Autism Spectrum Disorder Brain Research Articles

A Preliminary Study of Abnormal Centrality of Cortical Regions and Subsystems in Whole Brain Functional Connectivity of Autism Spectrum Disorder Boys.

The abnormal cortices of autism spectrum disorder (ASD) brains are uncertain. However, the pathological alterations of ASD brains are distributed throughout interconnected cortical systems. Functional connections (FCs) methodology identifies cooperation and separation characteristics of information process in macroscopic cortical activity patterns under the context of network neuroscience. Embracing the graph theory concepts, this paper introduces eigenvector centrality index (EC score) ground on the FCs, and further develops a new framework for researching the dysfunctional cortex of ASD in holism significance. The important process is to uncover noticeable regions and subsystems endowed with antagonistic stance in EC-scores of 26 ASD boys and 28 matched healthy controls (HCs). For whole brain regional EC scores of ASD boys, orbitofrontal superior medial cortex, insula R, posterior cingulate gyrus L, and cerebellum 9 L are endowed with different EC scores significantly. In the brain subsystems level, EC scores of DMN, prefrontal lobe, and cerebellum are aberrant in the ASD boys. Generally, the EC scores display widespread distribution of diseased regions in ASD brains. Meanwhile, the discovered regions and subsystems, such as MPFC, AMYG, INS, prefrontal lobe, and DMN, are engaged in social processing. Meanwhile, the CBCL externalizing problem scores are associated with EC scores.

Closing the species gap: Translational approaches to studying sensory processing differences relevant for autism spectrum disorder.

The study of sensory phenotypes has great potential for increasing research translation between species, a necessity to decipher the neural mechanisms that contribute to higher-order differences in neurological conditions such as autism spectrum disorder (ASD). Over the past decade, despite separate advances in our understanding of the structural and functional differences within the brain of autistic and non-autistic individuals and in rodent models for ASD, researchers have had difficulty translating the findings in murine species to humans, mostly due to incompatibility in experimental methodologies used to screen for ASD phenotypes. Focusing on sensory phenotypes offers an avenue to close the species gap because sensory pathways are highly conserved across species and are affected by the same risk-factors as the higher-order brain areas mostly responsible for the diagnostic criteria for ASD. By first reviewing how sensory processing has been studied to date, we direct our focus to electrophysiological and behavioral techniques that can be used to study sensory phenotypes consistently across species. Using auditory sensory phenotypes as a template, we seek to improve the accessibility of translational methods by providing a framework for collecting cohesive data in both rodents and humans. Specifically, evoked-potentials, acoustic startle paradigms, and psychophysical detection/discrimination paradigms can be created and implemented in a coordinated and systematic fashion across species. Through careful protocol design and collaboration, sensory processing phenotypes can be harnessed to bridge the gap that exists between preclinical animal studies and human testing, so that mutually held questions in autism research can be answered. LAY SUMMARY: It has always been difficult to relate results from animal research to humans. We try to close this gap by studying changes in sensory processing using careful protocol design and collaboration between clinicians and researchers. Sensory pathways are comparable between animals and humans, and are affected in the same way as the rest of the brain in ASD. Using changes in hearing as a template, we point the field in an innovative direction by providing a framework for collecting cohesive data in rodents and humans.

Decreased Cortical Nrf2 Gene Expression in Autism Spectrum Disorder and its Relationship to Thiol and Cobalamin status

