Abnormality of Early White Matter Development in Tuberous Sclerosis Complex and Autism Spectrum Disorder: Longitudinal Analysis of Diffusion Tensor Imaging Measures.

Background: Abnormalities in white matter development may influence development of autism spectrum disorder in tuberous sclerosis complex (TSC). Our goals for this study were as follows: (1) use data from a longitudinal neuroimaging study of tuberous sclerosis complex (TACERN) to develop optimized linear mixed effects models for analyzing longitudinal, repeated diffusion tensor imaging metrics (fractional anisotropy, mean diffusivity) pertaining to select white matter tracts, in relation to positive Autism Diagnostic Observation Schedule-Second Edition classification at 36 months, and (2) perform an exploratory analysis using optimized models applied to all white matter tracts from these data. Methods: Eligible participants (3-12 months) underwent brain magnetic resonance imaging (MRI) at repeated time points from ages 3 to 36 months. Positive Autism Diagnostic Observation Schedule-Second Edition classification at 36 months was used. Linear mixed effects models were fine-tuned separately for fractional anisotropy values (using fractional anisotropy corpus callosum as test outcome) and mean diffusivity values (using mean diffusivity right posterior limb internal capsule as test outcome). Fixed effects included participant age, within-participant longitudinal age, and autism spectrum disorder diagnosis. Results: Analysis included data from n = 78. After selecting separate optimal models for fractional anisotropy and mean diffusivity values, we applied these models to fractional anisotropy and mean diffusivity of all 27 white matter tracts. Fractional anisotropy corpus callosum was related to positive Autism Diagnostic Observation Schedule-Second Edition classification (coefficient = 0.0093, P = .0612), and mean diffusivity right inferior cerebellar peduncle was related to positive Autism Diagnostic Observation Schedule-Second Edition classification (coefficient = -0.00002071, P = .0445), though these findings were not statistically significant after multiple comparisons correction. Conclusion: These optimized linear mixed effects models possibly implicate corpus callosum and cerebellar pathology in development of autism spectrum disorder in tuberous sclerosis complex, but future studies are needed to replicate these findings and explore contributors of heterogeneity in these models.

Neuroanatomy of autism: what is the role of the cerebellum?

Autism (or autism spectrum disorder) was initially defined as a psychiatric disorder, with the likely cause maternal behavior (the very destructive "refrigerator mother" theory). It took several decades for research into brain mechanisms to become established. Both neuropathological and imaging studies found differences in the cerebellum in autism spectrum disorder, the most widely documented being a decreased density of Purkinje cells in the cerebellar cortex. The popular interpretation of these results is that cerebellar neuropathology is a critical cause of autism spectrum disorder. We challenge that view by arguing that if fewer Purkinje cells are critical for autism spectrum disorder, then any condition that causes the loss of Purkinje cells should also cause autism spectrum disorder. We will review data on damage to the cerebellum from cerebellar lesions, tumors, and several syndromes (Joubert syndrome, Fragile X, and tuberous sclerosis). Collectively, these studies raise the question of whether the cerebellum really has a role in autism spectrum disorder. Autism spectrum disorder is now recognized as a genetically caused developmental disorder. A better understanding of the genes that underlie the differences in brain development that result in autism spectrum disorder is likely to show that these genes affect the development of the cerebellum in parallel with the development of the structures that do underlie autism spectrum disorder.

Decreased brain iron deposition based on quantitative susceptibility mapping correlates with reduced neurodevelopmental status in children with autism spectrum disorder.

To investigate potential correlations between the susceptibility values of certain brain regions and the severity of disease or neurodevelopmental status in children with autism spectrum disorder (ASD), 18 ASD children and 15 healthy controls (HCs) were recruited. The neurodevelopmental status was assessed by the Gesell Developmental Schedules (GDS) and the severity of the disease was evaluated by the Autism Behavior Checklist (ABC). Eleven brain regions were selected as regions of interest and the susceptibility values were measured by quantitative susceptibility mapping. To evaluate the diagnostic capacity of susceptibility values in distinguishing ASD and HC, the receiver operating characteristic (ROC) curve was computed. Pearson and Spearman partial correlation analysis were used to depict the correlations between the susceptibility values, the ABC scores, and the GDS scores in the ASD group. ROC curves showed that the susceptibility values of the left and right frontal white matter had a larger area under the curve in the ASD group. The susceptibility value of the right globus pallidus was positively correlated with the GDS-fine motor scale score. These findings indicated that the susceptibility value of the right globus pallidus might be a viable imaging biomarker for evaluating the neurodevelopmental status of ASD children.

