Sex differences in autism: a resting-state fMRI investigation of functional brain connectivity in males and females

Performance of machine learning classification models of autism using resting-state fMRI is contingent on sample heterogeneity

Autism spectrum disorders (ASDs) are heterogeneous neurodevelopmental conditions. In fMRI studies, including most machine learning studies seeking to distinguish ASD from typical developing (TD) samples, cohorts differing in gender and symptom severity composition are often treated statistically as one "ASD group". Using resting-state functional connectivity (FC) data, we implemented random forest to build diagnostic classifiers in 4 ASD samples including a total of 656 participants (N_ASD = 306, N_TD = 350, ages 6-18). Groups were manipulated to titrate heterogeneity of gender and symptom severity and partially overlapped. Each sample differed on inclusionary criteria: (1) all genders, unrestricted severity range; (2) only male participants, unrestricted severity; (3) all genders, higher severity only; (4) only male participants, higher severity. Each set consisted of 200 participants per group (ASD, TD; matched on age and head motion), 160 for training and 40 for validation. FMRI time series from 237 regions of interest (ROIs) were Pearson correlated in a 237×237 FC matrix and classifiers were built using random forest in training samples. Classification accuracies in validation samples were 62.5%, 65%, 70% and 73.75%, respectively for samples 1-4. Connectivity within cingulo-opercular task control (COTC) network, and between COTC ROIs and default mode and dorsal attention network contributed overall most informative features, but features differed across sets. Findings suggest that diagnostic classifiers vary depending on ASD sample composition. Specifically, greater homogeneity of samples regarding gender and symptom severity enhances classifier performance. However, given the true heterogeneity of ASDs, performance metrics alone may not adequately reflect classifier utility.

Sex differentiation of brain structures in autism: Findings from a gray matter asymmetry study

Autism spectrum disorder (ASD) is diagnosed much more often in males than females. This male predominance has prompted a number of studies to examine how sex differences are related to the neural expression of ASD. Different theories, such as the "extreme male brain" theory, the "female protective effect" (FPE) theory, and the gender incoherence (GI) theory, provide different explanations for the mixed findings of sex-related neural expression of ASD. This study sought to clarify whether either theory applies to the brain structure in individuals with ASD by analyzing a selective high-quality data subset from an open data resource (Autism Brain Imaging Data Exchange I and II) including 35 males/35 females with ASD and 86 male/86 female typical-controls (TCs). We examined the sex-related changes in ASD in gray matter asymmetry measures (i.e., asymmetry index, AI) derived from voxel-based morphometry using a 2 (diagnosis: ASD vs. TC) ×  2 (sex: female vs. male) factorial design. A diagnosis-by-sex interaction effect was identified in the planum temporale/Heschl's gyrus: (i) compared to females, males exhibited decreased AI (indicating more leftward brain asymmetry) in the TC group, whereas AI was greater (indicating less leftward brain asymmetry) for males than for females in the ASD group; and (ii) females with ASD showed reduced AI (indicating more leftward brain asymmetry) compared to female TCs, whereas there were no differences between ASDs and TCs in the male group. This interaction pattern supports the FPE theory in showing greater brain structure changes (masculinization) in females with ASD. LAY SUMMARY: To understand the neural mechanisms underlying male predominance in autism spectrum disorder (ASD), we investigated the sex differences in ASD-related alterations in brain asymmetry. We found greater changes in females with ASD compared with males with ASD, revealing a female protective effect. These findings provide novel insights into the neurobiology of sex differences in ASD.

Quantitative and Qualitative Sex Modulations in the Brain Anatomy of Autism

BACKGROUND

Sex-based neurobiological heterogeneity in autism is poorly understood. Research is disproportionately biased to males, leading to an unwarranted presumption that autism neurobiology is the same across sexes. Previous neuroimaging studies using amalgamated multicenter datasets to increase autistic female samples are characterized by large statistical noise.

METHODS

We used a better-powered dataset of 1183 scans of 839 individuals-299 (467 scans) autistic males, 74 (102 scans) autistic females, 240 (334 scans) control males, and 226 (280 scans) control females-to test two whole-brain models of overall/global sex modulations on autism neuroanatomy, by summary measures computed across the brain: the local magnitude model, in which the same brain regions/circuitries are involved across sexes but effect sizes are larger in females, indicating quantitative sex modulation; and spatial dissimilarity model, in which the neuroanatomy differs spatially between sexes, indicating qualitative sex modulation. The male and female autism groups were matched on age, IQ, and autism symptoms. Autism brain features were defined by comparisons with same-sex control individuals.

RESULTS

Across five metrics (cortical thickness, surface area, volume, mean absolute curvature, and subcortical volume), we found no evidence supporting the local magnitude model. We found indicators supporting the spatial dissimilarity model on cortical mean absolute curvature and subcortical volume, but not on other metrics.

CONCLUSIONS

The overall/global autism neuroanatomy in females and males does not simply differ quantitatively in the same brain regions/circuitries. They may differ qualitatively in spatial involvement in cortical curvature and subcortical volume. The neuroanatomy of autism may be partly sex specific. Sex stratification to inform autism preclinical/clinical research is needed to identify sex-informed neurodevelopmental targets.

Towards robust and replicable sex differences in the intrinsic brain function of autism

BACKGROUND

Marked sex differences in autism prevalence accentuate the need to understand the role of biological sex-related factors in autism. Efforts to unravel sex differences in the brain organization of autism have, however, been challenged by the limited availability of female data.

METHODS

We addressed this gap by using a large sample of males and females with autism and neurotypical (NT) control individuals (ABIDE; Autism: 362 males, 82 females; NT: 409 males, 166 females; 7-18 years). Discovery analyses examined main effects of diagnosis, sex and their interaction across five resting-state fMRI (R-fMRI) metrics (voxel-level Z > 3.1, cluster-level P < 0.01, gaussian random field corrected). Secondary analyses assessed the robustness of the results to different pre-processing approaches and their replicability in two independent samples: the EU-AIMS Longitudinal European Autism Project (LEAP) and the Gender Explorations of Neurogenetics and Development to Advance Autism Research.

RESULTS

Discovery analyses in ABIDE revealed significant main effects of diagnosis and sex across the intrinsic functional connectivity of the posterior cingulate cortex, regional homogeneity and voxel-mirrored homotopic connectivity (VMHC) in several cortical regions, largely converging in the default network midline. Sex-by-diagnosis interactions were confined to the dorsolateral occipital cortex, with reduced VMHC in females with autism. All findings were robust to different pre-processing steps. Replicability in independent samples varied by R-fMRI measures and effects with the targeted sex-by-diagnosis interaction being replicated in the larger of the two replication samples-EU-AIMS LEAP.

LIMITATIONS

Given the lack of a priori harmonization among the discovery and replication datasets available to date, sample-related variation remained and may have affected replicability.

CONCLUSIONS

Atypical cross-hemispheric interactions are neurobiologically relevant to autism. They likely result from the combination of sex-dependent and sex-independent factors with a differential effect across functional cortical networks. Systematic assessments of the factors contributing to replicability are needed and necessitate coordinated large-scale data collection across studies.

A review of resting-state fMRI and its use to examine psychiatric disorders

Resting-state fMRI (rs-fMRI) has emerged as an alternative method to study brain function in human and animal models. In humans, it has been widely used to study psychiatric disorders including schizophrenia, bipolar disorder, autism spectrum disorders, and attention deficit hyperactivity disorders. In this review, rs-fMRI and its advantages over task based fMRI, its currently used analysis methods, and its application in psychiatric disorders using different analysis methods are discussed. Finally, several limitations and challenges of rs-fMRI applications are also discussed.

Difference in default mode network subsystems in autism across childhood and adolescence

LAY ABSTRACT

Neuroimaging research has identified a network of brain regions that are more active when we daydream compared to when we are engaged in a task. This network has been named the default mode network. Furthermore, differences in the default mode network are the most consistent findings in neuroimaging research in autism. Recent studies suggest that the default mode network is composed of subnetworks that are tied to different functions, namely memory and understanding others' minds. In this study, we investigated if default mode network differences in autism are related to specific subnetworks of the default mode network and if these differences change across childhood and adolescence. Our results suggest that the subnetworks of the default mode network are less differentiated in autism in middle childhood compared to neurotypicals. By late adolescence, the default mode network subnetwork organisation was similar in the autistic and neurotypical groups. These findings provide a foundation for future studies to investigate if this developmental pattern relates to improvements in the integration of memory and social understanding as autistic children grow up.