Background The etiology of Autism spectrum disorder (ASD) is suspected to involve redox imbalances. In accordance with this, we previously published that sulfur metabolites in the methionine cycle and transsulfuration pathway were dysregulated in ASD frontal cortex. This was accompanied by disturbed vitamin B12 or cobalamin status. Cobalamin abundance and levels of the bioactive species methylcobalamin (MeCbl) were decreased, while levels of oxidized inert hydroxocobalamin (OHCbl) were increased in those tissues. Cellular cobalamin status is dependent on antioxidant availability. Reports have described decreased expression or activity of nuclear factor (erythroid-derived 2)-like 2 (Nrf2) in blood cells in ASD. Nrf2 is a transcription factor that promotes transcription of genes involved in maintaining antioxidant and detoxification status. We followed up on our postmortem study by performing real-time quantitative polymerase chain reaction (RT-qPCR) to investigate expression redox-linked genes. Genes included Nrf2 (NFE2L2), cystathionine beta synthase (CBS), cystathionine gamma-lyase (CTH), solute carrier family 1 member 1 (SLC1A1), glutathione synthetase (GSS), and glutathione reductase (GSR). We then searched for correlations among gene expression, thiols, and cobalamins to understand what factors may contribute to deranged sulfur and cobalamin metabolism in the brain in ASD. Methods RNA was isolated from control and ASD frontal cortex tissue using RNAqueous-4PCR kit manufactured by Ambion. Complementary DNA (cDNA) was synthesized with a Roche First Strand cDNA Synthesis kit. RT-qPCR was performed with a Roche LightCycler 480 model. Gene expression was normalized to glyceraldehyde 3-phosphate dehydrogenase. Bioinformatics searches were conducted with data downloaded from the consensus RNA dataset compiled by The Human Protein Atlas. Data were analyzed with Microsoft Excel and GraphPad Prism. Results NFE2L2, CBS, CTH, SLC1A1, and GSS RNA were decreased in ASD frontal cortex. Correlation analyses of pooled control and ASD data revealed strong associations between NFE2L2, cobalamin abundance, methionine, S-adenosylmethionine (SAM), and S-adenosylhomocysteine (SAH). An association was also found with the transsulfuration metabolite cystathionine. Homocysteine (HCY) and OHCbl were inversely correlated with NFE2L2 expression. We decided to use a bioinformatics approach to further probe a general connection between Nrf2 and cobalamin status, utilizing cobalamin levels in various tissues published by Hsu et al. in 1966. Data obtained from The Human Protein Atlas revealed impressive associations between the expression of Nrf2-regulated genes, NFE2L2 expression, and tissue cobalamin abundance as described by Hsu et al. Conclusion Our RT-qPCR data support a role for decreased Nrf2 activity as an important feature of ASD. We further find that NFE2L2 expression is related to the metabolic patterns we characterized in ASD frontal cortex. Results of our bioinformatics inquiry suggest a potential causal role for Nrf2 that requires further investigation.

A neurogenetic analysis of female autism.

Females versus males are less frequently diagnosed with autism spectrum disorder (ASD), and while understanding sex differences is critical to delineating the systems biology of the condition, female ASD is understudied. We integrated functional MRI and genetic data in a sex-balanced sample of ASD and typically developing youth (8–17 years old) to characterize female-specific pathways of ASD risk. Our primary objectives were to: (i) characterize female ASD (n = 45) brain response to human motion, relative to matched typically developing female youth (n = 45); and (ii) evaluate whether genetic data could provide further insight into the potential relevance of these brain functional differences. For our first objective we found that ASD females showed markedly reduced response versus typically developing females, particularly in sensorimotor, striatal, and frontal regions. This difference between ASD and typically developing females does not resemble differences between ASD (n = 47) and typically developing males (n = 47), even though neural response did not significantly differ between female and male ASD. For our second objective, we found that ASD females (n = 61), versus males (n = 66), showed larger median size of rare copy number variants containing gene(s) expressed in early life (10 postconceptual weeks to 2 years) in regions implicated by the typically developing female > female functional MRI contrast. Post hoc analyses suggested this difference was primarily driven by copy number variants containing gene(s) expressed in striatum. This striatal finding was reproducible among n = 2075 probands (291 female) from an independent cohort. Together, our findings suggest that striatal impacts may contribute to pathways of risk in female ASD and advocate caution in drawing conclusions regarding female ASD based on male-predominant cohorts.

Neural coding of formant-exaggerated speech and nonspeech in children with and without autism spectrum disorders.

