity MRI (fcMRI), were associated with strategy use. We found that human participants reliably selected one of two strategies across 2 days of task performance, either continuously accumulating evidence or waiting for task difficulty to decrease. Individual differences in decision strategy were predicted both by the degree of task-evoked activation of decision-related brain regions and by the strength of pretask correlated spontaneous brain activity. These results suggest that spontaneous brain activity constrains strategy selection on perceptual decisions.

The spatial structure of resting state connectivity stability on the scale of minutes

Resting state functional MRI (rsfMRI) connectivity patterns are not temporally stable, but fluctuate in time at scales shorter than most common rest scan durations (5–10 min). Consequently, connectivity patterns for two different portions of the same scan can differ drastically. To better characterize this temporal variability and understand how it is spatially distributed across the brain, we scanned subjects continuously for 60 min, at a temporal resolution of 1 s, while they rested inside the scanner. We then computed connectivity matrices between functionally-defined regions of interest for non-overlapping 1 min windows, and classified connections according to their strength, polarity, and variability. We found that the most stable connections correspond primarily to inter-hemispheric connections between left/right homologous ROIs. However, only 32% of all within-network connections were classified as most stable. This shows that resting state networks have some long-term stability, but confirms the flexible configuration of these networks, particularly those related to higher order cognitive functions. The most variable connections correspond primarily to inter-hemispheric, across-network connections between non-homologous regions in occipital and frontal cortex. Finally we found a series of connections with negative average correlation, but further analyses revealed that such average negative correlations may be related to the removal of CSF signals during pre-processing. Using the same dataset, we also evaluated how similarity of within-subject whole-brain connectivity matrices changes as a function of window duration (used here as a proxy for scan duration). Our results suggest scanning for a minimum of 10 min to optimize within-subject reproducibility of connectivity patterns across the entire brain, rather than a few predefined networks.

The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism

Autism spectrum disorders (ASDs) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, lifelong nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. Although the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE)-a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) data sets with corresponding structural MRI and phenotypic information from 539 individuals with ASDs and 573 age-matched typical controls (TCs; 7-64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 male subjects with ASDs and 403 male age-matched TCs. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo- and hyperconnectivity in the ASD literature; both were detected, although hypoconnectivity dominated, particularly for corticocortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASDs (mid- and posterior insula and posterior cingulate cortex), and highlighted less commonly explored regions such as the thalamus. The survey of the ABIDE R-fMRI data sets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international data sets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies.

Annual research review: Towards a developmental neuroscience of atypical social cognition

As a starting point for our review we use a developmental timeline, starting from birth and divided into major developmental epochs defined by key milestones of social cognition in typical development. For each epoch, we highlight those developmental disorders that diverge from the normal developmental pattern, what is known about these key milestones in the major disorders affecting social cognition, and any available research on the neural basis of these differences. We relate behavioural observations to four major networks of the social brain, that is, Amygdala, Mentalizing, Emotion and Mirror networks. We focus on those developmental disorders that are characterized primarily by social atypicality, such as autism spectrum disorder, social anxiety and a variety of genetically defined syndromes. The processes and aspects of social cognition we highlight are sketched in a putative network diagram, and include: agent identification, emotion processing and empathy, mental state attribution, self-processing and social hierarchy mapping involving social ‘policing’ and in-group/out-group categorization. Developmental disorders reveal some dissociable deficits in different components of this map of social cognition. This broad review across disorders, ages and aspects of social cognition leads us to some key questions: How can we best distinguish primary from secondary social disorders? Is social cognition especially vulnerable to developmental disorder, or surprisingly robust? Are cascading notions of social development, in which early functions are essential stepping stones or building bricks for later abilities, necessarily correct?

The implications of brain connectivity in the neuropsychology of autism

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.

Abnormal lateralization of functional connectivity between language and default mode regions in autism

Background

Lateralization of brain structure and function occurs in typical development, and abnormal lateralization is present in various neuropsychiatric disorders. Autism is characterized by a lack of left lateralization in structure and function of regions involved in language, such as Broca and Wernicke areas.

Methods

Using functional connectivity magnetic resonance imaging from a large publicly available sample (n = 964), we tested whether abnormal functional lateralization in autism exists preferentially in language regions or in a more diffuse pattern across networks of lateralized brain regions.

Results

The autism group exhibited significantly reduced left lateralization in a few connections involving language regions and regions from the default mode network, but results were not significant throughout left- and right-lateralized networks. There is a trend that suggests the lack of left lateralization in a connection involving Wernicke area and the posterior cingulate cortex associates with more severe autism.

Conclusions

Abnormal language lateralization in autism may be due to abnormal language development rather than to a deficit in hemispheric specialization of the entire brain.

The relationship between atypical visual processing and social skills in young children with autism

The present study examined whether atypical visual processing is related to the level of social skills in children with autism spectrum disorder (ASD). Thirty-eight young children with ASD (29 boys, 9 girls) were included. Atypical visual processing was assessed by coding the number of lateral glances and the amount of object grouping behavior on videotaped observations of the ADOS (aged 35 ± 9 months). The level of social skills was measured using the subscale interpersonal relationships of the Vineland SEEC (32 ± 7 months). A negative relationship with a medium effect size was found between lateral glances and interpersonal relationships. Object grouping behavior and interpersonal relationships were not related. This study suggests that visual perception may be a mechanism in the development of interpersonal relationships in ASD, which is in accordance with an embodied approach to social cognition.