A de novo frameshift variant in MED13 gene in a patient with autism spectrum disorder and magnetic resonance imaging abnormalities mimicking tuberous sclerosis.

The mediator complex subunit 13 (MED13) gene is implicated in neurodevelopmental disorders including autism spectrum disorder (ASD), intellectual disability, and speech delay with varying severity and course. Additional, extra central nervous system, features include eye or vision problems, hypotonia, congenital heart abnormalities, and dysmorphisms. We describe a 7-year- and 4-month-old girl evaluated for ASD whose brain magnetic resonance imaging was suggestive of multiple cortical tubers. The exome sequencing (ES - trio analysis) uncovered a unique, de novo, frameshift variant in the MED13 gene (c.4880del, D1627Vfs*17), with a truncating effect on the protein. This case report thus expands the phenotypic spectrum of MED13-related disorders to include brain abnormalities.

Multiple Classification of Brain MRI Autism Spectrum Disorder by Age and Gender Using Deep Learning.

The fact that the rapid and definitive diagnosis of autism cannot be made today and that autism cannot be treated provides an impetus to look into novel technological solutions. To contribute to the resolution of this problem through multiple classifications by considering age and gender factors, in this study, two quadruple and one octal classifications were performed using a deep learning (DL) approach. Gender in one of the four classifications and age groups in the other were considered. In the octal classification, classes were created considering gender and age groups. In addition to the diagnosis of ASD (Autism Spectrum Disorders), another goal of this study is to find out the contribution of gender and age factors to the diagnosis of ASD by making multiple classifications based on age and gender for the first time. Brain structural MRI (sMRI) scans of participators with ASD and TD (Typical Development) were pre-processed in the system originally designed for this purpose. Using the Canny Edge Detection (CED) algorithm, the sMRI image data was cropped in the data pre-processing stage, and the data set was enlarged five times with the data augmentation (DA) techniques. The most optimal convolutional neural network (CNN) models were developed using the grid search optimization (GSO) algorism. The proposed DL prediction system was tested with the five-fold cross-validation technique. Three CNN models were designed to be used in the system. The first of these models is the quadruple classification model created by taking gender into account (model 1), the second is the quadruple classification model created by taking into account age (model 2), and the third is the eightfold classification model created by taking into account both gender and age (model 3). ). The accuracy rates obtained for all three designed models are 80.94, 85.42 and 67.94, respectively. These obtained accuracy rates were compared with pre-trained models by using the transfer learning approach. As a result, it was revealed that age and gender factors were effective in the diagnosis of ASD with the system developed for ASD multiple classifications, and higher accuracy rates were achieved compared to pre-trained models.

An Analysis of Scoliosis in Autism Spectrum Disorder.