The presence of vowel exaggeration in infant-directed speech (IDS) may adapt to the age-appropriate demands in speech and language acquisition. Previous studies have provided behavioral evidence of atypical auditory processing towards IDS in children with autism spectrum disorders (ASD), while the underlying neurophysiological mechanisms remain unknown. This event-related potential (ERP) study investigated the neural coding of formant-exaggerated speech and nonspeech in 24 4- to 11-year-old children with ASD and 24 typically-developing (TD) peers. The EEG data were recorded using an alternating block design, in which each stimulus type (exaggerated/non-exaggerated sound) was presented with equal probability. ERP waveform analysis revealed an enhanced P1 for vowel formant exaggeration in the TD group but not in the ASD group. This speech-specific atypical processing in ASD was not found for the nonspeech stimuli which showed similar P1 enhancement in both ASD and TD groups. Moreover, the time-frequency analysis indicated that children with ASD showed differences in neural synchronization in the delta-theta bands for processing acoustic formant changes embedded in nonspeech. Collectively, the results add substantiating neurophysiological evidence (i.e., a lack of neural enhancement effect of vowel exaggeration) for atypical auditory processing of IDS in children with ASD, which may exert a negative effect on phonetic encoding and language learning. LAY SUMMARY: Atypical responses to motherese might act as a potential early marker of risk for children with ASD. This study investigated the neural responses to such socially relevant stimuli in the ASD brain, and the results suggested a lack of neural enhancement responding to the motherese even in individuals without intellectual disability.

Altered structural balance of resting-state networks in autism

What makes a network complex, in addition to its size, is the interconnected interactions between elements, disruption of which inevitably results in dysfunction. Likewise, the brain networks’ complexity arises from interactions beyond pair connections, as it is simplistic to assume that in complex networks state of a link is independently determined only according to its two constituting nodes. This is particularly of note in genetically complex brain impairments, such as the autism spectrum disorder (ASD), which has a surprising heterogeneity in manifestations with no clear-cut neuropathology. Accordingly, structural balance theory (SBT) affirms that in real-world signed networks, a link is remarkably influenced by each of its two nodes’ interactions with the third node within a triadic interrelationship. Thus, it is plausible to ask whether ASD is associated with altered structural balance resulting from atypical triadic interactions. In other words, it is the abnormal interplay of positive and negative interactions that matters in ASD, besides and beyond hypo (hyper) pair connectivity. To address this question, we explore triadic interactions based on SBT in the weighted signed resting-state functional magnetic resonance imaging networks of participants with ASD relative to healthy controls (CON). We demonstrate that balanced triads are overrepresented in the ASD and CON networks while unbalanced triads are underrepresented, providing first-time empirical evidence for the strong notion of structural balance on the brain networks. We further analyze the frequency and energy distributions of different triads and suggest an alternative description for the reduced functional integration and segregation in the ASD brain networks. Moreover, results reveal that the scale of change in the whole-brain networks’ energy is more narrow in the ASD networks during development. Last but not least, we observe that energy of the salience network and the default mode network are lower in ASD, which may be a reflection of the difficulty in dynamic switching and flexible behaviors. Altogether, these results provide insight into the atypical structural balance of the ASD brain (sub) networks. It also highlights the potential value of SBT as a new perspective in functional connectivity studies, especially in the case of neurodevelopmental disorders.

The landscape of somatic mutation in cerebral cortex of autistic and neurotypical individuals revealed by ultra-deep whole-genome sequencing.

We characterize the landscape of somatic mutations—mutations occurring after fertilization—in the human brain using ultra-deep (~250X) whole-genome sequencing of prefrontal cortex from 59 autism spectrum disorder (ASD) cases and 15 controls. We observe a mean of 26 somatic single nucleotide variants (sSNVs) per brain present in ≥4% of cells, with enrichment of mutations in coding and putative regulatory regions. Our analysis reveals that the first cell division after fertilization produces ~3.4 mutations, followed by 2–3 mutations in subsequent generations. This suggests that a typical individual possesses ~80 sSNVs present in ≥2% of cells—comparable to the number of de novo germline mutations per generation—with about half of individuals having at least one potentially function-altering somatic mutation somewhere in the cortex. ASD brains show an excess of somatic mutations in neural enhancer sequences compared to controls, suggesting that mosaic enhancer mutations may contribute to ASD risk.

Optogenetic Approaches to Understand the Neural Circuit Mechanism of Social Deficits Seen in Autism Spectrum Disorders.