Resting-state functional connectivity MRI reveals active processes central to cognition

Analysis of spontaneously correlated low-frequency activity fluctuations across the brain using functional magnetic resonance imaging (MRI)-commonly referred to as resting-state functional connectivity (RSFC) MRI-was initially seen as a useful tool for mapping functional-anatomic networks in the living human brain, characterizing brain changes and differences in clinical populations, and studying comparative anatomy across species. However, little was known about the potential relevance of RSFC to cognitive processes. Indeed, there has been considerable controversy and debate as to the utility of studying the resting-state in cognitive neuroscience. However, recent work has shown that RSFC, rather than merely reflecting passive or epiphenomenal activity within underlying functional-anatomic networks, reveals important dynamic processes that play an active role in cognition. RSFC has been associated with individual differences in a number of behavioral and cognitive domains, including perception, language, learning and memory, and the organization of conceptual knowledge. In this article, we review and integrate the latest research demonstrating that RSFC is functionally relevant to human behavior and higher-level cognition, and propose a hypothesis regarding its mechanism of action on functional network dynamics and cognition. We conclude that RSFC MRI will be an invaluable tool for future discovery of the fundamental neurocognitive interactions that underlie cognition. WIREs Cogn Sci 2014, 5:233-245. doi: 10.1002/wcs.1275 CONFLICT OF INTEREST: The authors have declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website.

Single-neuron correlates of atypical face processing in autism

People with autism spectrum disorder (ASD) show abnormal processing of faces. A range of morphometric, histological, and neuroimaging studies suggest the hypothesis that this abnormality may be linked to the amygdala. We recorded data from single neurons within the amygdalae of two rare neurosurgical patients with ASD. While basic electrophysiological response parameters were normal, there were specific and striking abnormalities in how individual facial features drove neuronal response. Compared to control patients, a population of neurons in the two ASD patients responded significantly more to the mouth, but less to the eyes. Moreover, we found a second class of face-responsive neurons for which responses to faces appeared normal. The findings confirm the amygdala's pivotal role in abnormal face processing by people with ASD at the cellular level and suggest that dysfunction may be traced to a specific subpopulation of neurons with altered selectivity for the features of faces.

The amygdala and the relevance detection theory of autism: an evolutionary perspective

In the last few decades there has been increasing interest in the role of the amygdala in psychiatric disorders and, in particular, in its contribution to the socio-emotional impairments in autism spectrum disorders (ASDs). Given that the amygdala is a component structure of the "social brain," several theoretical explanations compatible with amygdala dysfunction have been proposed to account for socio-emotional impairments in ASDs, including abnormal eye contact, gaze monitoring, face processing, mental state understanding, and empathy. Nevertheless, many theoretical accounts, based on the Amygdala Theory of Autism, fail to elucidate the complex pattern of impairments observed in this population, which extends beyond the social domain. As posited by the Relevance Detector theory (Sander et al., 2003), the human amygdala is a critical component of a brain circuit involved in the appraisal of self-relevant events that include, but are not restricted to, social stimuli. Here, we propose that the behavioral and social-emotional features of ASDs may be better understood in terms of a disruption in a "Relevance Detector Network" affecting the processing of stimuli that are relevant for the organism's self-regulating functions. In the present review, we will first summarize the main literature supporting the involvement of the amygdala in socio-emotional disturbances in ASDs. Next, we will present a revised version of the Amygdala Relevance Detector hypothesis and we will show that this theoretical framework can provide a better understanding of the heterogeneity of the impairments and symptomatology of ASDs. Finally, we will discuss some predictions of our model, and suggest new directions in the investigation of the role of the amygdala within the more generally disrupted cortical connectivity framework as a model of neural organization of the autistic brain.

Autistic adolescents show atypical activation of the brain's mentalizing system even without a prior history of mentalizing problems

Some autistic children pass classic Theory of Mind (ToM) tasks that others fail, but the significance of this finding is at present unclear. We identified two such groups of primary school age (labelled ToM+ and ToM-) and a matched comparison group of typically developing children (TD). Five years later we tested these participants again on a ToM test battery appropriate for adolescents and conducted an fMRI study with a story based ToM task. We also assessed autistic core symptoms at these two time points. At both times the ToM- group showed more severe social communication impairments than the ToM+ group, and while showing an improvement in mentalizing performance, they continued to show a significant impairment compared to the NT group. Two independent ROI analyses of the BOLD signal showed activation of the mentalizing network including medial prefrontal cortex, posterior cingulate and lateral temporal cortices. Strikingly, both ToM+ and ToM- groups showed very similar patterns of heightened activation in comparison with the NT group. No differences in other brain regions were apparent. Thus, autistic adolescents who do not have a history of mentalizing problems according to our ToM battery showed the same atypical neurophysiological response during mentalizing as children who did have such a history. This finding indicates that heterogeneity at the behavioural level may nevertheless map onto a similar phenotype at the neuro-cognitive level.

