Cortical morphological markers in children with autism: a structural magnetic resonance imaging study of thickness, area, volume, and gyrification

An Examination of Family Transmission of Traits Measured by the Social Responsiveness Scale-Short Form

PURPOSE

The Social Responsiveness Scale (SRS) is frequently used in research settings to measure characteristics associated with autism spectrum disorders (ASD). A short version has been developed but not yet tested for certain properties of the full SRS, such as familiality. The purpose of this study was to determine if prior familiality findings for the full SRS can be replicated using the short form by measuring the associations of the parental Social Responsiveness Scale-Short Form (SRS-SF) scores with child ASD diagnoses and child SRS-SF scores.

METHODS

We used a nested case-control study within a longitudinal cohort study design. Participants were selected from the Nurses' Health Study II (NHS II). Cases were children of study participants who had been diagnosed with ASD, while controls had not been diagnosed with ASD and were frequency matched by year of birth to cases. 2144 out of 3161 eligible participants returned SRS forms for a child and at least one parent. Participants in NHS II completed SRS forms for their spouses and spouses completed SRS forms for NHS II participants. Parental SRS-SF scores were based on a subset of 16 questions from the SRS. ASD diagnosis among children was reported by the mothers and validated in a subset using the Autism Diagnostic Interview-Revised, as well as child SRS-SF scores.

RESULTS

Children whose parents both had elevated SRS-SF scores (those in the top 20% of the study distribution) had a higher odds of ASD diagnosis than those who did not have elevated parental scores (OR 2.25; 95% CI 1.41, 3.58). Additionally, children whose fathers had elevated SRS-SF scores had a higher odds of ASD diagnosis (OR 2.18; 95% CI 1.60, 2.97) than those whose fathers scores were not elevated. In sex-stratified analyses, male children with elevated parental SRS-SF scores had a higher odds of ASD diagnosis than those who did not have elevated parental scores. These associations were not as evident among female children. Parental SRS-SF scores also predicted child SRS-SF scores among controls.

CONCLUSION

These findings are similar to prior findings for the full SRS and support the ability of the SRS-SF to capture familiality of ASD-related traits.

3D CNN for neuropsychiatry: Predicting Autism with interpretable Deep Learning applied to minimally preprocessed structural MRI data

Predictive modeling approaches are enabling progress toward robust and reproducible brain-based markers of neuropsychiatric conditions by leveraging the power of multivariate analyses of large datasets. While deep learning (DL) offers another promising avenue to further advance progress, there are challenges related to implementation in 3D (best for MRI) and interpretability. Here, we address these challenges and describe an interpretable predictive pipeline for inferring Autism diagnosis using 3D DL applied to minimally processed structural MRI scans. We trained 3D DL models to predict Autism diagnosis using the openly available ABIDE I and II datasets (n = 1329, split into training, validation, and test sets). Importantly, we did not perform transformation to template space, to reduce bias and maximize sensitivity to structural alterations associated with Autism. Our models attained predictive accuracies equivalent to those of previous machine learning (ML) studies, while side-stepping the time- and resource-demanding requirement to first normalize data to a template. Our interpretation step, which identified brain regions that contributed most to accurate inference, revealed regional Autism-related alterations that were highly consistent with the literature, encompassing a left-lateralized network of regions supporting language processing. We have openly shared our code and models to enable further progress towards remaining challenges, such as the clinical heterogeneity of Autism and site effects, and to enable the extension of our method to other neuropsychiatric conditions.

Heterogeneity and convergence across seven neuroimaging modalities: a review of the autism spectrum disorder literature

Background

A growing body of literature classifies autism spectrum disorder (ASD) as a heterogeneous, complex neurodevelopmental disorder that often is identified prior to three years of age. We aim to provide a narrative review of key structural and functional properties that differentiate the neuroimaging profile of autistic youth from their typically developing (TD) peers across different neuroimaging modalities.

Methods

Relevant studies were identified by searching for key terms in PubMed, with the most recent search conducted on September 1, 2023. Original research papers were included if they applied at least one of seven neuroimaging modalities (structural MRI, functional MRI, DTI, MRS, fNIRS, MEG, EEG) to compare autistic children or those with a family history of ASD to TD youth or those without ASD family history; included only participants <18 years; and were published from 2013 to 2023.

Results

In total, 172 papers were considered for qualitative synthesis. When comparing ASD to TD groups, structural MRI-based papers (n = 26) indicated larger subcortical gray matter volume in ASD groups. DTI-based papers (n = 14) reported higher mean and radial diffusivity in ASD participants. Functional MRI-based papers (n = 41) reported a substantial number of between-network functional connectivity findings in both directions. MRS-based papers (n = 19) demonstrated higher metabolite markers of excitatory neurotransmission and lower inhibitory markers in ASD groups. fNIRS-based papers (n = 20) reported lower oxygenated hemoglobin signals in ASD. Converging findings in MEG- (n = 20) and EEG-based (n = 32) papers indicated lower event-related potential and field amplitudes in ASD groups. Findings in the anterior cingulate cortex, insula, prefrontal cortex, amygdala, thalamus, cerebellum, corpus callosum, and default mode network appeared numerous times across modalities and provided opportunities for multimodal qualitative analysis.