The Development of Brain Network in Males with Autism Spectrum Disorders from Childhood to Adolescence: Evidence from fNIRS Study

In the current study, functional near-infrared spectroscopy (fNIRS) was used to collect resting-state signals from 77 males with autism spectrum disorders (ASD, age: 6~16.25) and 40 typically developing (TD) males (age: 6~16.58) in the theory-of-mind (ToM) network. The graph theory analysis was used to obtain the brain network properties in ToM network, and the multiple regression analysis demonstrated that males with ASD showed a comparable global network topology, and a similar age-related decrease in the medial prefrontal cortex area (mPFC) compared to TD individuals. Nevertheless, participants with ASD showed U-shaped trajectories of nodal metrics of right temporo-parietal junction (TPJ), and an age-related decrease in the left middle frontal gyrus (MFG), while trajectories of TD participants were opposite. The nodal metrics of the right TPJ was negatively associated with the social deficits of ASD, while the nodal metrics of the left MFG was negatively associated with the communication deficits of ASD. Current findings suggested a distinct developmental trajectory of the ToM network in males with ASD from childhood to adolescence.

Sexually dimorphic neuroanatomical differences relate to ASD-relevant behavioral outcomes in a maternal autoantibody mouse model

Immunoglobulin G (IgG) autoantibodies reactive to fetal brain proteins in mothers of children with ASD have been described by several groups. To understand their pathologic significance, we developed a mouse model of maternal autoantibody related ASD (MAR-ASD) utilizing the peptide epitopes from human autoantibody reactivity patterns. Male and female offspring prenatally exposed to the salient maternal autoantibodies displayed robust deficits in social interactions and increased repetitive self-grooming behaviors as juveniles and adults. In the present study, neuroanatomical differences in adult MAR-ASD and control offspring were assessed via high-resolution ex vivo magnetic resonance imaging (MRI) at 6 months of age. Of interest, MAR-ASD mice displayed significantly larger total brain volume and of the 159 regions examined, 31 were found to differ significantly in absolute volume (mm³) at an FDR of <5%. Specifically, the absolute volumes of several white matter tracts, cortical regions, and basal nuclei structures were significantly increased in MAR-ASD animals. These phenomena were largely driven by female MAR-ASD offspring, as no significant differences were seen with either absolute or relative regional volume in male MAR-ASD mice. However, structural covariance analysis suggests network-level desynchronization in brain volume in both male and female MAR-ASD mice. Additionally, preliminary correlational analysis with behavioral data relates that volumetric increases in numerous brain regions of MAR-ASD mice were correlated with social interaction and repetitive self-grooming behaviors in a sex-specific manner. These results demonstrate significant sex-specific effects in brain size, regional relationships, and behavior for offspring prenatally exposed to MAR-ASD autoantibodies relative to controls.

Individual Differences in Intrinsic Brain Networks Predict Symptom Severity in Autism Spectrum Disorders

The neurobiology of heterogeneous neurodevelopmental disorders such as Autism Spectrum Disorders (ASD) is still unknown. We hypothesized that differences in subject-level properties of intrinsic brain networks were important features that could predict individual variation in ASD symptom severity. We matched cases and controls from a large multicohort ASD dataset (ABIDE-II) on age, sex, IQ, and image acquisition site. Subjects were matched at the individual level (rather than at group level) to improve homogeneity within matched case-control pairs (ASD: n = 100, mean age = 11.43 years, IQ = 110.58; controls: n = 100, mean age = 11.43 years, IQ = 110.70). Using task-free functional magnetic resonance imaging, we extracted intrinsic functional brain networks using projective non-negative matrix factorization. Intrapair differences in strength in subnetworks related to the salience network (SN) and the occipital-temporal face perception network were robustly associated with individual differences in social impairment severity (T = 2.206, P = 0.0301). Findings were further replicated and validated in an independent validation cohort of monozygotic twins (n = 12; 3 pairs concordant and 3 pairs discordant for ASD). Individual differences in the SN and face-perception network are centrally implicated in the neural mechanisms of social deficits related to ASD.

Atypical Inter-Network Deactivation Associated With the Posterior Default-Mode Network in Autism Spectrum Disorder

Previous studies have suggested that atypical deactivation of functional brain networks contributes to the complex cognitive and behavioral profile associated with autism spectrum disorder (ASD). However, these studies have not considered the temporal dynamics of deactivation mechanisms between the networks. In this study, we examined (a) mutual deactivation and (b) mutual activation-deactivation (i.e., anticorrelated) time-lag patterns between resting-state networks (RSNs) in young adults with ASD (n = 20) and controls (n = 20) by applying the recently defined dynamic lag analysis (DLA) method, which measures time-lag variations peak-by-peak between the networks. In order to achieve temporally accurate lag patterns, the brain imaging data was acquired with a fast functional magnetic resonance imaging (fMRI) sequence (TR = 100 ms). Group-level independent component analysis was used to identify 16 RSNs for the DLA. We found altered mutual deactivation timings in ASD in (a) three of the deactivated and (b) two of the transiently anticorrelated (activated-deactivated) RSN pairs, which survived the strict threshold for significance of surrogate data. Of the significant RSN pairs, 80% included the posterior default-mode network (DMN). We propose that temporally altered deactivation mechanisms, including timings and directionality, between the posterior DMN and RSNs mediating processing of socially relevant information may contribute to the ASD phenotype. LAY SUMMARY: To understand autistic traits on a neural level, we examined temporal fluctuations in information flow between brain regions in young adults with autism spectrum disorder (ASD) and controls. We used a fast neuroimaging procedure to investigate deactivation mechanisms between brain regions. We found that timings and directionality of communication between certain brain regions were temporally altered in ASD, suggesting atypical deactivation mechanisms associated with the posterior default-mode network.

Identifying brain areas correlated with ADOS raw scores by studying altered dynamic functional connectivity patterns

Altered functional connectivity patterns play an important role in explaining autism spectrum disorder related impairments. In order to examine such connectivity, resting state functional MRI is the most commonly used technique. To date, the majority of works in this area examine a whole time series of brain activation as a discrete stationary process. This study proposes a more detailed analysis of how functional connectivity fluctuates over time and how it is used to quantify instances demonstrating overconnectivity or underconnectivity. Non-parametric surrogates test identifies the areas where underconnectivity or overconnectivity correlate with the Autism Diagnosis Observation Schedule. In addition, this study shows how the areas identified affect the subjects behaviors. Our ultimate goal is a personalized autism diagnosis and treatment CAD system, where each subject impairments are distinctly mapped so they can be addressed with targeted treatments.

Sex-related patterns of intrinsic functional connectivity in children and adolescents with autism spectrum disorders

LAY SUMMARY

We investigated whether children and adolescents with autism spectrum disorders show sex-specific patterns of brain function (using functional magnetic resonance imaging) that are well documented in typically developing males and females. We found, unexpectedly, that boys and girls with autism do not differ in their brain functional connectivity, whereas typically developing boys and girls showed differences in a brain network involved in thinking about self and others (the default mode network). Results suggest that autism may be characterized by a lack of brain sex differentiation.

Multi-Class ASD Classification Based on Functional Connectivity and Functional Correlation Tensor via Multi-Source Domain Adaptation and Multi-View Sparse Representation

The resting-state functional magnetic resonance imaging (rs-fMRI) reflects functional activity of brain regions by blood-oxygen-level dependent (BOLD) signals. Up to now, many computer-aided diagnosis methods based on rs-fMRI have been developed for Autism Spectrum Disorder (ASD). These methods are mostly the binary classification approaches to determine whether a subject is an ASD patient or not. However, the disease often consists of several sub-categories, which are complex and thus still confusing to many automatic classification methods. Besides, existing methods usually focus on the functional connectivity (FC) features in grey matter regions, which only account for a small portion of the rs-fMRI data. Recently, the possibility to reveal the connectivity information in the white matter regions of rs-fMRI has drawn high attention. To this end, we propose to use the patch-based functional correlation tensor (PBFCT) features extracted from rs-fMRI in white matter, in addition to the traditional FC features from gray matter, to develop a novel multi-class ASD diagnosis method in this work. Our method has two stages. Specifically, in the first stage of multi-source domain adaptation (MSDA), the source subjects belonging to multiple clinical centers (thus called as source domains) are all transformed into the same target feature space. Thus each subject in the target domain can be linearly reconstructed by the transformed subjects. In the second stage of multi-view sparse representation (MVSR), a multi-view classifier for multi-class ASD diagnosis is developed by jointly using both views of the FC and PBFCT features. The experimental results using the ABIDE dataset verify the effectiveness of our method, which is capable of accurately classifying each subject into a respective ASD sub-category.