Resting state FMRI research in child psychiatric disorders

Concurring with the shift from linking functions to specific brain areas towards studying network integration, resting state FMRI (R-FMRI) has become an important tool for delineating the functional network architecture of the brain. Fueled by straightforward data collection, R-FMRI analysis methods as well as studies reporting on R-FMRI have flourished, and already impact research on child- and adolescent psychiatric disorders. Here, we review R-FMRI analysis techniques and outline current methodological debates. Furthermore, we provide an overview of the main R-FMRI findings related to child- and adolescent psychiatric disorders. R-FMRI research has contributed significantly to our understanding of brain function in child and adolescent psychiatry: existing hypotheses based on task-based FMRI were confirmed and new insights into the brain's functional architecture of disorders were established. However, results were not always consistent. While resting state networks are robust and reproducible, neuroimaging research in psychiatric disorders is especially complicated by tremendous phenotypic heterogeneity. It is imperative that we overcome this heterogeneity when integrating neuroimaging into the diagnostic and treatment process. As R-FMRI allows investigating the richness of the human functional connectome and can be easily collected and aggregated into large-scale datasets, it is clear that R-FMRI can be a powerful tool in our quest to understand psychiatric pathology.

Age related changes in striatal resting state functional connectivity in autism

Characterizing the nature of developmental change is critical to understanding the mechanisms that are impaired in complex neurodevelopment disorders such as autism spectrum disorder (ASD) and, pragmatically, may allow us to pinpoint periods of plasticity when interventions are particularly useful. Although aberrant brain development has long been theorized as a characteristic feature of ASD, the neural substrates have been difficult to characterize, in part due to a lack of developmental data and to performance confounds. To address these issues, we examined the development of intrinsic functional connectivity, with resting state fMRI from late childhood to early adulthood (8–36 years), using a seed based functional connectivity method with the striatal regions. Overall, we found that both groups show decreases in cortico-striatal circuits over age. However, when controlling for age, ASD participants showed increased connectivity with parietal cortex and decreased connectivity with prefrontal cortex relative to typically developed (TD) participants. In addition, ASD participants showed aberrant age-related connectivity with anterior aspects of cerebellum, and posterior temporal regions (e.g., fusiform gyrus, inferior and superior temporal gyri). In sum, we found prominent differences in the development of striatal connectivity in ASD, most notably, atypical development of connectivity in striatal networks that may underlie cognitive and social reward processing. Our findings highlight the need to identify the biological mechanisms of perturbations in brain reorganization over development, which may also help clarify discrepant findings in the literature.

Brain hyperconnectivity in children with autism and its links to social deficits

Autism spectrum disorder (ASD), a neurodevelopmental disorder affecting nearly 1 in 88 children, is thought to result from aberrant brain connectivity. Remarkably, there have been no systematic attempts to characterize whole-brain connectivity in children with ASD. Here, we use neuroimaging to show that there are more instances of greater functional connectivity in the brains of children with ASD in comparison to those of typically developing children. Hyperconnectivity in ASD was observed at the whole-brain and subsystems levels, across long- and short-range connections, and was associated with higher levels of fluctuations in regional brain signals. Brain hyperconnectivity predicted symptom severity in ASD, such that children with greater functional connectivity exhibited more severe social deficits. We replicated these findings in two additional independent cohorts, demonstrating again that at earlier ages, the brain of children with ASD is largely functionally hyperconnected in ways that contribute to social dysfunction. Our findings provide unique insights into brain mechanisms underlying childhood autism.

Phenotypic variability in resting-state functional connectivity: current status

We reviewed the extant literature with the goal of assessing the extent to which resting-state functional connectivity is associated with phenotypic variability in healthy and disordered populations. A large corpus of work has accumulated to date (125 studies), supporting the association between intrinsic functional connectivity and individual differences in a wide range of domains-not only in cognitive, perceptual, motoric, and linguistic performance, but also in behavioral traits (e.g., impulsiveness, risky decision making, personality, and empathy) and states (e.g., anxiety and psychiatric symptoms) that are distinguished by cognitive and affective functioning, and in neurological conditions with cognitive and motor sequelae. Further, intrinsic functional connectivity is sensitive to remote (e.g., early-life stress) and enduring (e.g., duration of symptoms) life experience, and it exhibits plasticity in response to recent experience (e.g., learning and adaptation) and pharmacological treatment. The most pervasive associations were observed with the default network; associations were also widespread between the cingulo-opercular network and both cognitive and affective behaviors, while the frontoparietal network was associated primarily with cognitive functions. Associations of somatomotor, frontotemporal, auditory, and amygdala networks were relatively restricted to the behaviors linked to their respective putative functions. Surprisingly, visual network associations went beyond visual function to include a variety of behavioral traits distinguished by affective function. Together, the reviewed evidence sets the stage for testing causal hypothesis about the functional role of intrinsic connectivity and augments its potential as a biomarker for healthy and disordered brain function.

Analysis of cortical shape in children with simplex autism

We used surface-based morphometry to test for differences in cortical shape between children with simplex autism (n = 34, mean age 11.4 years) and typical children (n = 32, mean age 11.3 years). This entailed testing for group differences in sulcal depth and in 3D coordinates after registering cortical midthickness surfaces to an atlas target using 2 independent registration methods. We identified bilateral differences in sulcal depth in restricted portions of the anterior-insula and frontal-operculum (aI/fO) and in the temporoparietal junction (TPJ). The aI/fO depth differences are associated with and likely to be caused by a shape difference in the inferior frontal gyrus in children with simplex autism. Comparisons of average midthickness surfaces of children with simplex autism and those of typical children suggest that the significant sulcal depth differences represent local peaks in a larger pattern of regional differences that are below statistical significance when using coordinate-based analysis methods. Cortical regions that are statistically significant before correction for multiple measures are peaks of more extended, albeit subtle regional differences that may guide hypothesis generation for studies using other imaging modalities.