BACKGROUND: Children with autism/Asperger are grouped into the diagnosis of autism spectrum disorder (ASD). It remains uncertain whether children with ASD and scoliosis have radiographic and clinical outcomes similar to idiopathic scoliosis (IS) patients. METHODS: A single-center, retrospective review of a prospective scoliosis registry evaluated patients who had a posterior spinal fusion±Anterior Spinal Fusion and an underlying diagnosis of ASD between 1990 and 2021. A 2:1 match with AIS patients by age and sex was compared using demographic, radiographic, intraoperative, and SRS-22/30 variables. RESULTS: Thirty patients with ASD (63% male, mean age at surgery 14.6±2.5 y) met inclusion criteria, with a follow-up of 2.46±1.00 years. Despite no differences in curve magnitude preoperatively, patients with ASD had a higher percent correction at 2-year follow-up (66% vs. 57%, P =0.01) and improved mean curve magnitude (20±10 degrees) at 2-year follow-up compared with IS patients (27±11 degrees, P <0.01). ASD patients had less lumbar lordosis preoperatively (40±12 vs. 53±14, P <0.01), but there were no significant differences in sagittal parameters at 2-year follow-up. There were no significant differences in the rate of complications at 2-year follow-up between ASD and AIS cohorts. CONCLUSIONS: Although patients with ASD exhibited decreased lordosis compared with IS patients preoperatively, their radiographic outcomes at 2-year follow-up were the same. In addition, ASD patients maintained greater curve correction than IS patients at 2 years follow-up. LEVEL OF EVIDENCE: Prognostic retrospective study.

Aspects of autism spectrum disorder and correlation with neuroimaging findings in tuberous sclerosis complex.

BACKGROUND: Tuberous sclerosis complex (TSC) patients may have different specific neuropsychological deficits related to the location of the tubers. Autism spectrum disorders (ASD) are common in TSC patients but the relationship between these diagnoses has not been formally explored. In this study we sought to examine brain Magnetic Resonance Imaging (MRI) findings in TSC patients with ASD. METHODS: We evaluated 34 TSC patients on the basis of DSM-V diagnostic criteria for ASD, Wechsler Intelligence Scale for Children (WISC-R), psychiatrist's examination and also structured parent interviews. The number and localization of the tubers, postcontrast signal characteristics of the tubers, SWI findings, DWI findings on brain MRI were recorded. Demographic features, epilepsy histories, number of antiseizure medications, cognitive status were eveluated also. Patients were divided into two groups: ASD group, which represented group 1 and group 2 consisting of patients without any ASD symptoms. RESULTS: In our study, the mean number of tuber count was 21.8 in patients with ASD patients (Group 1, n = 13) and 12.4 in other TSC patients without ASD (Group 2, n = 21). Rate of tubers in prefrontal cortex/whole tubers (0.51) in patients with ASD was determined to be higher in group 1 (p = 0.003). Also a significant difference was detected between generalize epileptiform activities on EEG and the rate of DRE (p = 0.002; p = 0.001) between groups. Cognitive disturbances and infantile spasm history were similar between groups. TSC2 mutations have been identified in 29 (86%) patients. CONCLUSION: The mean of total tuber count and the rate of the location in the prefrontal cortex were determined to be higher in TSC patients with ASD. Specific areas on brain MRI may help understanding the development of ASD in TSC patients.

White matter disruptions related to inattention and autism spectrum symptoms in tuberous sclerosis complex.

Tuberous sclerosis complex is a rare genetic multisystem condition that is associated with a high prevalence of neurodevelopmental disorders such as autism and attention-deficit/hyperactivity disorder. The underlying neural mechanisms of the emergence of these symptom domains in tuberous sclerosis complex remain unclear. Here, we use fixel-based analysis of diffusion-weighted imaging, which allows for the differentiation between multiple fibre populations within a voxel, to compare white matter properties in 16 participants with tuberous sclerosis complex (aged 11-19) and 12 age and sex matched control participants. We further tested associations between white matter alterations and autism and inattention symptoms as well as cognitive ability in participants with tuberous sclerosis complex. Compared to controls, participants with tuberous sclerosis complex showed reduced fibre density cross-section (FDC) in the dorsal branch of right superior longitudinal fasciculus and bilateral inferior longitudinal fasciculus, reduced fibre density (FD) in bilateral tapetum, and reduced fibre cross-section (FC) in the ventral branch of right superior longitudinal fasciculus. In participants with tuberous sclerosis complex, the extent of FDC reductions in right superior longitudinal fasciculus was significantly associated with autism traits (social communication difficulties and restricted, repetitive behaviours), whereas FDC reductions in right inferior longitudinal fasciculus were associated with inattention. The observed white matter alterations were unrelated to cognitive ability. Our findings shed light on the fibre-specific biophysical properties of white matter alterations in tuberous sclerosis complex and suggest that these regional changes are selectively associated with the severity of neurodevelopmental symptoms.