Sex Differences in Salience Network Connectivity and its Relationship to Sensory Over-Responsivity in Youth with Autism Spectrum Disorder

Individuals with autism spectrum disorder (ASD) are significantly more likely to experience sensory over-responsivity (SOR) compared to neurotypical controls. SOR in autism has been shown to be related to atypical functional connectivity in the salience network (SN), a brain network thought to help direct attention to the most relevant stimuli in one's environment. However, all studies to date which have examined the neurobiological basis of sensory processing in ASD have used primarily male samples so little is known about sex differences in the neural processing of sensory information. This study examined the relationship between SOR and resting-state functional connectivity in the SN for 37 males and 16 females with autism, ages 8-17 years. While there were no sex differences in parent-rated SOR symptoms, there were significant sex differences in how SOR related to SN connectivity. Relative to females with ASD, males with ASD showed a stronger association between SOR and increased connectivity between the salience and primary sensory networks, suggesting increased allocation to sensory information. Conversely, for females with ASD, SOR was more strongly related to increased connectivity between the SN and prefrontal cortex. Results suggest that the underlying mechanisms of SOR in ASD are sex specific, providing insight into the differences seen in the diagnosis rate and symptom profiles of males and females with ASD. LAY SUMMARY: Sensory over-responsivity (SOR) is common in autism. Most research on the neural basis of SOR has focused on males, so little is known about SOR or its neurobiology in females with autism spectrum disorder. Here despite no sex differences in SOR symptoms, we found sex differences in how SOR related to intrinsic connectivity in a salience detection network. Results show sex differences in the neural mechanisms underlying SOR and inform sex differences seen in diagnosis rates and symptom profiles in autism. Autism Res 2020, 13: 1489-1500. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.

Fixel Based Analysis Reveals Atypical White Matter Micro- and Macrostructure in Adults With Autism Spectrum Disorder: An Investigation of the Role of Biological Sex

Atypical white matter (WM) microstructure is commonly implicated in the neuropathophysiology of autism spectrum disorder (ASD). Fixel based analysis (FBA), at the cutting-edge of diffusion-weighted imaging, can account for crossing WM fibers and can provide indices of both WM micro- and macrostructure. We applied FBA to investigate WM structure between 25 (12 males, 13 females) adults with ASD and 24 (12 males, 12 females) matched controls. As the role of biological sex on the neuropathophysiology of ASD is of increasing interest, this was also explored. There were no significant differences in WM micro- or macrostructure between adults with ASD and matched healthy controls. When data were stratified by sex, females with ASD had reduced fiber density and cross-section (FDC), a combined metric comprised of micro- and macrostructural measures, in the corpus callosum, a finding not detected between the male sub-groups. We conclude that micro- and macrostructural WM aberrations are present in ASD, and may be influenced by biological sex.

Multi-site fMRI analysis using privacy-preserving federated learning and domain adaptation: ABIDE results

Deep learning models have shown their advantage in many different tasks, including neuroimage analysis. However, to effectively train a high-quality deep learning model, the aggregation of a significant amount of patient information is required. The time and cost for acquisition and annotation in assembling, for example, large fMRI datasets make it difficult to acquire large numbers at a single site. However, due to the need to protect the privacy of patient data, it is hard to assemble a central database from multiple institutions. Federated learning allows for population-level models to be trained without centralizing entities' data by transmitting the global model to local entities, training the model locally, and then averaging the gradients or weights in the global model. However, some studies suggest that private information can be recovered from the model gradients or weights. In this work, we address the problem of multi-site fMRI classification with a privacy-preserving strategy. To solve the problem, we propose a federated learning approach, where a decentralized iterative optimization algorithm is implemented and shared local model weights are altered by a randomization mechanism. Considering the systemic differences of fMRI distributions from different sites, we further propose two domain adaptation methods in this federated learning formulation. We investigate various practical aspects of federated model optimization and compare federated learning with alternative training strategies. Overall, our results demonstrate that it is promising to utilize multi-site data without data sharing to boost neuroimage analysis performance and find reliable disease-related biomarkers. Our proposed pipeline can be generalized to other privacy-sensitive medical data analysis problems. Our code is publicly available at: https://github.com/xxlya/Fed_ABIDE/.

Reconciling Dimensional and Categorical Models of Autism Heterogeneity: A Brain Connectomics and Behavioral Study

BACKGROUND

Heterogeneity in autism spectrum disorder (ASD) has hindered the development of biomarkers, thus motivating subtyping efforts. Most subtyping studies divide individuals with ASD into nonoverlapping (categorical) subgroups. However, continuous interindividual variation in ASD suggests that there is a need for a dimensional approach.

METHODS

A Bayesian model was employed to decompose resting-state functional connectivity (RSFC) of individuals with ASD into multiple abnormal RSFC patterns, i.e., categorical subtypes, henceforth referred to as "factors." Importantly, the model allowed each individual to express one or more factors to varying degrees (dimensional subtyping). The model was applied to 306 individuals with ASD (5.2-57 years of age) from two multisite repositories. Post hoc analyses associated factors with symptoms and demographics.

RESULTS

Analyses yielded three factors with dissociable whole-brain hypo- and hyper-RSFC patterns. Most participants expressed multiple (categorical) factors, suggestive of a mosaic of subtypes within individuals. All factors shared abnormal RSFC involving the default mode network, but the directionality (hypo- or hyper-RSFC) differed across factors. Factor 1 was associated with core ASD symptoms. Factors 1 and 2 were associated with distinct comorbid symptoms. Older male participants preferentially expressed factor 3. Factors were robust across control analyses and were not associated with IQ or head motion.

CONCLUSIONS

There exist at least three ASD factors with dissociable whole-brain RSFC patterns, behaviors, and demographics. Heterogeneous default mode network hypo- and hyper-RSFC across the factors might explain previously reported inconsistencies. The factors differentiated between core ASD and comorbid symptoms-a less appreciated domain of heterogeneity in ASD. These factors are coexpressed in individuals with ASD with different degrees, thus reconciling categorical and dimensional perspectives of ASD heterogeneity.

Neural responsivity to social rewards in autistic female youth

Autism is hypothesized to be in part driven by a reduced sensitivity to the inherently rewarding nature of social stimuli. Previous neuroimaging studies have indicated that autistic males do indeed display reduced neural activity to social rewards, but it is unknown whether this finding extends to autistic females, particularly as behavioral evidence suggests that affected females may not exhibit the same reduction in social motivation as their male peers. We therefore used functional magnetic resonance imaging to examine social reward processing during an instrumental implicit learning task in 154 children and adolescents (ages 8-17): 39 autistic girls, 43 autistic boys, 33 typically developing girls, and 39 typically developing boys. We found that autistic girls displayed increased activity to socially rewarding stimuli, including greater activity in the nucleus accumbens relative to autistic boys, as well as greater activity in lateral frontal cortices and the anterior insula compared with typically developing girls. These results demonstrate for the first time that autistic girls do not exhibit the same reduction in activity within social reward systems as autistic boys. Instead, autistic girls display increased neural activation to such stimuli in areas related to reward processing and salience detection. Our findings indicate that a reduced sensitivity to social rewards, as assessed with a rewarded instrumental implicit learning task, does not generalize to affected female youth and highlight the importance of studying potential sex differences in autism to improve our understanding of the condition and its heterogeneity.