Shared and distinct intrinsic functional network centrality in autism and attention-deficit/hyperactivity disorder

BACKGROUND

Individuals with autism spectrum disorders (ASD) often exhibit symptoms of attention-deficit/hyperactivity disorder (ADHD). Across both disorders, observations of distributed functional abnormalities suggest aberrant large-scale brain network connectivity. Yet, common and distinct network correlates of ASD and ADHD remain unidentified. Here, we aimed to examine patterns of dysconnection in school-age children with ASD and ADHD and typically developing children who completed a resting state functional magnetic resonance imaging scan.

METHODS

We measured voxelwise network centrality, functional connectivity metrics indexing local (degree centrality [DC]) and global (eigenvector centrality) functional relationships across the entire brain connectome, in resting state functional magnetic resonance imaging data from 56 children with ASD, 45 children with ADHD, and 50 typically developing children. A one-way analysis of covariance, with group as fixed factor (whole-brain corrected), was followed by post hoc pairwise comparisons.

RESULTS

Cortical and subcortical areas exhibited centrality abnormalities, some common to both ADHD and ASD, such as in precuneus. Others were disorder-specific and included ADHD-related increases in DC in right striatum/pallidum, in contrast with ASD-related increases in bilateral temporolimbic areas. Secondary analyses differentiating children with ASD into those with or without ADHD-like comorbidity (ASD(+) and ASD(-), respectively) revealed that the ASD(+) group shared ADHD-specific abnormalities in basal ganglia. By contrast, centrality increases in temporolimbic areas characterized children with ASD regardless of ADHD-like comorbidity. At the cluster level, eigenvector centrality group patterns were similar to DC.

CONCLUSIONS

ADHD and ASD are neurodevelopmental disorders with distinct and overlapping clinical presentations. This work provides evidence for both shared and distinct underlying mechanisms at the large-scale network level.

How do shared-representations and emotional processes cooperate in response to social threat signals?

Research in social cognition has mainly focused on the detection and comprehension of others' mental and emotional states. Doing so, past studies have adopted a "contemplative" view of the role of the observer engaged in a social interaction. However, the adaptive problem posed by the social environment is first and foremost that of coordination, which demands more of social cognition beyond mere detection and comprehension of others' hidden states. Offering a theoretical framework that takes into account the dynamical aspect of social interaction - notably by accounting for constant interplay between emotional appraisal and motor processes in socially engaged human brain - thus constitutes an important challenge for the field of social cognition. Here, we propose that our social environment can be seen as presenting opportunities for actions regarding others. Within such a framework, non-verbal social signals such as emotional displays are considered to have evolved to influence the observer in consistent ways. Consequently, social signals can modulate motor responses in observers. In line with this theoretical framework we provide evidence that emotional and motor processes are actually tightly linked during the perception of threat signals. This is ultimately reflected in the human brain by constant interplay between limbic and motor areas.

Underconnectivity of the superior temporal sulcus predicts emotion recognition deficits in autism

Neurodevelopmental disconnections have been assumed to cause behavioral alterations in autism spectrum disorders (ASDs). Here, we combined measurements of intrinsic functional connectivity (iFC) from resting-state functional magnetic resonance imaging (fMRI) with task-based fMRI to explore whether altered activity and/or iFC of the right posterior superior temporal sulcus (pSTS) mediates deficits in emotion recognition in ASD. Fifteen adults with ASD and 15 matched-controls underwent resting-state and task-based fMRI, during which participants discriminated emotional states from point light displays (PLDs). Intrinsic FC of the right pSTS was further examined using 584 (278 ASD/306 controls) resting-state data of the Autism Brain Imaging Data Exchange (ABIDE). Participants with ASD were less accurate than controls in recognizing emotional states from PLDs. Analyses revealed pronounced ASD-related reductions both in task-based activity and resting-state iFC of the right pSTS with fronto-parietal areas typically encompassing the action observation network (AON). Notably, pSTS-hypo-activity was related to pSTS-hypo-connectivity, and both measures were predictive of emotion recognition performance with each measure explaining a unique part of the variance. Analyses with the large independent ABIDE dataset replicated reductions in pSTS-iFC to fronto-parietal regions. These findings provide novel evidence that pSTS hypo-activity and hypo-connectivity with the fronto-parietal AON are linked to the social deficits characteristic of ASD.

Multisite functional connectivity MRI classification of autism: ABIDE results

Background: Systematic differences in functional connectivity MRI metrics have been consistently observed in autism, with predominantly decreased cortico-cortical connectivity. Previous attempts at single subject classification in high-functioning autism using whole brain point-to-point functional connectivity have yielded about 80% accurate classification of autism vs. control subjects across a wide age range. We attempted to replicate the method and results using the Autism Brain Imaging Data Exchange (ABIDE) including resting state fMRI data obtained from 964 subjects and 16 separate international sites.