Individuals with neurodevelopmental disorders, such as autism spectrum disorders (ASDs), are diagnosed based on nonquantitative objective parameters such as behavioral phenotypes. It is still unclear how any neural mechanism affects such behavioral phenotypes in these patients. In human genetics, a large number of genetic abnormalities including single nucleotide variation (SNV) and copy number variation (CNV) have been found in individuals with ASDs. It is thought that influence of such variations converges on dysfunction of neural circuit resulting in common behavioral phenotypes of ASDs such as deficits in social communication and interaction. Recent studies suggest that an excitatory/inhibitory (E/I) imbalanced state, which induces disruption of neural circuit activities, is one of the pathophysiological abnormalities in ASD brains. To assess the causal relationship between brain abnormalities and behavioral deficits, we can take advantage of optogenetics with animal models of ASDs that recapitulate human genetic mutations. Here, we review optogenetics studies being utilized to dissect neural circuit mechanisms associated with social deficits in model mice of ASD. Optogenetic manipulation of disrupted neural activities would help us understand how neural circuits affect behavioral deficits observed in ASDs.

The Parvalbumin Hypothesis of Autism Spectrum Disorder.

The prevalence of autism spectrum disorder (ASD)—a type of neurodevelopmental disorder—is increasing and is around 2% in North America, Asia, and Europe. Besides the known genetic link, environmental, epigenetic, and metabolic factors have been implicated in ASD etiology. Although highly heterogeneous at the behavioral level, ASD comprises a set of core symptoms including impaired communication and social interaction skills as well as stereotyped and repetitive behaviors. This has led to the suggestion that a large part of the ASD phenotype is caused by changes in a few and common set of signaling pathways, the identification of which is a fundamental aim of autism research. Using advanced bioinformatics tools and the abundantly available genetic data, it is possible to classify the large number of ASD-associated genes according to cellular function and pathways. Cellular processes known to be impaired in ASD include gene regulation, synaptic transmission affecting the excitation/inhibition balance, neuronal Ca2+ signaling, development of short-/long-range connectivity (circuits and networks), and mitochondrial function. Such alterations often occur during early postnatal neurodevelopment. Among the neurons most affected in ASD as well as in schizophrenia are those expressing the Ca2+-binding protein parvalbumin (PV). These mainly inhibitory interneurons present in many different brain regions in humans and rodents are characterized by rapid, non-adaptive firing and have a high energy requirement. PV expression is often reduced at both messenger RNA (mRNA) and protein levels in human ASD brain samples and mouse ASD (and schizophrenia) models. Although the human PVALB gene is not a high-ranking susceptibility/risk gene for either disorder and is currently only listed in the SFARI Gene Archive, we propose and present supporting evidence for the Parvalbumin Hypothesis, which posits that decreased PV level is causally related to the etiology of ASD (and possibly schizophrenia).

Examining volumetric gradients based on the frustum surface ratio in the brain in autism spectrum disorder.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is accompanied by neurodevelopmental differences in regional cortical volume (CV), and a potential layer‐specific pathology. Conventional measures of CV, however, do not indicate how volume is distributed across cortical layers. In a sample of 92 typically developing (TD) controls and 92 adult individuals with ASD (aged 18–52 years), we examined volumetric gradients by quantifying the degree to which CV is weighted from the pial to the white surface of the brain. Overall, the spatial distribution of Frustum Surface Ratio (FSR) followed the gyral and sulcal pattern of the cortex and approximated a bimodal Gaussian distribution caused by a linear mixture of vertices on gyri and sulci. Measures of FSR were highly correlated with vertex‐wise estimates of mean curvature, sulcal depth, and pial surface area, although none of these features explained more than 76% variability in FSR on their own. Moreover, in ASD, we observed a pattern of predominant increases in the degree of FSR relative to TD controls, with an atypical neurodevelopmental trajectory. Our findings suggest a more outward‐weighted gradient of CV in ASD, which may indicate a larger contribution of supragranular layers to regional differences in CV.

Comprehensive Analysis of RNA-Seq Gene Expression Profiling of Brain Transcriptomes Reveals Novel Genes, Regulators, and Pathways in Autism Spectrum Disorder.

Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with deficits in social communication ability and repetitive behavior. The pathophysiological events involved in the brain of this complex disease are still unclear. Methods: In this study, we aimed to profile the gene expression signatures of brain cortex of ASD patients, by using two publicly available RNA-seq studies, in order to discover new ASD-related genes. Results: We detected 1567 differentially expressed genes (DEGs) by meta-analysis, where 1194 were upregulated and 373 were downregulated genes. Several ASD-related genes previously reported were also identified. Our meta-analysis identified 235 new DEGs that were not detected using the individual RNA-seq studies used. Some of those genes, including seven DEGs (PAK1, DNAH17, DOCK8, DAPP1, PCDHAC2, and ERBIN, SLC7A7), have been confirmed in previous reports to be associated with ASD. Gene Ontology (GO) and pathways analysis showed several molecular pathways enriched by the DEGs, namely, osteoclast differentiation, TNF signaling pathway, complement and coagulation cascade. Topological analysis of protein–protein interaction of the ASD brain cortex revealed proteomics hub gene signatures: MYC, TP53, HDAC1, CDK2, BAG3, CDKN1A, GABARAPL1, EZH2, VIM, and TRAF1. We also identified the transcriptional factors (TFs) regulating DEGs, namely, FOXC1, GATA2, YY1, FOXL1, USF2, NFIC, NFKB1, E2F1, TFAP2A, HINFP. Conclusion: Novel core genes and molecular signatures involved with ASD were identified by our meta-analysis.

Integrative genomics identifies a convergent molecular subtype that links epigenomic with transcriptomic differences in autism

Autism spectrum disorder (ASD) is a phenotypically and genetically heterogeneous neurodevelopmental disorder. Despite this heterogeneity, previous studies have shown patterns of molecular convergence in post-mortem brain tissue from autistic subjects. Here, we integrate genome-wide measures of mRNA expression, miRNA expression, DNA methylation, and histone acetylation from ASD and control brains to identify a convergent molecular subtype of ASD with shared dysregulation across both the epigenome and transcriptome. Focusing on this convergent subtype, we substantially expand the repertoire of differentially expressed genes in ASD and identify a component of upregulated immune processes that are associated with hypomethylation. We utilize eQTL and chromosome conformation datasets to link differentially acetylated regions with their cognate genes and identify an enrichment of ASD genetic risk variants in hyperacetylated noncoding regulatory regions linked to neuronal genes. These findings help elucidate how diverse genetic risk factors converge onto specific molecular processes in ASD.

A Machine Learning Approach to Predicting Autism Risk Genes: Validation of Known Genes and Discovery of New Candidates.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with a strong genetic basis. The role of de novo mutations in ASD has been well established, but the set of genes implicated to date is still far from complete. The current study employs a machine learning-based approach to predict ASD risk genes using features from spatiotemporal gene expression patterns in human brain, gene-level constraint metrics, and other gene variation features. The genes identified through our prediction model were enriched for independent sets of ASD risk genes, and tended to be down-expressed in ASD brains, especially in frontal and parietal cortex. The highest-ranked genes not only included those with strong prior evidence for involvement in ASD (for example, NBEA, HERC1, and TCF20), but also indicated potentially novel candidates, such as, MYCBP2 and CAND1, which are involved in protein ubiquitination. We also showed that our method outperformed state-of-the-art scoring systems for ranking curated ASD candidate genes. Gene ontology enrichment analysis of our predicted risk genes revealed biological processes clearly relevant to ASD, including neuronal signaling, neurogenesis, and chromatin remodeling, but also highlighted other potential mechanisms that might underlie ASD, such as regulation of RNA alternative splicing and ubiquitination pathway related to protein degradation. Our study demonstrates that human brain spatiotemporal gene expression patterns and gene-level constraint metrics can help predict ASD risk genes. Our gene ranking system provides a useful resource for prioritizing ASD candidate genes.