Self-weighted adaptive structure learning for ASD diagnosis via multi-template multi-center representation

As a kind of neurodevelopmental disease, autism spectrum disorder (ASD) can cause severe social, communication, interaction, and behavioral challenges. To date, many imaging-based machine learning techniques have been proposed to address ASD diagnosis issues. However, most of these techniques are restricted to a single template or dataset from one imaging center. In this paper, we propose a novel multi-template multi-center ensemble classification scheme for automatic ASD diagnosis. Specifically, based on different pre-defined templates, we construct multiple functional connectivity (FC) brain networks for each subject based on our proposed Pearson's correlation-based sparse low-rank representation. After extracting features from these FC networks, informative features to learn optimal similarity matrix are then selected by our self-weighted adaptive structure learning (SASL) model. For each template, the SASL method automatically assigns an optimal weight learned from the structural information without additional weights and parameters. Finally, an ensemble strategy based on the multi- template multi-center representations is applied to derive the final diagnosis results. Extensive experiments are conducted on the publicly available Autism Brain Imaging Data Exchange (ABIDE) database to demonstrate the efficacy of our proposed method. Experimental results verify that our proposed method boosts ASD diagnosis performance and outperforms state-of-the-art methods.

Sex Differences in QEEG in Psychopath Offenders

Introduction. Functional brain differences related to sex in psychopathic behavior represent an important field of neuroscience research; there are few studies on this area, mainly in offender samples. Objective. The aim of this study was to investigate the presence of electrophysiological differences between male and female psychopath offenders; specifically, we wanted to assess whether the results in quantitative EEG, low-resolution electromagnetic tomography (LORETA), and changes in synchronous brain activity could be related to sex influence. Sample and Methods. The study included 31 male and 12 female psychopath offenders, according to the Hare Psychopathy Checklist-Revised criteria from 2 prisons located in Havana City. The EEG visual inspection characteristics and the use of frequency domain quantitative analysis techniques are described. Results. The resting EEG visual analyses revealed a high percentage of EEG abnormalities in both studied groups. Significant statistical differences between the mean parameters of cross spectral measures between psychopathic offender groups were found in the beta band at bilateral frontal derivation and centroparietal areas. LORETA showed differences especially in the paralimbic and parieto-occipital areas Synchronization likelihood revealed a significant group effect in the 26 to 30 Hz band. These results indicate that combining quantitative EEG, LORETA analysis, and synchronization likelihood may improve the neurofunctional differentiation between psychopath offenders of both sexes.

Sex Differences in Functional Connectivity of the Salience, Default Mode, and Central Executive Networks in Youth with ASD

Autism spectrum disorder (ASD) is associated with the altered functional connectivity of 3 neurocognitive networks that are hypothesized to be central to the symptomatology of ASD: the salience network (SN), default mode network (DMN), and central executive network (CEN). Due to the considerably higher prevalence of ASD in males, however, previous studies examining these networks in ASD have used primarily male samples. It is thus unknown how these networks may be differentially impacted among females with ASD compared to males with ASD, and how such differences may compare to those observed in neurotypical individuals. Here, we investigated the functional connectivity of the SN, DMN, and CEN in a large, well-matched sample of girls and boys with and without ASD (169 youth, ages 8-17). Girls with ASD displayed greater functional connectivity between the DMN and CEN than boys with ASD, whereas typically developing girls and boys differed in SN functional connectivity only. Together, these results demonstrate that youth with ASD exhibit altered sex differences in these networks relative to what is observed in typical development, and highlight the importance of considering sex-related biological factors and participant sex when characterizing the neural mechanisms underlying ASD.

Sex Differences in the Amygdala Resting-State Connectome of Children With Autism Spectrum Disorder

BACKGROUND

Multifactorial liability models predict greater dissimilarity in the neural phenotype of autism spectrum disorder (ASD) in female individuals than in male individuals, while gender incoherence and extreme male brain models predict attenuated sex differences in ASD. The amygdala is an informative target to explore these models because it is implicated in both the neurobiology of ASD and sex differences in typical development.

METHODS

This study investigated amygdala resting-state functional connectivity in a cohort of 116 children with ASD (36 female) and 58 typically developing children (27 female) 2 to 7 years of age during natural sleep. First, multivariate distance matrix regression assessed global sex and diagnostic differences across the amygdala connectome. Second, univariate general linear models identified regions with mean connectivity differences.

RESULTS

Multivariate distance matrix regression revealed greater differences between typically developing children and those with ASD in females than in males, consistent with multifactorial liability models, and attenuated sex differences in the left amygdala connectome of children with ASD in a pattern consistent with the gender incoherence model. Univariate analysis identified similar sex differences in dorsomedial and ventral prefrontal cortices, lingual gyrus, and posterior cingulate cortex, but also noted that lower amygdala connectivity with superior temporal sulcus is observed across sexes.

CONCLUSIONS

This study provides evidence that compared with sex-matched control subjects, ASD manifests differently in the brain at the time of diagnosis and prior to the influence of compensatory mechanisms in male and female children, consistent with multifactorial liability models, and that ASD is associated with reduced sex differences in a pattern consistent with gender incoherence models.

The developmental neurotoxicity of legacy vs. contemporary polychlorinated biphenyls (PCBs): similarities and differences

Although banned from production for decades, PCBs remain a significant risk to human health. A primary target of concern is the developing brain. Epidemiological studies link PCB exposures in utero or during infancy to increased risk of neuropsychiatric deficits in children. Nonclinical studies of legacy congeners found in PCB mixtures synthesized prior to the ban on PCB production suggest that non-dioxin-like (NDL) congeners are predominantly responsible for the developmental neurotoxicity associated with PCB exposures. Mechanistic studies suggest that NDL PCBs alter neurodevelopment via ryanodine receptor-dependent effects on dendritic arborization. Lightly chlorinated congeners, which were not present in the industrial mixtures synthesized prior to the ban on PCB production, have emerged as contemporary environmental contaminants, but there is a paucity of data regarding their potential developmental neurotoxicity. PCB 11, a prevalent contemporary congener, is found in the serum of children and their mothers, as well as in the serum of pregnant women at increased risk for having a child diagnosed with a neurodevelopmental disorder (NDD). Recent data demonstrates that PCB 11 modulates neuronal morphogenesis via mechanisms that are convergent with and divergent from those implicated in the developmental neurotoxicity of legacy NDL PCBs. This review summarizes these data and discusses their relevance to adverse neurodevelopmental outcomes in humans.

Characterizing intrinsic functional connectivity in relation to impaired self-regulation in intellectually able male youth with autism spectrum disorder

While a considerable number of youth with autism spectrum disorder exhibit impaired self-regulation (dysregulation), little is known about the neural correlates of dysregulation in autism spectrum disorder. In a sample of intellectually able boys with autism spectrum disorder (further categorized as those with and without dysregulation) and typically developing boys (aged 7–17 years), we conducted a multivariate connectome-wide association study to examine the intrinsic functional connectivity with resting-state functional magnetic resonance imaging. Dysregulation was defined by the sum of Attention, Aggression, and Anxiety/Depression subscales on the Child Behavior Checklist. We identified that both categorical and dimensional neural correlates of dysregulation in youth with autism spectrum disorder involved atypical connectivity among the components of multiple brain networks, especially between those subserving sensorimotor processing and salience encoding, beyond higher-level cognitive control circuitries. Interaction within the attention network might serve as autism spectrum disorder–specific neural correlates underpinning dysregulation. Our results highlight that the inter-individual variability in dysregulation might contribute to the inconsistency in the neuroimaging literature of autism spectrum disorder. Collectively, the present findings provide evidence to suggest that dysregulation might be considered as both categorical and dimensional moderators to parse heterogeneity of autism spectrum disorder.

Lay Abstract

Impaired self-regulation (i.e., dysregulation in affective, behavioral, and cognitive control), is commonly present in young people with autism spectrum disorder (ASD). However, little is known about what is happening in people’s brains when self-regulation is impaired in young people with ASD. We used a technique called functional MRI (which measures brain activity by detecting changes associated with blood flow) at a resting state (when participants are not asked to do anything) to research this in intellectually able young people with ASD. We found that brains with more connections, especially between regions involved in sensorimotor processing and regions involved in the processes that enable peoples to focus their attention on the most pertinent features from the sensory environment (salience processing), were related to more impaired self-regulation in young people with and without ASD. We also found that impaired self-regulation was related to increased communication within the brain system involved in voluntary orienting attention to a sensory cue (the dorsal attention network) in young people with ASD. These results highlight how different people have different degrees of dysregulation, which has been largely overlooked in the earlier brain imaging reports on ASD. This might contribute to understanding some of the inconsistencies in the existing published literature on this topic.