Cross-Disorder Analysis of Shared Genetic Components Between Cortical Structures and Major Psychiatric Disorders.

BACKGROUND AND HYPOTHESIS: Although large-scale neuroimaging studies have demonstrated similar patterns of structural brain abnormalities across major psychiatric disorders, the underlying genetic etiology behind these similar cross-disorder patterns is not well understood. STUDY DESIGN: We quantified the extent of shared genetic components between cortical structures and major psychiatric disorders (CS-MPD) by using genome-wide association study (GWAS) summary statistics of 70 cortical structures (surface area and thickness of the whole cortex and 34 cortical regions) and five major psychiatric disorders, consisting of attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SCZ). Cross-disorder analyses were then conducted to estimate the degree of similarity in CS-MPD shared genetic components among these disorders. STUDY RESULTS: The CS-MPD shared genetic components have medium-to-strong positive correlations in ADHD, BD, MDD, and SCZ (r = 0.415 to r = 0.806) while ASD was significantly correlated with ADHD, BD, and SCZ (r = 0.388 to r = 0.403). These pairwise correlations of CS-MPD shared genetic components among disorders were significantly associated with corresponding cross-disorder similarities in cortical structural abnormalities (r = 0.668), accounting for 44% variance. In addition, one latent shared factor consisted primarily of BD, MDD, and SCZ, explaining 62.47% of the total variance in CS-MPD shared genetic components of all disorders. CONCLUSIONS: The current results bridge the gap between shared cross-disorder heritability and shared structural brain abnormalities in major psychiatric disorders, providing important implications for a shared genetic basis of cortical structures in these disorders.

Magnetic resonance spectroscopy features of the thalamus and the cerebellum and their association with clinical features in children with autism spectrum disorder: a prospective study. / å­¤ç‹¬ç—‡è°±ç³»éšœç¢å„¿ç«¥ä¸˜è„‘å’Œå°è„‘ç£å ±æŒ¯æ³¢è°±ç‰¹å¾å’Œä¸´åºŠå ³ç³»çš„å‰çž»æ€§ç ”ç©¶.

OBJECTIVES: To study the changes in biochemical metabolites in the thalamus and the cerebellum and their association with clinical features in children with autism spectrum disorder (ASD). METHODS: In this prospective study, magnetic resonance spectroscopy (MRS) with point-resolved spatial selection was used to analyze the thalamus and the cerebellum at both sides in 50 children with ASD aged 2-6 years. Creatine (Cr) was as the internal standard to measure the relative values of N-acetylaspartate (NAA)/Cr, choline (Cho)/Cr, myoinositol (MI)/Cr, and glutamine and glutamate complex (Glx)/Cr, and the differences in metabolites and their association with clinical symptoms were compared. RESULTS: In the children with ASD, NAA/Cr in the left thalamus was positively correlated with the scores of hearing-language and hand-eye coordination in the Griffiths Development Scales-Chinese (P<0.05). Cho/Cr in the right cerebellum was positively correlated with the scores of personal-social competence, hearing-language, and hand-eye coordination (P<0.05). NAA/Cr and Glx/Cr in the left thalamus were positively correlated with those in the left cerebellum (P<0.05). There was no significant difference in metabolites between the left and right sides of the thalamus and the cerebellum in the children with ASD (P>0.05). CONCLUSIONS: There are metabolic disorders in the cerebellum and the thalamus in children with ASD, and there is a correlation between the changes of metabolites in the left cerebellum and the left thalamus. Some metabolic indexes are related to the clinical symptoms of ASD. MRS may reveal the pathological basis of ASD and provide a basis for diagnosis and prognosis assessment of ASD as a noninvasive and quantitative detection method.

A translational exploration of the effects of WNT2 variants on altered cortical structures in autism spectrum disorder.