Methods: For each of 964 subjects, we obtained pairwise functional connectivity measurements from a lattice of 7266 regions of interest covering the gray matter (26.4 million “connections”) after preprocessing that included motion and slice timing correction, coregistration to an anatomic image, normalization to standard space, and voxelwise removal by regression of motion parameters, soft tissue, CSF, and white matter signals. Connections were grouped into multiple bins, and a leave-one-out classifier was evaluated on connections comprising each set of bins. Age, age-squared, gender, handedness, and site were included as covariates for the classifier.

Results: Classification accuracy significantly outperformed chance but was much lower for multisite prediction than for previous single site results. As high as 60% accuracy was obtained for whole brain classification, with the best accuracy from connections involving regions of the default mode network, parahippocampaland fusiform gyri, insula, Wernicke Area, and intraparietal sulcus. The classifier score was related to symptom severity, social function, daily living skills, and verbal IQ. Classification accuracy was significantly higher for sites with longer BOLD imaging times.

Conclusions: Multisite functional connectivity classification of autism outperformed chance using a simple leave-one-out classifier, but exhibited poorer accuracy than for single site results. Attempts to use multisite classifiers will likely require improved classification algorithms, longer BOLD imaging times, and standardized acquisition parameters for possible future clinical utility.

Aberrant neural mediation of verbal fluency in autism spectrum disorders

OBJECTIVE

Contrasts of verbal fluency and automatic speech provide an opportunity to evaluate the neural underpinnings of generativity and flexibility in autism spectrum disorders (ASD).

METHOD

We used functional magnetic resonance imaging (fMRI) to contrast brain activity in high functioning ASD (n=17, mean verbal IQ=117) and neurotypical (NT; n=20, mean verbal IQ=112) adolescent and young adult males (12-23years). Participants responded to three word generation conditions: automatic speech (reciting months), category fluency, and letter fluency.

RESULTS

Our paradigm closely mirrored behavioral fluency tasks by requiring overt, free recall word generation while controlling for differences in verbal output between the groups and systematically increasing the task demand. The ASD group showed reduced neural response compared to the NT participants during fluency tasks in multiple regions of left anterior and posterior cortices, and sub-cortical structures. Six of these regions fell in cortico-striatal circuits previously linked to repetitive behaviors (Langen, Durston, Kas, van Engeland, & Staal, 2011), and activity in two of them (putamen and thalamus) was negatively correlated with autism repetitive behavior symptoms in the ASD group. In addition, response in left inferior frontal gyrus was differentially modulated in the ASD, relative to the NT, group as a function of task demand.

CONCLUSIONS

These data indicate a specific, atypical brain response in ASD to demanding generativity tasks that may have relevance to repetitive behavior symptoms in ASD as well as to difficulties generating original verbal responses.

Methods to detect, characterize, and remove motion artifact in resting state fMRI

Head motion systematically alters correlations in resting state functional connectivity fMRI (RSFC). In this report we examine impact of motion on signal intensity and RSFC correlations. We find that motion-induced signal changes (1) are often complex and variable waveforms, (2) are often shared across nearly all brain voxels, and (3) often persist more than 10s after motion ceases. These signal changes, both during and after motion, increase observed RSFC correlations in a distance-dependent manner. Motion-related signal changes are not removed by a variety of motion-based regressors, but are effectively reduced by global signal regression. We link several measures of data quality to motion, changes in signal intensity, and changes in RSFC correlations. We demonstrate that improvements in data quality measures during processing may represent cosmetic improvements rather than true correction of the data. We demonstrate a within-subject, censoring-based artifact removal strategy based on volume censoring that reduces group differences due to motion to chance levels. We note conditions under which group-level regressions do and do not correct motion-related effects.

Atypical modulation of distant functional connectivity by cognitive state in children with Autism Spectrum Disorders

We examined whether modulation of functional connectivity by cognitive state differed between pre-adolescent children with Autism Spectrum Disorders (ASD) and age and IQ-matched control children. Children underwent functional magnetic resonance imaging (fMRI) during two states, a resting state followed by a sustained attention task. A voxel-wise method was used to characterize functional connectivity at two levels, local (within a voxel's 14 mm neighborhood) and distant (outside of the voxel's 14 mm neighborhood to the rest of the brain) and regions exhibiting Group × State interaction were identified for both types of connectivity maps. Distant functional connectivity of regions in the left frontal lobe (dorsolateral [BA 11, 10]; supplementary motor area extending into dorsal anterior cingulate [BA 32/8]; and premotor [BA 6, 8, 9]), right parietal lobe (paracentral lobule [BA 6]; angular gyrus [BA 39/40]), and left posterior middle temporal cortex (BA 19/39) showed a Group × State interaction such that relative to the resting state, connectivity reduced (i.e., became focal) in control children but increased (i.e., became diffuse) in ASD children during the task state. Higher state-related increase in distant connectivity of left frontal and right angular gyrus predicted worse inattention in ASD children. Two graph theory measures (global efficiency and modularity) were also sensitive to Group × State differences, with the magnitude of state-related change predicting inattention in the ASD children. Our results indicate that as ASD children transition from an unconstrained to a sustained attentional state, functional connectivity of frontal and parietal regions with the rest of the brain becomes more widespread in a manner that may be maladaptive as it was associated with attention problems in everyday life.