Autism spectrum disorder

Autism spectrum disorder is a construct used to describe individuals with a specific combination of impairments in social communication and repetitive behaviours, highly restricted interests and/or sensory behaviours beginning early in life. The worldwide prevalence of autism is just under 1%, but estimates are higher in high-income countries. Although gross brain pathology is not characteristic of autism, subtle anatomical and functional differences have been observed in post-mortem, neuroimaging and electrophysiological studies. Initially, it was hoped that accurate measurement of behavioural phenotypes would lead to specific genetic subtypes, but genetic findings have mainly applied to heterogeneous groups that are not specific to autism. Psychosocial interventions in children can improve specific behaviours, such as joint attention, language and social engagement, that may affect further development and could reduce symptom severity. However, further research is necessary to identify the long-term needs of people with autism, and treatments and the mechanisms behind them that could result in improved independence and quality of life over time. Families are often the major source of support for people with autism throughout much of life and need to be considered, along with the perspectives of autistic individuals, in both research and practice.

Potential explanations of behavioural and other differences and similarities between males and females with autism spectrum disorder

Several potential explanations may be dependent on the dynamics of prenatal and postnatal testosterone in males and females, and to be consistent with Baron-Cohen's concept of extreme male brain. This paper explores the evidence that male and female autistic subjects differ on the average in that they have had different exposures to the causes of autism, females bearing higher genetic burdens for ASD (autistic spectrum disorder), and males having a greater exposure to high intrauterine levels of testosterone (T). The high levels of intrauterine (and possibly postnatal) testosterone to which ASD cases have been exposed, cause a less masculinized physical habitus (including facial features) in exposed males, and a more masculinized physical habitus in exposed females. ASD genes (as opposed to intrauterine testosterone) are mainly responsible for a low mean IQ in ASD (especially female cases). Exposure to high intrauterine T increases the probability that foetuses will be male, thus potentially explaining the high sex ratio (proportion male) of cases of ASD. The Gender Incoherence Model seems to be based on facts unrelated directly to autism. The shifts towards the other sex are argued to be consequent on sex-different reactions to prenatal exposure to high T, not on the pathology itself. The suspected underdiagnosis of female cases is partially dependent on the different proportions of environmental and genetic causes to which male and female cases are hypothesized to have been exposed, and the consequent 'more normal' behaviour of female cases.

Sex/gender differences in neurology and psychiatry: Autism

Autism is a heterogenous set of early-onset neurodevelopmental conditions that are more prevalent in males than in females. Due to the high phenotypic, neurobiological, developmental, and etiological heterogeneity in the autism spectrum, recent research programs are increasingly exploring whether sex- and gender-related factors could be helpful markers to clarify the heterogeneity in autism and work toward a personalized approach to intervention and support. In this chapter, we summarize recent clinical and neuroscientific research addressing sex/gender influences in autism and explore how sex/gender-based investigations shed light on similar or different underlying neurodevelopmental mechanisms of autism by sex/gender. We review evidence that may help to explain some of the underlying sex-related biological mechanisms associated with autism, including genetics and the effects of sex steroid hormones in the prenatal environment. We conclude that current research points toward coexisting quantitative and, perhaps more evidently, qualitative sex/gender-modulation effects in autism across multiple neurobiological aspects. However, converging findings of specific neurobiological presentations and sex/gender-informed mechanisms cutting across the many subgroups within the autism spectrum are still lacking. Future research should use big data approaches and new stratification methods to decompose sex/gender-related heterogeneity in autism and work toward personalized, sex/gender-informed intervention and support for autistic people.

Self-Regulation of the Fusiform Face Area in Autism Spectrum: A Feasibility Study With Real-Time fMRI Neurofeedback

One of the most important and early impairments in autism spectrum disorder (ASD) is the abnormal visual processing of human faces. This deficit has been associated with hypoactivation of the fusiform face area (FFA), one of the main hubs of the face-processing network. Neurofeedback based on real-time fMRI (rtfMRI-NF) is a technique that allows the self-regulation of circumscribed brain regions, leading to specific neural modulation and behavioral changes. The aim of the present study was to train participants with ASD to achieve up-regulation of the FFA using rtfMRI-NF, to investigate the neural effects of FFA up-regulation in ASD. For this purpose, three groups of volunteers with normal I.Q. and fluent language were recruited to participate in a rtfMRI-NF protocol of eight training runs in 2 days. Five subjects with ASD participated as part of the experimental group and received contingent feedback to up-regulate bilateral FFA. Two control groups, each one with three participants with typical development (TD), underwent the same protocol: one group with contingent feedback and the other with sham feedback. Whole-brain and functional connectivity analysis using each fusiform gyrus as independent seeds were carried out. The results show that individuals with TD and ASD can achieve FFA up-regulation with contingent feedback. RtfMRI-NF in ASD produced more numerous and stronger short-range connections among brain areas of the ventral visual stream and an absence of the long-range connections to insula and inferior frontal gyrus, as observed in TD subjects. Recruitment of inferior frontal gyrus was observed in both groups during FAA up-regulation. However, insula and caudate nucleus were only recruited in subjects with TD. These results could be explained from a neurodevelopment perspective as a lack of the normal specialization of visual processing areas, and a compensatory mechanism to process visual information of faces. RtfMRI-NF emerges as a potential tool to study visual processing network in ASD, and to explore its clinical potential.

Altered inter- and intrahemispheric functional connectivity dynamics in autistic children

Emerging evidence has associated autism spectrum disorder (ASD) with static functional connectivity abnormalities between multiple brain regions. However, the temporal dynamics of intra‐ and interhemispheric functional connectivity patterns remain unknown in ASD. Resting‐state functional magnetic resonance imaging data were analyzed for 105 ASD and 102 demographically matched typically developing control (TC) children (age range: 7–12 years) available from the Autism Brain Imaging Data Exchange database. Whole‐brain functional connectivity was decomposed into ipsilateral and contralateral functional connectivity, and sliding‐window analysis was utilized to capture the intra‐ and interhemispheric dynamic functional connectivity density (dFCD) patterns. The temporal variability of the functional connectivity dynamics was further quantified using the standard deviation (SD) of intra‐ and interhemispheric dFCD across time. Finally, a support vector regression model was constructed to assess the relationship between abnormal dFCD variance and autism symptom severity. Both intra‐ and interhemispheric comparisons showed increased dFCD variability in the anterior cingulate cortex/medial prefrontal cortex and decreased variability in the fusiform gyrus/inferior temporal gyrus in autistic children compared with TC children. Autistic children additionally showed lower intrahemispheric dFCD variability in sensorimotor regions including the precentral/postcentral gyrus. Moreover, aberrant temporal variability of the contralateral dFCD predicted the severity of social communication impairments in autistic children. These findings demonstrate altered temporal dynamics of the intra‐ and interhemispheric functional connectivity in brain regions incorporating social brain network of ASD, and highlight the potential role of abnormal interhemispheric communication dynamics in neural substrates underlying impaired social processing in ASD.

Enhancement of indirect functional connections with shortest path length in the adult autistic brain

Autism is a neurodevelopmental condition characterized by atypical brain functional organization. Here we investigated the intrinsic indirect (semi‐metric) connectivity of the functional connectome associated with autism. Resting‐state functional magnetic resonance imaging scans were acquired from 65 neurotypical adults (33 males/32 females) and 61 autistic adults (30 males/31 females). From functional connectivity networks, semi‐metric percentages (SMPs) were calculated to assess the proportion of indirect shortest functional pathways at global, hemisphere, network, and node levels. Group comparisons were then conducted to ascertain differences between autism and neurotypical control groups. Finally, the strength and length of edges were examined to explore the patterns of semi‐metric connections associated with autism. Compared with neurotypical controls, autistic adults displayed significantly higher SMP at all spatial scales, similar to prior observations in adolescents. Differences were primarily in weaker, longer‐distance edges in the majority between networks. However, no significant diagnosis‐by‐sex interaction effects were observed on global SMP. These findings suggest increased indirect functional connectivity in the autistic brain is persistent from adolescence to adulthood and is indicative of reduced functional network integration.