BACKGROUND: Evidence suggests that cortical anatomy may be aytpical in autism spectrum disorder. The wingless-type MMTV integration site family, member 2 (WNT2), a candidate gene for autism spectrum disorder, may regulate cortical development. However, it is unclear whether WNT2 variants are associated with altered cortical thickness in autism spectrum disorder. METHODS: In a sample of 118 people with autism spectrum disorder and 122 typically developing controls, we investigated cortical thickness using FreeSurfer software. We then examined the main effects of the WNT2 variants and the interactions of group × SNP and age × SNP for each hemisphere and brain region that was altered in people with autism spectrum disorder. RESULTS: Compared to neurotypical controls, people with autism spectrum disorder showed reduced mean cortical thickness in both hemispheres and 9 cortical regions after false discovery rate correction, including the right cingulate gyrus, the orbital gyrus, the insula, the inferior frontal gyrus (orbital part and triangular part), the lateral occipitotemporal gyrus, the posterior transverse collateral sulcus, the lateral sulcus and the superior temporal sulcus. In the full sample, 2 SNPs of WNT2 (rs6950765 and rs2896218) showed age × SNP interactions for the mean cortical thickness of both hemispheres, the middle-posterior cingulate cortex and the superior temporal cortex. LIMITATIONS: We examined the genetic effect for each hemisphere and the 9 regions that were altered in autism spectrum disorder. The age effect we found in this cross-sectional study needs to be examined in longitudinal studies. CONCLUSION: Based on neuroimaging and genetic data, our findings suggest that WNT2 variants might be associated with altered cortical thickness in autism spectrum disorder. Whether and how these WNT2 variants might involve cortical thinning requires further investigation. TRIAL REGISTRATION: ClinicalTrials.gov no. NCT01582256. PROTOCOL REGISTRATION: National Institutes of Health no. NCT00494754.

Striatal dopamine synthesis capacity in autism spectrum disorder and its relation with social defeat: an [18F]-FDOPA PET/CT study.

Alterations in dopamine signalling have been implied in autism spectrum disorder (ASD), and these could be associated with the risk of developing a psychotic disorder in ASD adults. Negative social experiences and feelings of social defeat might result in an increase in dopamine functioning. However, few studies examined dopamine functioning in vivo in ASD. Here we examine whether striatal dopamine synthesis capacity is increased in ASD and associated with social defeat. Forty-four unmedicated, non-psychotic adults diagnosed with ASD and 22 matched controls, aged 18-30 years, completed a dynamic 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine positron emission tomography/computed tomography ([18F]-FDOPA PET/CT) scan to measure presynaptic dopamine synthesis capacity in the striatum. We considered unwanted loneliness, ascertained using the UCLA Loneliness Scale, as primary measure of social defeat. We found no statistically significant difference in striatal dopamine synthesis capacity between ASD and controls (F1,60 = 0.026, p = 0.87). In ASD, striatal dopamine synthesis capacity was not significantly associated with loneliness (ß = 0.01, p = 0.96). Secondary analyses showed comparable results when examining the associative, limbic, and sensorimotor sub-regions of the striatum (all p-values > 0.05). Results were similar before and after adjusting for age, sex, smoking-status, and PET/CT-scanner-type. In conclusion, in unmedicated, non-psychotic adults with ASD, striatal dopamine synthesis capacity is not increased and not associated with social defeat.

A Neuroimaging Preparation Protocol Tailored for Autism.

This paper describes the key basic elements required for a successful multi-parametric MRI data acquisition in awake children with autism. The procedure was designed by taking into account methodological challenges arising from the acquisition of Resting State fMRI (RS fMRI) data, and factors such as cost, time, and staff availability. The ultimate aim was to prepare an imaging preparation protocol with high transferability to the whole autism spectrum, adaptable for use in a multi-site research with multiple time points. As part of a randomized pharmaco-intervention study, 31 children aged 4-10 years with Neurofibromatosis 1 and autism underwent MR imaging at baseline and end of intervention. The protocol consisted of tailored habituation instructions including gradual exposure to scanner noise, a social stories booklet, positive incentive strategies, and Play Therapy support. Success rate for initial acquisition was 71% for GABA+ MR spectroscopy at either location, 87% for perfusion, and 67% for diffusion assessment, and 71% for RS fMRI. Qualitative data indicated that 84% parents found the habituation protocol helpful. LAY SUMMARY: Here we describe a protocol for brain Magnetic Resonance Imaging (MRI) tailored for children with ASD to help reduce stress and avoid sedation during scanning. This procedure can make advanced medical imaging more accessible and promote a better MRI experience for families of children with ASD.