Autologous bone marrow mononuclear cell therapy for autism: an open label proof of concept study

Cellular therapy is an emerging therapeutic modality with a great potential for the treatment of autism. Recent findings show that the major underlying pathogenetic mechanisms of autism are hypoperfusion and immune alterations in the brain. So conceptually, cellular therapy which facilitates counteractive processes of improving perfusion by angiogenesis and balancing inflammation by immune regulation would exhibit beneficial clinical effects in patients with autism. This is an open label proof of concept study of autologous bone marrow mononuclear cells (BMMNCs) intrathecal transplantation in 32 patients with autism followed by multidisciplinary therapies. All patients were followed up for 26 months (mean 12.7). Outcome measures used were ISAA, CGI, and FIM/Wee-FIM scales. Positron Emission Tomography-Computed Tomography (PET-CT) scan recorded objective changes. Out of 32 patients, a total of 29 (91%) patients improved on total ISAA scores and 20 patients (62%) showed decreased severity on CGI-I. The difference between pre- and postscores was statistically significant (P < 0.001) on Wilcoxon matched-pairs signed rank test. On CGI-II 96% of patients showed global improvement. The efficacy was measured on CGI-III efficacy index. Few adverse events including seizures in three patients were controlled with medications. The encouraging results of this leading clinical study provide future directions for application of cellular therapy in autism.

Two distinct forms of functional lateralization in the human brain

The hemispheric lateralization of certain faculties in the human brain has long been held to be beneficial for functioning. However, quantitative relationships between the degree of lateralization in particular brain regions and the level of functioning have yet to be established. Here we demonstrate that two distinct forms of functional lateralization are present in the left vs. the right cerebral hemisphere, with the left hemisphere showing a preference to interact more exclusively with itself, particularly for cortical regions involved in language and fine motor coordination. In contrast, right-hemisphere cortical regions involved in visuospatial and attentional processing interact in a more integrative fashion with both hemispheres. The degree of lateralization present in these distinct systems selectively predicted behavioral measures of verbal and visuospatial ability, providing direct evidence that lateralization is associated with enhanced cognitive ability.

Reconceptualizing functional brain connectivity in autism from a developmental perspective

While there is almost universal agreement amongst researchers that autism is associated with alterations in brain connectivity, the precise nature of these alterations continues to be debated. Theoretical and empirical work is beginning to reveal that autism is associated with a complex functional phenotype characterized by both hypo- and hyper-connectivity of large-scale brain systems. It is not yet understood why such conflicting patterns of brain connectivity are observed across different studies, and the factors contributing to these heterogeneous findings have not been identified. Developmental changes in functional connectivity have received inadequate attention to date. We propose that discrepancies between findings of autism related hypo-connectivity and hyper-connectivity might be reconciled by taking developmental changes into account. We review neuroimaging studies of autism, with an emphasis on functional magnetic resonance imaging studies of intrinsic functional connectivity in children, adolescents and adults. The consistent pattern emerging across several studies is that while intrinsic functional connectivity in adolescents and adults with autism is generally reduced compared with age-matched controls, functional connectivity in younger children with the disorder appears to be increased. We suggest that by placing recent empirical findings within a developmental framework, and explicitly characterizing age and pubertal stage in future work, it may be possible to resolve conflicting findings of hypo- and hyper-connectivity in the extant literature and arrive at a more comprehensive understanding of the neurobiology of autism.

Salience network-based classification and prediction of symptom severity in children with autism

IMPORTANCE

Autism spectrum disorder (ASD) affects 1 in 88 children and is characterized by a complex phenotype, including social, communicative, and sensorimotor deficits. Autism spectrum disorder has been linked with atypical connectivity across multiple brain systems, yet the nature of these differences in young children with the disorder is not well understood.

OBJECTIVES

To examine connectivity of large-scale brain networks and determine whether specific networks can distinguish children with ASD from typically developing (TD) children and predict symptom severity in children with ASD.

DESIGN, SETTING, AND PARTICIPANTS

Case-control study performed at Stanford University School of Medicine of 20 children 7 to 12 years old with ASD and 20 age-, sex-, and IQ-matched TD children.

MAIN OUTCOMES AND MEASURES

Between-group differences in intrinsic functional connectivity of large-scale brain networks, performance of a classifier built to discriminate children with ASD from TD children based on specific brain networks, and correlations between brain networks and core symptoms of ASD.

RESULTS

We observed stronger functional connectivity within several large-scale brain networks in children with ASD compared with TD children. This hyperconnectivity in ASD encompassed salience, default mode, frontotemporal, motor, and visual networks. This hyperconnectivity result was replicated in an independent cohort obtained from publicly available databases. Using maps of each individual's salience network, children with ASD could be discriminated from TD children with a classification accuracy of 78%, with 75% sensitivity and 80% specificity. The salience network showed the highest classification accuracy among all networks examined, and the blood oxygen-level dependent signal in this network predicted restricted and repetitive behavior scores. The classifier discriminated ASD from TD in the independent sample with 83% accuracy, 67% sensitivity, and 100% specificity.

CONCLUSIONS AND RELEVANCE

Salience network hyperconnectivity may be a distinguishing feature in children with ASD. Quantification of brain network connectivity is a step toward developing biomarkers for objectively identifying children with ASD.