Sparse Multiview Task-Centralized Ensemble Learning for ASD Diagnosis Based on Age- and Sex-Related Functional Connectivity Patterns

Autism spectrum disorder (ASD) is an age- and sex-related neurodevelopmental disorder that alters the brain's functional connectivity (FC). The changes caused by ASD are associated with different age- and sex-related patterns in neuroimaging data. However, most contemporary computer-assisted ASD diagnosis methods ignore the aforementioned age-/sex-related patterns. In this paper, we propose a novel sparse multiview task-centralized (Sparse-MVTC) ensemble classification method for image-based ASD diagnosis. Specifically, with the age and sex information of each subject, we formulate the classification as a multitask learning problem, where each task corresponds to learning upon a specific age/sex group. We also extract multiview features per subject to better reveal the FC changes. Then, in Sparse-MVTC learning, we select a certain central task and treat the rest as auxiliary tasks. By considering both task-task and view-view relationships between the central task and each auxiliary task, we can learn better upon the entire dataset. Finally, by selecting the central task, in turn, we are able to derive multiple classifiers for each task/group. An ensemble strategy is further adopted, such that the final diagnosis can be integrated for each subject. Our comprehensive experiments on the ABIDE database demonstrate that our proposed Sparse-MVTC ensemble learning can significantly outperform the state-of-the-art classification methods for ASD diagnosis.

Adolescent sex differences in cortico-subcortical functional connectivity during response inhibition

Numerous lines of evidence have shown that cognitive processes engaged during response inhibition tasks are associated with structure and functional integration of regions within fronto-parietal networks. However, while prior studies have started to characterize how intrinsic connectivity during resting state differs between boys and girls, comparatively less is known about how functional connectivity differs between males and females when brain function is exogenously driven by the processing demands of typical Go/No-Go tasks that assess both response inhibition and error processing. The purpose of this study was to characterize adolescent sex differences and possible changes in sexually dimorphic regional functional connectivity across adolescent development in both cortical and subcortical brain connectivity elicited during a visual Go/No-Go task. A total of 130 healthy adolescents (ages 12-25 years) performed a Go/No-Go task during functional magnetic resonance imaging. High model-order group independent component analysis was used to characterize whole-brain network functional connectivity during response inhibition and then a univariate technique used to evaluate differences related to sex and age. As predicted and similar to previously described findings from non-task-driven resting state connectivity studies, functional connectivity sex differences were observed in several subcortical regions, including the amygdala, caudate, thalamus, and cortical regions, including inferior frontal gyrus engaged most strongly during successful response inhibition and/or error processing. Importantly, adolescent boys and girls exhibited different normative profiles of age-related changes in several default mode networks of regions and anterior cingulate cortex. These results suggest that cortical-subcortical functional networks supporting response inhibition operate differently between sexes during adolescence.

Sex Differences in Resting-State Functional Connectivity of the Cerebellum in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is more prevalent in males than females, but the underlying neurobiology of this sex bias remains unclear. Given its involvement in ASD, its role in sensorimotor, cognitive, and socio-affective processes, and its developmental sensitivity to sex hormones, the cerebellum is a candidate for understanding this sex difference. The current study used resting-state functional magnetic resonance imaging (fMRI) to investigate sex-dependent differences in cortico-cerebellar organization in ASD. We collected resting-state fMRI scans from 47 females (23 ASD, 24 controls) and 120 males (56 ASD, 65 controls). Using a measure of global functional connectivity (FC), we ran a linear mixed effects analysis to determine whether there was a sex-by-diagnosis interaction in resting-state FC. Subsequent seed-based analyses from the resulting clusters were run to clarify the global connectivity effects. Two clusters in the bilateral cerebellum exhibited a diagnosis-by-sex interaction in global connectivity. These cerebellar clusters further showed a pattern of interaction with regions in the cortex, including bilateral fusiform, middle occipital, middle frontal, and precentral gyri, cingulate cortex, and precuneus. Post hoc tests revealed a pattern of cortico-cerebellar hyperconnectivity in ASD females and a pattern of hypoconnectivity in ASD males. Furthermore, cortico-cerebellar FC in females more closely resembled that of control males than that of control females. These results shed light on the sex-specific pathophysiology of ASD and are indicative of potentially divergent neurodevelopmental trajectories for each sex. This sex-dependent, aberrant cerebellar connectivity in ASD might also underlie some of the motor and/or socio-affective difficulties experienced by members of this population, but the symptomatic correlate(s) of these brain findings remain unknown.

Clinical Trial Registration: www.ClinicalTrials.gov, NIH Clinical Study Protocol 10-M-0027 (ZIA MH002920-09) identifier #NCT01031407

Women and Autism Spectrum Disorder: Diagnosis and Implications for Treatment of Adolescents and Adults

PURPOSE OF REVIEW

We review the recent literature regarding the implications of gender on the diagnosis and treatment of autism spectrum disorder (ASD) in women and adolescent females. We also discuss important clinical observations in treating this population.

RECENT FINDINGS

Growing research supports gender specificity in ASD symptom presentation. Differing phenotypes, psychiatric co-morbidities, and level of "camouflaging" (behavioral coping strategies to conceal symptoms for use in social situations) are thought to further contribute to the discrepancy in prevalence rates and resulting misdiagnosis or delayed diagnosis in adolescent females and women. Both nosological and cultural factors appear to be contributing to differences in the diagnosis of ASD in women. These differences in presentation have important implications for late diagnosis, treatment of ASD, and the quality of life for women with autism.

Altered resting-state dynamics in autism spectrum disorder: Causal to the social impairment?

Autism spectrum disorder (ASD) is characterized by profound impairments in social abilities and by restricted interests and repetitive behaviors. Much work in the past decade has been dedicated to understanding the brain-bases of ASD, and in the context of resting-state functional connectivity fMRI in high-functioning adolescents and adults, the field has established a set of reliable findings: decreased cortico-cortical interactions among brain regions thought to be engaged in social processing, along with a simultaneous increase in thalamo-cortical and striato-cortical interactions. However, few studies have attempted to manipulate these altered patterns, leading to the question of whether such patterns are actually causally involved in producing the corresponding behavioral impairments. We discuss a few such recent attempts in the domains of fMRI neurofeedback and overt social interaction during scanning, and we conclude that the evidence of causal involvement is somewhat mixed. We highlight the potential role of the thalamus and striatum in ASD and emphasize the need for studies that directly compare scanning during multiple cognitive states in addition to the resting-state.

Overt social interaction and resting state in young adult males with autism: core and contextual neural features

Conversation is an important and ubiquitous social behaviour. Individuals with autism spectrum disorder (autism) without intellectual disability often have normal structural language abilities but deficits in social aspects of communication like pragmatics, prosody, and eye contact. Previous studies of resting state activity suggest that intrinsic connections among neural circuits involved with social processing are disrupted in autism, but to date no neuroimaging study has examined neural activity during the most commonplace yet challenging social task: spontaneous conversation. Here we used functional MRI to scan autistic males (n = 19) without intellectual disability and age- and IQ-matched typically developing control subjects (n = 20) while they engaged in a total of 193 face-to-face interactions. Participants completed two kinds of tasks: conversation, which had high social demand, and repetition, which had low social demand. Autistic individuals showed abnormally increased task-driven interregional temporal correlation relative to controls, especially among social processing regions and during high social demand. Furthermore, these increased correlations were associated with parent ratings of participants' social impairments. These results were then compared with previously-acquired resting state data (56 autism, 62 control subjects). While some interregional correlation levels varied by task or rest context, others were strikingly similar across both task and rest, namely increased correlation among the thalamus, dorsal and ventral striatum, somatomotor, temporal and prefrontal cortex in the autistic individuals, relative to the control groups. These results suggest a basic distinction. Autistic cortico-cortical interactions vary by context, tending to increase relative to controls during task and decrease during test. In contrast, striato- and thalamocortical relationships with socially engaged brain regions are increased in both task and rest, and may be core to the condition of autism.