Evoked and intrinsic brain network dynamics in children with autism spectrum disorder.

OBJECTIVE: Brain dynamics underlie flexible cognition and behavior, yet little is known regarding this relationship in autism spectrum disorder (ASD). We examined time-varying changes in functional co-activation patterns (CAPs) across rest and task-evoked brain states to characterize differences between children with ASD and typically developing (TD) children and identify relationships with severity of social behaviors and restricted and repetitive behaviors. METHOD: 17 children with ASD and 27 TD children ages 7-12 completed a resting-state fMRI scan and four runs of a non-cued attention switching task. Metrics indexing brain dynamics were generated from dynamic CAPs computed across three major large-scale brain networks: midcingulo-insular (M-CIN), medial frontoparietal (M-FPN), and lateral frontoparietal (L-FPN). RESULTS: Five time-varying CAPs representing dynamic co-activations among network nodes were identified across rest and task fMRI datasets. Significant Diagnosis × Condition interactions were observed for the dwell time of CAP 3, representing co-activation between nodes of the M-CIN and L-FPN, and the frequency of CAP 1, representing co-activation between nodes of the L-FPN. A significant brain-behavior association between dwell time of CAP 5, representing co-activation between nodes of the M-FPN, and social abilities was also observed across both groups of children. CONCLUSION: Analysis of brain co-activation patterns reveals altered dynamics among three core networks in children with ASD, particularly evident during later stages of an attention task. Dimensional analyses demonstrating relationships between M-FPN dwell time and social abilities suggest that metrics of brain dynamics may index individual differences in social cognition and behavior.

NeuroMark: An automated and adaptive ICA based pipeline to identify reproducible fMRI markers of brain disorders.

Many mental illnesses share overlapping or similar clinical symptoms, confounding the diagnosis. It is important to systematically characterize the degree to which unique and similar changing patterns are reflective of brain disorders. Increasing sharing initiatives on neuroimaging data have provided unprecedented opportunities to study brain disorders. However, it is still an open question on replicating and translating findings across studies. Standardized approaches for capturing reproducible and comparable imaging markers are greatly needed. Here, we propose a pipeline based on the priori-driven independent component analysis, NeuroMark, which is capable of estimating brain functional network measures from functional magnetic resonance imaging (fMRI) data that can be used to link brain network abnormalities among different datasets, studies, and disorders. NeuroMark automatically estimates features adaptable to each individual subject and comparable across datasets/studies/disorders by taking advantage of the reliable brain network templates extracted from 1828 healthy controls as guidance. Four studies including 2442 subjects were conducted spanning six brain disorders (schizophrenia, autism spectrum disorder, mild cognitive impairment, Alzheimer's disease, bipolar disorder, and major depressive disorder) to evaluate validity of the proposed pipeline from different perspectives (replication of brain abnormalities, cross-study comparison, identification of subtle brain changes, and multi-disorder classification using identified biomarkers). Our results highlight that NeuroMark effectively identified replicated brain network abnormalities of schizophrenia across different datasets; revealed interesting neural clues on the overlap and specificity between autism and schizophrenia; demonstrated brain functional impairments present to varying degrees in mild cognitive impairments and Alzheimer's disease; and captured biomarkers that achieved good performance in classifying bipolar disorder and major depressive disorder.

A Multimodal Study of the Contributions of Conduction Velocity to the Auditory Evoked Neuromagnetic Response: Anomalies in Autism Spectrum Disorder.