Correcting brain-wide correlation differences in resting-state FMRI

Brain function in "resting" state has been extensively studied with functional magnetic resonance imaging (FMRI). However, drawing valid inferences, particularly for group comparisons, is fraught with pitfalls. Differing levels of brain-wide correlations can confound group comparisons. Global signal regression (GSReg) attempts to reduce this confound and is commonly used, even though it differentially biases correlations over brain regions, potentially leading to false group differences. We propose to use average brain-wide correlations as a measure of global correlation (GCOR), and examine the circumstances under which it can be used to identify or correct for differences in global fluctuations. In the process, we show the bias induced by GSReg to be a function only of the data's covariance matrix, and use simulations to compare corrections with GCOR as covariate to GSReg under various scenarios. We find that unlike GSReg, GCOR is a conservative approach that can reduce global variations, while avoiding the introduction of false significant differences, as GSReg can. However, as with GSReg, one cannot escape the interaction effect between the grouping variable and GCOR covariate on effect size. While GCOR is a complementary measure for resting state-FMRI applicable to legacy data, it is a lesser substitute for proper level-I denoising. We also assess the applicability of GCOR to empirical data with motion-based subject grouping and compare group differences to those using GSReg. We find that, while GCOR reduced correlation differences between high and low movers, it is doubtful that motion was the sole driver behind the differences in the first place.

Intrinsic gray-matter connectivity of the brain in adults with autism spectrum disorder

Autism spectrum disorders (ASD) are a group of neurodevelopmental conditions that are accompanied by atypical brain connectivity. So far, in vivo evidence for atypical structural brain connectivity in ASD has mainly been based on neuroimaging studies of cortical white matter. However, genetic studies suggest that abnormal connectivity in ASD may also affect neural connections within the cortical gray matter. Such intrinsic gray-matter connections are inherently more difficult to describe in vivo but may be inferred from a variety of surface-based geometric features that can be measured using magnetic resonance imaging. Here, we present a neuroimaging study that examines the intrinsic cortico-cortical connectivity of the brain in ASD using measures of "cortical separation distances" to assess the global and local intrinsic "wiring costs" of the cortex (i.e., estimated length of horizontal connections required to wire the cortex within the cortical sheet). In a sample of 68 adults with ASD and matched controls, we observed significantly reduced intrinsic wiring costs of cortex in ASD, both globally and locally. Differences in global and local wiring cost were predominantly observed in fronto-temporal regions and also significantly predicted the severity of social and repetitive symptoms (respectively). Our study confirms that atypical cortico-cortical "connectivity" in ASD is not restricted to the development of white-matter connections but may also affect the intrinsic gray-matter architecture (and connectivity) within the cortical sheet. Thus, the atypical connectivity of the brain in ASD is complex, affecting both gray and white matter, and forms part of the core neural substrates underlying autistic symptoms.

Selective disruption of sociocognitive structural brain networks in autism and alexithymia

Autism spectrum conditions (ASC) are neurodevelopmental disorders characterized by abnormal social cognition. A core feature of ASC is disrupted Theory of Mind (ToM), our ability to take the mental perspective of others. ASC is also associated with alexithymia, a trait characterized by altered emotional interoception and empathy. Here, we applied structural MRI covariance analysis to assess whether ASC and alexithymia differentially affect structural brain networks associated with sociocognitive and socioaffective functions. Based on previous functional MRI findings, we expected disrupted ToM networks (centered on dorsomedial prefontal cortex [dmPFC], and temporo-parietal junction [TPJ]) in ASC, while alexithymia would affect networks centered on fronto-insular cortex (FI), regions associated with interoception of emotion and empathy. Relative to controls, ASC indeed showed reduced covariance in networks centered on dmPFC and TPJ, but not within FI networks. Irrespective of ASC, covariance was negatively modulated by alexithymia in networks extending from FI to posterior regions. Network findings were complemented by self-reports, indicating decreased perspective taking but normal empathic concern in ASC. Our results show divergent effects of ASC and alexithymia on inter-regional structural networks, suggesting that networks mediating socioaffective processes may be separable from networks mediating sociocognitive processing.

The perils of global signal regression for group comparisons: a case study of Autism Spectrum Disorders

We have previously argued from a theoretical basis that the standard practice of regression of the Global Signal from the fMRI time series in functional connectivity studies is ill advised, particularly when comparing groups of participants. Here, we demonstrate in resting-state data from participants with an Autism Spectrum Disorder and matched controls that these concerns are also well founded in real data. Using the prior theoretical work to formulate predictions, we show: (1) rather than simply altering the mean or range of correlation values amongst pairs of brain regions, Global Signal Regression systematically alters the rank ordering of values in addition to introducing negative values, (2) it leads to a reversal in the direction of group correlation differences relative to other preprocessing approaches, with a higher incidence of both long-range and local correlation differences that favor the Autism Spectrum Disorder group, (3) the strongest group differences under other preprocessing approaches are the ones most altered by Global Signal Regression, and (4) locations showing group differences no longer agree with those showing correlations with behavioral symptoms within the Autism Spectrum Disorder group. The correlation matrices of both participant groups under Global Signal Regression were well predicted by our previous mathematical analyses, demonstrating that there is nothing mysterious about these results. Finally, when independent physiological nuisance measures are lacking, we provide a simple alternative approach for assessing and lessening the influence of global correlations on group comparisons that replicates our previous findings. While this alternative performs less well for symptom correlations than our favored preprocessing approach that includes removal of independent physiological measures, it is preferable to the use of Global Signal Regression, which prevents unequivocal conclusions about the direction or location of group differences.