Sex-Dependent Effects of 2,2',3,5',6-Pentachlorobiphenyl on Dendritic Arborization of Primary Mouse Neurons

Early life exposures to environmental contaminants are implicated in the pathogenesis of many neurodevelopmental disorders (NDDs). These disorders often display sex biases, but whether environmental neurotoxicants act in a sex-dependent manner to modify neurodevelopment is largely unknown. Since altered dendritic morphology is associated with many NDDs, we tested the hypothesis that male and female primary mouse neurons are differentially susceptible to the dendrite-promoting activity of 2,2',3,5',6-pentachlorobiphenyl (PCB 95). Hippocampal and cortical neuron-glia co-cultures were exposed to vehicle (0.1% dimethylsulfoxide) or PCB 95 (100 fM-1 μM) from day in vitro 7-9. As determined by Sholl analysis, PCB 95-enhanced dendritic growth in female but not male hippocampal and cortical neurons. In contrast, both male and female neurons responded to bicuculline with increased dendritic complexity. Detailed morphometric analyses confirmed that PCB 95 effects on the number and length of primary and nonprimary dendrites varied depending on sex, brain region and PCB concentration, and that female neurons responded more consistently with increased dendritic growth and at lower concentrations of PCB 95 than their male counterparts. Exposure to PCB 95 did not alter cell viability or the ratio of neurons to glia in cultures of either sex. These results demonstrate that cultured female mouse hippocampal and cortical neurons are more sensitive than male neurons to the dendrite-promoting activity of PCB 95, and suggest that mechanisms underlying PCB 95-induced dendritic growth are sex-dependent. These data highlight the importance of sex in neuronal responses to environmental neurotoxicants.

Extreme male developmental trajectories of homotopic brain connectivity in autism

It has been proposed that autism spectrum disorder (ASD) may be characterized by an extreme male brain (EMB) pattern of brain development. Here, we performed the first investigation of how age-related changes in functional brain connectivity may be expressed differently in females and males with ASD. We analyzed resting-state functional magnetic resonance imaging data of 107 typically developing (TD) females, 114 TD males, 104 females, and 115 males with ASD (6-26 years) from the autism brain imaging data exchange repository. We explored how interhemispheric homotopic connectivity and its maturational curvatures change across groups. Differences between ASD and TD and between females and males with ASD were observed for the rate of changes in connectivity in the absence of overall differences in connectivity. The largest portion of variance in age-related changes in connectivity was described through similarities between TD males, ASD males, and ASD females, in contrast to TD females. We found that shape of developmental curvature is associated with symptomatology in both males and females with ASD. We demonstrated that females and males with ASD tended to follow the male pattern of developmental changes in interhemispheric connectivity, supporting the EMB theory of ASD.

Sex differences of brain and their implications for personalized therapy

Nowadays, it is known that the sex differences regard many organs, e.g., liver, vessels, pancreas, lungs, bronchi and also the brain. Sex differences are not just a matter of ethical and moral principles, as they are central to explain many still unknown diseases and their understanding is a prerequisite to develop an effective therapy for each individual. This review reports on those sex differences that are not only macroscopic and morphological, but also involve molecular and functional dimorphism in the brain. It will recapitulate the main structural differences between male and female brain including the neurotransmission systems; in particular, the main objective is to identify a correlation, already known or to be investigated in the future, between the differences that characterize male and female brains from a morphological and biochemical point of view and neurological syndromes. This correlation could provide a starting point for future scientific research aimed to investigate and define a personalized therapy.

A Personalized Autism Diagnosis CAD System Using a Fusion of Structural MRI and Resting-State Functional MRI Data

Autism spectrum disorder is a neuro-developmental disorder that affects the social abilities of the patients. Yet, the gold standard of autism diagnosis is the autism diagnostic observation schedule (ADOS). In this study, we are implementing a computer-aided diagnosis system that utilizes structural MRI (sMRI) and resting-state functional MRI (fMRI) to demonstrate that both anatomical abnormalities and functional connectivity abnormalities have high prediction ability of autism. The proposed system studies how the anatomical and functional connectivity metrics provide an overall diagnosis of whether the subject is autistic or not and are correlated with ADOS scores. The system provides a personalized report per subject to show what areas are more affected by autism-related impairment. Our system achieved accuracies of 75% when using fMRI data only, 79% when using sMRI data only, and 81% when fusing both together. Such a system achieves an important next step towards delineating the neurocircuits responsible for the autism diagnosis and hence may provide better options for physicians in devising personalized treatment plans.

Genetic mutations in Ca2+ signaling alter dendrite morphology and social approach in juvenile mice

Dendritic morphology is a critical determinant of neuronal connectivity, and calcium signaling plays a predominant role in shaping dendrites. Altered dendritic morphology and genetic mutations in calcium signaling are both associated with neurodevelopmental disorders (NDDs). In this study we tested the hypothesis that dendritic arborization and NDD-relevant behavioral phenotypes are altered by human mutations that modulate calcium-dependent signaling pathways implicated in NDDs. The dendritic morphology of pyramidal neurons in CA1 hippocampus and somatosensory cortex was quantified in Golgi-stained brain sections from juvenile mice of both sexes expressing either a human gain-of-function mutation in ryanodine receptor 1 (T4826I-RYR1), a human CGG repeat expansion (170-200 CGG repeats) in the fragile X mental retardation gene 1 (FMR1 premutation), both mutations (double mutation; DM), or wildtype mice. In hippocampal neurons, increased dendritic arborization was observed in male T4826I-RYR1 and, to a lesser extent, male FMR1 premutation neurons. Dendritic morphology of cortical neurons was altered in both sexes of FMR1 premutation and DM animals with the most pronounced differences seen in DM females. Genotype also impaired behavior, as assessed using the three-chambered social approach test. The most striking lack of sociability was observed in DM male and female mice. In conclusion, mutations that alter the fidelity of calcium signaling enhance dendritic arborization in a brain region- and sex-specific manner and impair social behavior in juvenile mice. The phenotypic outcomes of these mutations likely provide a susceptible biological substrate for additional environmental stressors that converge on calcium signaling to determine individual NDD risk.

Evaluation of Altered Functional Connections in Male Children With Autism Spectrum Disorders on Multiple-Site Data Optimized With Machine Learning

No univocal and reliable brain-based biomarkers have been detected to date in Autism Spectrum Disorders (ASD). Neuroimaging studies have consistently revealed alterations in brain structure and function of individuals with ASD; however, it remains difficult to ascertain the extent and localization of affected brain networks. In this context, the application of Machine Learning (ML) classification methods to neuroimaging data has the potential to contribute to a better distinction between subjects with ASD and typical development controls (TD). This study is focused on the analysis of resting-state fMRI data of individuals with ASD and matched TD, available within the ABIDE collection. To reduce the multiple sources of heterogeneity that impact on understanding the neural underpinnings of autistic condition, we selected a subgroup of 190 subjects (102 with ASD and 88 TD) according to the following criteria: male children (age range: 6.5-13 years); rs-fMRI data acquired with open eyes; data from the University sites that provided the largest number of scans (KKI, NYU, UCLA, UM). Connectivity values were evaluated as the linear correlation between pairs of time series of brain areas; then, a Linear kernel Support Vector Machine (L-SVM) classification, with an inter-site cross-validation scheme, was carried out. A permutation test was conducted to identify over-connectivity and under-connectivity alterations in the ASD group. The mean L-SVM classification performance, in terms of the area under the ROC curve (AUC), was 0.75 ± 0.05. The highest performance was obtained using data from KKI, NYU and UCLA sites in training and data from UM as testing set (AUC = 0.83). Specifically, stronger functional connectivity (FC) in ASD with respect to TD involve (p < 0.001) the angular gyrus with the precuneus in the right (R) hemisphere, and the R frontal operculum cortex with the pars opercularis of the left (L) inferior frontal gyrus. Weaker connections in ASD group with respect to TD are the intra-hemispheric R temporal fusiform cortex with the R hippocampus, and the L supramarginal gyrus with L planum polare. The results indicate that both under- and over-FC occurred in a selected cohort of ASD children relative to TD controls, and that these functional alterations are spread in different brain networks.