This multimodal imaging study used magnetoencephalography, diffusion magnetic resonance imaging (MRI), and gamma-aminobutyric acid (GABA) magnetic resonance spectroscopy (MRS) to identify and contrast the multiple physiological mechanisms associated with auditory processing efficiency in typically developing (TD) children and children with autism spectrum disorder (ASD). Efficient transmission of auditory input between the ear and auditory cortex is necessary for rapid encoding of auditory sensory information. It was hypothesized that the M50 auditory evoked response latency would be modulated by white matter microstructure (indexed by diffusion MRI) and by tonic inhibition (indexed by GABA MRS). Participants were 77 children diagnosed with ASD and 40 TD controls aged 7-17 years. A model of M50 latency with auditory radiation fractional anisotropy and age as independent variables was able to predict 52% of M50 latency variance in TD children, but only 12% of variance in ASD. The ASD group exhibited altered patterns of M50 latency modulation characterized by both higher variance and deviation from the expected structure-function relationship established with the TD group. The TD M50 latency model was used to identify a subpopulation of ASD who are significant "outliers" to the TD model. The ASD outlier group exhibited unexpectedly long M50 latencies in conjunction with significantly lower GABA levels. These findings indicate the dependence of electrophysiologic sensory response latency on underlying microstructure (white matter) and neurochemistry (synaptic activity). This study demonstrates the use of biologically based measures to stratify ASD according to their brain-level "building blocks" as an alternative to their behavioral phenotype. LAY SUMMARY: Children with ASD often have a slower brain response when hearing sounds. This study used multiple brain imaging techniques to examine the structural and neurochemical factors which control the brain's response time to auditory tones in children with ASD and TD children. The relationship between brain imaging measures and brain response time was also used to identify ASD subgroups. Autism Res 2020, 13: 1730-1745. © 2020 International Society for Autism Research and Wiley Periodicals LLC.

Brain morphological analysis in PTEN hamartoma tumor syndrome.

PTEN hamartoma tumor syndrome (PHTS) is a spectrum of hereditary cancer syndromes caused by germline mutations in PTEN. PHTS is of high interest, because of its high rate of neurological comorbidities including macrocephaly, autism spectrum disorder, and intellectual dysfunction. Since detailed brain morphology and connectivity of PHTS remain unclear, we quantitatively evaluated brain magnetic resonance imaging (MRI) in PHTS. Sixteen structural T1-weighted and 9 diffusion-weighted MR images from 12 PHTS patients and neurotypical controls were used for structural and high-angular resolution diffusion MRI (HARDI) tractography analyses. Mega-corpus callosum was observed in 75%, polymicrogyria in 33%, periventricular white matter lesions in 83%, and heterotopia in 17% of the PHTS participants. While gyrification index and hemispheric cortical thickness showed no significant differences between the two groups, significantly increased global and regional brain volumes, and regionally thicker cortices in PHTS participants were observed. HARDI tractography showed increased volume and length of callosal pathways, increased volume of the arcuate fasciculi (AF), and increased length of the bilateral inferior longitudinal fasciculi (ILF), bilateral inferior fronto-occipital fasciculi (IFOF), and bilateral uncinate fasciculus. A decrease in fractional anisotropy and an increased in apparent diffusion coefficient values of the AF, left ILF, and left IFOF in PHTS.

Imaging of PTEN-related abnormalities in the central nervous system.

The phosphatase and tensin homolog (PTEN) located at 10q23.31 is a tumor suppressor gene expressed ubiquitously, and loss of function mutations lead to aberrant growth, angiogenesis, and an increased risk for a variety of tumors. PTEN mutations have been associated with multiple abnormalities in the central nervous system, and a number of clinical phenotypes are now attributed to germline PTEN mutations, collectively referred to as PTEN hamartoma tumor syndrome (PHTS). Most notably, these include Cowden syndrome (CS), Bannayan-Riley-Ruvalcaba syndrome (BRRS), and autism spectrum disorders with macrocephaly. It is important to recognize the neuroimaging features associated with PTEN mutations to not only avoid misdiagnosis in cases of known PHTS but also to guide genetic testing in patients who do not yet have an established diagnosis. In this review, the central nervous system imaging features of PTEN-related disorders are discussed.