A preliminary study of atypical cortical change ability of dynamic whole-brain functional connectivity in autism spectrum disorder

Objectives Designing new objectively diagnostic methods of autism spectrum disorder (ASD) are burning questions. Dynamic functional connectivity (DFC) methodology based on fMRI data are an effective lever to investigate changeability evolution of signal synchronization in macroscopic neural activity patterns. Methods Embracing the network dynamics concepts, this paper introduces changeability index (-score)which is focused on time-varying aspects of FCs, and develops a new framework for researching the roots of ASD brains at resting states in holism significance. The important process is to uncover noticeable regions and subsystems endowed with antagonistic stance in -scores of between atypical and typical DFCs of 30 healthy controls (HCs) and 48 ASD patients. Results The abnormities of edge C-scores are found across widespread brain cortex in ASD brains. For whole brain regional C-scores of ASD patients, orbitofrontal middle cortex L, inferior triangular frontal gyrus L, middle occipital gyrus L, postcentral gyrus L, supramarginal L, supramarginal R, cerebellum 8 L, and cerebellum 10 Rare endowed with significantly different -scores.At brain subsystems level, C-scores in left hemisphere, right hemisphere, top hemisphere, bottom hemisphere, frontal lobe, parietal lobe, occipital lobe, cerebellum sub systems are abnormal in ASD patients. Conclusions The ASD brains have whole-brain abnormity on widespread regions. Through the strict evidence-based study, it was found that the changeability index (C-score) is a meaningful biological marker to explore cortical activity in ASD.

Transcriptomic Analysis Reveals Abnormal Expression of Prion Disease Gene Pathway in Brains from Patients with Autism Spectrum Disorders.

The role of infections in the pathogenesis of autism spectrum disorder (ASD) is still controversial. In this study, we aimed to evaluate markers of infections and immune activation in ASD by performing a meta-analysis of publicly available whole-genome transcriptomic datasets of brain samples from autistic patients and otherwise normal people. Among the differentially expressed genes, no significant enrichment was observed for infectious diseases previously associated with ASD, including herpes simplex virus-1 (HSV-1), cytomegalovirus and Epstein–Barr virus in brain samples, nor was it found in peripheral blood from ASD patients. Interestingly, a significant number of genes belonging to the “prion diseases” pathway were found to be modulated in our ASD brain meta-analysis. Overall, our data do not support an association between infection and ASD. However, the data do provide support for the involvement of pathways related to other neurodegenerative diseases and give input to uncover novel pathogenetic mechanisms underlying ASD.

5-aminolevulinic acid inhibits oxidative stress and ameliorates autistic-like behaviors in prenatal valproic acid-exposed rats

Autism spectrum disorders (ASDs) constitute a neurodevelopmental disorder characterized by social deficits, repetitive behaviors, and learning disability. Oxidative stress and mitochondrial dysfunction are associated with ASD brain pathology. Here, we used oxidative stress in prenatal valproic acid (VPA)-exposed rats as an ASD model. After maternal VPA exposure (600 mg/kg, p.o.) on embryonic day (E) 12.5, temporal analyses of oxidative stress in the brain using an anti-4-hydroxy-2-nonenal antibody revealed that oxidative stress was increased in the hippocampus after birth. This was accompanied by aberrant enzymatic activity in the mitochondrial electron transport chain and reduced adenosine triphosphate (ATP) levels in the hippocampus. VPA-exposed rats exhibited impaired spatial reference and object recognition memory alongside impaired social behaviors and repetitive behaviors. ASD-like behaviors including learning and memory were rescued by chronic oral administration of 5-aminolevulinic acid (5-ALA; 30 mg/kg/day) and intranasal administration of oxytocin (OXT; 12 μg/kg/day), a neuropeptide that improves social behavior in ASD patients. 5-ALA but not OXT treatment ameliorated oxidative stress and mitochondrial dysfunction in the hippocampus of VPA-exposed rats. Fewer parvalbumin-positive interneurons were observed in VPA-exposed rats. Both 5-ALA and OXT treatments augmented the number of parvalbumin-positive interneurons. Collectively, our results indicate that oral 5-ALA administration ameliorated oxidative stress and mitochondrial dysfunction, suggesting that 5-ALA administration improves ASD-like neuropathology and behaviors via mechanisms different to those of OXT.

Behavioural profiling of autism connectivity abnormalities.