A Novel Biomarker of Compensatory Recruitment of Face Emotional Imagery Networks in Autism Spectrum Disorder

Imagery of facial expressions in Autism Spectrum Disorder (ASD) is likely impaired but has been very difficult to capture at a neurophysiological level. We developed an approach that allowed to directly link observation of emotional expressions and imagery in ASD, and to derive biomarkers that are able to classify abnormal imagery in ASD. To provide a handle between perception and action imagery cycles it is important to use visual stimuli exploring the dynamical nature of emotion representation. We conducted a case-control study providing a link between both visualization and mental imagery of dynamic facial expressions and investigated source responses to pure face-expression contrasts. We were able to replicate the same highly group discriminative neural signatures during action observation (dynamical face expressions) and imagery, in the precuneus. Larger activation in regions involved in imagery for the ASD group suggests that this effect is compensatory. We conducted a machine learning procedure to automatically identify these group differences, based on the EEG activity during mental imagery of facial expressions. We compared two classifiers and achieved an accuracy of 81% using 15 features (both linear and non-linear) of the signal from theta, high-beta and gamma bands extracted from right-parietal locations (matching the precuneus region), further confirming the findings regarding standard statistical analysis. This robust classification of signals resulting from imagery of dynamical expressions in ASD is surprising because it far and significantly exceeds the good classification already achieved with observation of neutral face expressions (74%). This novel neural correlate of emotional imagery in autism could potentially serve as a clinical interventional target for studies designed to improve facial expression recognition, or at least as an intervention biomarker.

3,3'-Dichlorobiphenyl (PCB 11) promotes dendritic arborization in primary rat cortical neurons via a CREB-dependent mechanism

PCB 11 (3,3'-dichlorobiphenyl), a contemporary congener produced as a byproduct of current pigment production processes, has recently emerged as a prevalent worldwide pollutant. We recently demonstrated that exposure to PCB 11 increases dendritic arborization in vitro, but the mechanism(s) mediating this effect remain unknown. To address this data gap, primary cortical neuron-glia co-cultures derived from neonatal Sprague-Dawley rats were exposed for 48 h to either vehicle (0.1% DMSO) or PCB 11 at concentrations ranging from 1 fM to 1 nM in the absence or presence of pharmacologic antagonists of established molecular targets of higher chlorinated PCBs. Reporter cell lines were used to test activity of PCB 11 at the aryl hydrocarbon receptor (AhR) and thyroid hormone receptor (THR). PCB 11 lacked activity at the AhR and THR, and antagonism of these receptors had no effect on the dendrite-promoting activity of PCB 11. Pharmacologic antagonism of various calcium channels or treatment with antioxidants also did not alter PCB 11-induced dendritic arborization. In contrast, pharmacologic blockade or shRNA knockdown of cAMP response element-binding protein (CREB) significantly decreased dendritic growth in PCB 11-exposed cultures, suggesting PCB 11 promotes dendritic growth via CREB-mediated mechanisms. Since CREB signaling is crucial for normal neurodevelopment, and perturbations of CREB signaling have been associated with neurodevelopmental disorders, our findings suggest that this contemporary pollutant poses a threat to the developing brain, particularly in individuals with heritable mutations that promote CREB signaling.

Using resting state functional MRI to build a personalized autism diagnosis system

Autism spectrum disorder (ASD) is a neuro-developmental disorder associated with social impairments, communication difficulties, and restricted and repetitive behaviors. Yet, there is no confirmed cause identified for ASD. Studying the functional connectivity of the brain is an emerging technique used in diagnosing and understanding ASD. In this study, we obtained the resting state functional MRI data of 283 subjects from the National Database of Autism Research (NDAR). An automated autism diagnosis system was built using the data from NDAR. The proposed system is machine learning based. Power spectral densities (PSDs) of time courses corresponding to the spatial activation areas are used as input features, feeds them to a stacked autoencoder then builds a classifier using probabilistic support vector machines. Over the used dataset, around 90% of sensitivity, specificity and accuracy was achieved by our machine learning system. Moreover, the system generalization ability was checked over two different prevalence values, one for the general population and the other for the of high risk population, and the system proved to be very generalizable, especially among the population of high risk. The proposed system generates a full personalized report for each subject, along with identifying the global differences between ASD and typically developed (TD) subjects and its ability to diagnose autism. It shows the impacted areas and the severity of implications. From the clinical aspect, this report is considered very valuable as it helps in both predicting and understanding behavior of autistic subjects. Moreover, it helps in designing a plan for personalized treatment per each individual subject. The proposed work is taking a step towards achieving personalized medicine in autism which is the ultimate goal of our group's research efforts in this area.

Brain Connectivity and Neuroimaging of Social Networks in Autism

Impairments in social communication (SC) predominate among the core diagnostic features of autism spectrum disorders (ASDs). Neuroimaging has revealed numerous findings of atypical activity and connectivity of 'social brain' networks, yet no consensus view on crucial developmental causes of SC deficits has emerged. Aside from methodological challenges, the deeper problem concerns the clinical label of ASD. While genetic studies have not comprehensively explained the causes of nonsyndromic ASDs, they highlight that the clinical label encompasses many etiologically different disorders. The question of how potential causes and etiologies converge onto a comparatively narrow set of SC deficits remains. Only neuroimaging designs searching for subtypes within ASD cohorts (rather than conventional group level designs) can provide translationally informative answers.

Partially impaired functional connectivity states between right anterior insula and default mode network in autism spectrum disorder

Time-invariant resting-state functional connectivity studies have illuminated the crucial role of the right anterior insula (rAI) in prominent social impairments of autism spectrum disorder (ASD). However, a recent dynamic connectivity study demonstrated that rather than being stationary, functional connectivity patterns of the rAI vary significantly across time. The present study aimed to explore the differences in functional connectivity in dynamic states of the rAI between individuals with ASD and typically developing controls (TD). Resting-state functional magnetic resonance imaging data obtained from a publicly available database were analyzed in 209 individuals with ASD and 298 demographically matched controls. A k-means clustering algorithm was utilized to obtain five dynamic states of functional connectivity of the rAI. The temporal properties, frequency properties, and meta-analytic decoding were first identified in TD group to obtain the characteristics of each rAI dynamic state. Multivariate analysis of variance was then performed to compare the functional connectivity patterns of the rAI between ASD and TD groups in obtained states. Significantly impaired connectivity was observed in ASD in the ventral medial prefrontal cortex and posterior cingulate cortex, which are two critical hubs of the default mode network (DMN). States in which ASD showed decreased connectivity between the rAI and these regions were those more relevant to socio-cognitive processing. From a dynamic perspective, these findings demonstrate partially impaired resting-state functional connectivity patterns between the rAI and DMN across states in ASD, and provide novel insights into the neural mechanisms underlying social impairments in individuals with ASD.

Personalized Intrinsic Network Topography Mapping and Functional Connectivity Deficits in Autism Spectrum Disorder

BACKGROUND

Recent advances in techniques using functional magnetic resonance imaging data demonstrate individually specific variation in brain architecture in healthy individuals. To our knowledge, the effects of individually specific variation in complex brain disorders have not been previously reported.

METHODS

We developed a novel approach (Personalized Intrinsic Network Topography, PINT) for localizing individually specific resting-state networks using conventional resting-state functional magnetic resonance imaging scans. Using cross-sectional data from participants with autism spectrum disorder (ASD; n = 393) and typically developing (TD) control participants (n = 496) across 15 sites, we tested: 1) effect of diagnosis and age on the variability of intrinsic network locations and 2) whether prior findings of functional connectivity differences in persons with ASD compared with TD persons remain after PINT application.

RESULTS

We found greater variability in the spatial locations of resting-state networks within individuals with ASD compared with those in TD individuals. For TD persons, variability decreased from childhood into adulthood and increased in late life, following a U-shaped pattern that was not present in those with ASD. Comparison of intrinsic connectivity between groups revealed that the application of PINT decreased the number of hypoconnected regions in ASD.

CONCLUSIONS

Our results provide a new framework for measuring altered brain functioning in neurodevelopmental disorders that may have implications for tracking developmental course, phenotypic heterogeneity, and ultimately treatment response. We underscore the importance of accounting for individual variation in the study of complex brain disorders.