Left hemispheric deficit in the sustained neuromagnetic response to periodic click trains in children with ASD.

BACKGROUND: Deficits in perception and production of vocal pitch are often observed in people with autism spectrum disorder (ASD), but the neural basis of these deficits is unknown. In magnetoencephalogram (MEG), spectrally complex periodic sounds trigger two continuous neural responses-the auditory steady state response (ASSR) and the sustained field (SF). It has been shown that the SF in neurotypical individuals is associated with low-level analysis of pitch in the 'pitch processing center' of the Heschl's gyrus. Therefore, alternations in this auditory response may reflect atypical processing of vocal pitch. The SF, however, has never been studied in people with ASD. METHODS: We used MEG and individual brain models to investigate the ASSR and SF evoked by monaural 40 Hz click trains in boys with ASD (N = 35) and neurotypical (NT) boys (N = 35) aged 7-12-years. RESULTS: In agreement with the previous research in adults, the cortical sources of the SF in children were located in the left and right Heschl's gyri, anterolateral to those of the ASSR. In both groups, the SF and ASSR dominated in the right hemisphere and were higher in the hemisphere contralateral to the stimulated ear. The ASSR increased with age in both NT and ASD children and did not differ between the groups. The SF amplitude did not significantly change between the ages of 7 and 12 years. It was moderately attenuated in both hemispheres and was markedly delayed and displaced in the left hemisphere in boys with ASD. The SF delay in participants with ASD was present irrespective of their intelligence level and severity of autism symptoms. LIMITATIONS: We did not test the language abilities of our participants. Therefore, the link between SF and processing of vocal pitch in children with ASD remains speculative. CONCLUSION: Children with ASD demonstrate atypical processing of spectrally complex periodic sound at the level of the core auditory cortex of the left-hemisphere. The observed neural deficit may contribute to speech perception difficulties experienced by children with ASD, including their poor perception and production of linguistic prosody.

Cortical excitation-inhibition ratio mediates the effect of pre-attentive auditory processing deficits on interpersonal difficulties.

Several lines of evidence identify aberrant excitatory-inhibitory neural processes across autism and schizophrenia spectrum disorders, particularly within the psychosocial domain. Such neural processes include increased excitatory glutamate and reduced inhibitory GABA concentrations, which may affect auditory pre-attentive processing as indexed by the mismatch negativity (MMN); thus, an excitation-inhibition imbalance might lead to aberrant MMN, which might in turn drive the relationship between the MMN and psychosocial difficulties. This research has the potential to enhance the neurochemical understanding of the relationship between electrophysiology (MMN) and behavioural/clinical measures (psychosocial difficulties). Thirty-eight adults (18 male, 18-40 years) completed the Schizotypal Personality Questionnaire (SPQ) and Autism-Spectrum Quotient (AQ). Glutamate and GABA concentrations in bilateral superior temporal cortex (STC) were quantified using proton magnetic resonance spectroscopy (1H-MRS) while auditory MMN to a duration deviant was measured with magnetoencephalography. Spearman correlations probed the relationships between STC glutamate/GABA ratios, MMN amplitude and latency, and AQ and SPQ dimensions. Mediation effects of glutamate/GABA ratios on the relationship between MMN and AQ-SPQ dimensions were probed using causal mediation analysis. Only SPQ-interpersonal and AQ-communication were significantly correlated with right hemisphere glutamate/GABA ratios and MMN latency (ps < 0.05), which were themselves correlated (p = .035). Two mediation models were investigated, with right MMN latency as predictor and SPQ-interpersonal and AQ-communication as outcome variables. Right STC glutamate/GABA ratios significantly mediated the relationship between MMN latency and SPQ-interpersonal scores, but only partially mediated the relationship between MMN latency and AQ-communication scores. These findings support the growing body of literature pointing toward an excitation-inhibition imbalance that is central to psychosocial functioning across multi-dimensional spectrum disorders, such as autism and schizophrenia, and provides neurochemical indicators of the processes that underlie psychosocial dysfunction.