Aberrant splicing in neurological diseases

Splicing of precursor messenger RNA (pre-mRNA) removes the intervening sequences (introns) and joins the expressed regions (exons) in the nucleus, before an intron-containing eukaryotic mRNA transcript can be exported and translated into proteins in the cytoplasm. While some sequences are always included or excluded (constitutive splicing), others can be selectively used (alternative splicing) in this process. Particularly by alternative splicing, up to tens of thousands of variant transcripts can be produced from a single gene, which contributes greatly to the proteomic diversity for such complex cellular functions as 'wiring' neurons in the nervous system. Disruption of this process leads to aberrant splicing, which accounts for the defects of up to 50% of mutations that cause certain human genetic diseases. In this review, we describe the different mechanisms of aberrant splicing that cause or have been associated with neurological diseases.

Decision making: from neuroscience to psychiatry

Adaptive behaviors increase the likelihood of survival and reproduction and improve the quality of life. However, it is often difficult to identify optimal behaviors in real life due to the complexity of the decision maker's environment and social dynamics. As a result, although many different brain areas and circuits are involved in decision making, evolutionary and learning solutions adopted by individual decision makers sometimes produce suboptimal outcomes. Although these problems are exacerbated in numerous neurological and psychiatric disorders, their underlying neurobiological causes remain incompletely understood. In this review, theoretical frameworks in economics and machine learning and their applications in recent behavioral and neurobiological studies are summarized. Examples of such applications in clinical domains are also discussed for substance abuse, Parkinson's disease, attention-deficit/hyperactivity disorder, schizophrenia, mood disorders, and autism. Findings from these studies have begun to lay the foundations necessary to improve diagnostics and treatment for various neurological and psychiatric disorders.

Increased gyrification, but comparable surface area in adolescents with autism spectrum disorders

Autism spectrum disorders are associated with atypically excessive early brain growth. Recent studies suggest that later cortical development, specifically cortical thickness, during adolescence and young adulthood is also aberrant. Nevertheless, previous studies of other surface-based metrics (e.g. surface area and gyrification) at high-resolution in autism spectrum disorders are limited. Forty-one males with autism spectrum disorders and 39 typically developing males matched on age (mean ≈ 17; range = 12-24 years) and IQ (mean ≈ 113; range = 85-143) provided high-resolution 3 T anatomical magnetic resonance imaging scans. The FreeSurfer image analysis suite quantified vertex-level surface area and gyrification. There were gyrification increases in the autism spectrum disorders group (relative to typically developing subjects) localized to bilateral posterior cortices (cluster corrected P < 0.01). Furthermore, the association between vocabulary knowledge and gyrification in left inferior parietal cortex (typically developing group: positive correlation; autism spectrum disorders group: no association) differed between groups. Finally, there were no group differences in surface area, and there was no interaction between age and group for either surface area or gyrification (both groups showed decreasing gyrification with increasing age). The present study complements and extends previous work by providing the first evidence of increased gyrification (though no differences in surface area) at high resolution among adolescents and young adults with autism spectrum disorders and by showing a dissociation in the relationship between vocabulary and gyrification in autism spectrum disorders versus typically developing subjects. In contrast with previous findings of age-related cortical thinning in this same autism spectrum disorders sample, here we find that increases in gyrification are maintained across adolescence and young adulthood, implicating developmentally dissociable cortical atypicalities in autism spectrum disorders.

Abnormal brain synchrony in Down Syndrome

Down Syndrome is the most common genetic cause for intellectual disability, yet the pathophysiology of cognitive impairment in Down Syndrome is unknown. We compared fMRI scans of 15 individuals with Down Syndrome to 14 typically developing control subjects while they viewed 50 min of cartoon video clips. There was widespread increased synchrony between brain regions, with only a small subset of strong, distant connections showing underconnectivity in Down Syndrome. Brain regions showing negative correlations were less anticorrelated and were among the most strongly affected connections in the brain. Increased correlation was observed between all of the distributed brain networks studied, with the strongest internetwork correlation in subjects with the lowest performance IQ. A functional parcellation of the brain showed simplified network structure in Down Syndrome organized by local connectivity. Despite increased interregional synchrony, intersubject correlation to the cartoon stimuli was lower in Down Syndrome, indicating that increased synchrony had a temporal pattern that was not in response to environmental stimuli, but idiosyncratic to each Down Syndrome subject. Short-range, increased synchrony was not observed in a comparison sample of 447 autism vs. 517 control subjects from the Autism Brain Imaging Exchange (ABIDE) collection of resting state fMRI data, and increased internetwork synchrony was only observed between the default mode and attentional networks in autism. These findings suggest immature development of connectivity in Down Syndrome with impaired ability to integrate information from distant brain regions into coherent distributed networks.

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Adjacent brain regions are more synchronized in Down Syndrome.

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Distant brain regions show less synchronization in Down Syndrome.

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Negatively correlated brain regions are less anticorrelated in Down Syndrome.

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Down Syndrome subjects show simplified brain network architecture.

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Increased brain synchrony does not reflect a response to environmental stimuli.