Brain regions are functionally diverse, and a given region may engage in a variety of tasks. This functional diversity of brain regions may be one factor that has prevented the finding of consistent biomarkers for brain disorders such as autism spectrum disorder (ASD). Thus, methods to characterise brain regions would help to determine how functional abnormalities contribute to affected behaviours. As the first illustration of the meta-analytic behavioural profiling procedure, we evaluated how the regions with disrupted connectivity in ASD contributed to various behaviours. Connectivity abnormalities were determined from a published degree centrality group comparison based on functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange. Using BrainMap's database of task-based neuroimaging studies, behavioural profiles were created for abnormally connected regions by relating these regions to tasks activating them. Hyperconnectivity in ASD brains was significantly related to memory, attention, reasoning, social, execution and speech behaviours. Hypoconnectivity was related to vision, execution and speech behaviours. The procedure outlines the first clinical neuroimaging application of a behavioural profiling method that estimates the functional diversity of brain regions, allowing for the relation of abnormal functional connectivity to diagnostic criteria. Behavioural profiling and the computational insights it provides can facilitate better understanding of the functional manifestations of various disorders, including ASD.

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.

Diagnosing autism spectrum disorder using brain entropy: A fast entropy method

Background and objectivePrevious resting-state fMRI-based diagnostic models for autism spectrum disorder (ASD) were based on traditional linear features. The complexity of the ASD brain remains unexplored. MethodsTo increase our understanding of the nonlinear neural mechanisms in ASD, entropy (i.e., approximate entropy (ApEn) and sample entropy (SampEn)) method was used to analyze the resting-state fMRI datasets collected from 21 ASD patients and 26 typically developing (TD) individuals. Here, a fast entropy algorithm was proposed through matrix computation. We combined entropy with a support-vector machine and selected "important entropy" as features to diagnose ASD. The classification performance of the fast entropy method was compared to the state-of-the-art functional connectivity (FC) method. ResultsThe area under the receiver operating characteristic curve based on FC was 0.62. The areas under the receiver operating characteristic curves based on ApEn and SampEn were 0.79 and 0.89, respectively. The results showed that the proposed fast entropy method was more efficacious than the FC method. In addition, lower entropy was found in the ASD patients. The ApEn of the left postcentral gyrus (rs = −0.556, p = 0.009) and the SampEn of the right lingual gyrus (rs = −0.526, p = 0.014) were both significantly negatively related to Autism Diagnostic Observation Schedule total scores in the ASD patients. The proposed algorithm for entropy computation was faster than the traditional entropy method. ConclusionsOur study provides a new perspective to better understand the neural mechanisms of ASD. Brain entropy based on a fast algorithm was applied to distinguish ASD patients from TD individuals. ApEn and SampEn could be potential biomarkers in ASD investigations.

T lymphocytes and cytotoxic astrocyte blebs correlate across autism brains.

Autism spectrum disorder (ASD) affects 1 in 59 children, yet except for rare genetic causes, the etiology in most ASD remains unknown. In the ASD brain, inflammatory cytokine and transcript profiling shows increased expression of genes encoding mediators of the innate immune response. We evaluated postmortem brain tissue for adaptive immune cells and immune cell-mediated cytotoxic damage that could drive this innate immune response in the ASD brain. Standard neuropathology diagnostic methods including histology and immunohistochemistry were extended with automated image segmentation to quantify identified pathologic features in the postmortem brains. We report multifocal perivascular lymphocytic cuffs contain increased numbers of lymphocytes in ~65% of ASD compared to control brains in males and females, across all ages, in most brain regions, and in white and gray matter, and leptomeninges. CD3+ T lymphocytes predominate over CD20+ B lymphocytes and CD8+ over CD4+ T lymphocytes in ASD brains. Importantly, the perivascular cuff lymphocyte numbers correlate to the quantity of astrocyte-derived round membranous blebs. Membranous blebs form as a cytotoxic reaction to lymphocyte attack. Consistent with multifocal immune cell-mediated injury at perivascular cerebrospinal fluid (CSF)-brain barriers, a subset of white matter vessels have increased perivascular space (with jagged contours) and collagen in ASD compared to control brains. CSF-brain barrier pathology is also evident at cerebral cortex pial and ventricular ependymal surfaces in ASD. The findings suggest dysregulated cellular immunity damages astrocytes at foci along the CSF-brain barrier in ASD. ANN NEUROL 2019;86:885-898.