Conclusions

Comparing across neuroimaging modalities, we found significant differences between the ASD and TD neuroimaging profile in addition to substantial heterogeneity. Inconsistent results are frequently seen within imaging modalities, comparable study populations and research designs. Still, converging patterns across imaging modalities support various existing theories on ASD.

Structural and functional whole brain changes in autism spectrum disorder at different age stages

Autism spectrum disorder (ASD) is a developmental disorder involving regional changes and local neural disturbances. However, few studies have investigated the dysfunctional phenomenon across different age stages. This study explores the structural and functional brain changes across different developmental stages in individuals with ASD, focusing on childhood (6-12 years), adolescence (12-18 years), and adulthood (18 + years). Using a comprehensive set of neuroimaging metrics, including modulated and non-modulated voxel-based morphometry (VBM), regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF), and fractional ALFF (fALFF), we identified significant stage-specific alterations in both VBM and functional measurements. Our results reveal that ASD is associated with progressive and stage-specific abnormalities in brain structure and function, with distinct patterns emerging at each developmental stage. Specifically, we observed significant modulated VBM reductions in the precuneus, lentiform nucleus, and inferior parietal lobule, accompanied by increases in the midbrain and sub-gyral regions. Moreover, we observed unmodulated VBM increment in regions including lentiform nucleus and thalamus. Functionally, ReHo analyses demonstrated disrupted local synchronization in the medial frontal gyrus, while ALFF and fALFF metrics highlighted altered spontaneous brain activity in the sub-gyral and sub-lobar. Finally, correlation analyses revealed that stage-specific findings are closely linked to clinical social- and behavior-related scores, with VBM in the inferior parietal lobule and putamen as well as ReHo in supplemental motor area being significantly associated with restrictive repetitive behaviors in childhood. These findings underscore the importance of considering age-specific brain changes when studying ASD and suggest that targeted interventions may be necessary at different developmental stages.

Brain-Charting Autism and Attention-Deficit/Hyperactivity Disorder Reveals Distinct and Overlapping Neurobiology

BACKGROUND

Autism and attention-deficit/hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental conditions with complex underlying neurobiology that is still poorly understood. Despite overlapping presentation and sex-biased prevalence, autism and ADHD are rarely studied together and sex differences are often overlooked. Population modeling, often referred to as normative modeling, provides a unified framework for studying age-specific and sex-specific divergences in brain development.

METHODS

Here, we used population modeling and a large, multisite neuroimaging dataset (N = 4255 after quality control) to characterize cortical anatomy associated with autism and ADHD, benchmarked against models of average brain development based on a sample of more than 75,000 individuals. We also examined sex and age differences and relationship with autistic traits and explored the co-occurrence of autism and ADHD.

RESULTS

We observed robust neuroanatomical signatures of both autism and ADHD. Overall, autistic individuals showed greater cortical thickness and volume that was localized to the superior temporal cortex, whereas individuals with ADHD showed more global increases in cortical thickness but lower cortical volume and surface area across much of the cortex. The co-occurring autism+ADHD group showed a unique pattern of widespread increases in cortical thickness and certain decreases in surface area. We also found that sex modulated the neuroanatomy of autism but not ADHD, and there was an age-by-diagnosis interaction for ADHD only.

CONCLUSIONS

These results indicate distinct cortical differences in autism and ADHD that are differentially affected by age and sex as well as potentially unique patterns related to their co-occurrence.

Altered gyrification in chemotherapy-treated older long-term breast cancer survivors

PURPOSE

The purpose of this prospective longitudinal study was to evaluate the changes in brain surface gyrification in older long-term breast cancer survivors 5-15 years after chemotherapy treatment.

METHODS

Older breast cancer survivors aged ≥ 65 years treated with chemotherapy (C+) or without chemotherapy (C-) 5-15 years prior and age- and sex-matched healthy controls (HC) were recruited (time point 1 (TP1)) and followed up for 2 years (time point 2 (TP2)). Study assessments for both time points included neuropsychological (NP) testing with the NIH Toolbox cognition battery and cortical gyrification analysis based on brain MRI.

RESULTS

The study cohort with data for both TP1 and TP2 consisted of the following: 10 participants for the C+ group, 12 participants for the C- group, and 13 participants for the HC group. The C+ group had increased gyrification in six local gyral regions including the right fusiform, paracentral, precuneus, superior, middle temporal gyri and left pars opercularis gyrus, and it had decreased gyrification in two local gyral regions from TP1 to TP2 (p < .05, Bonferroni corrected). The C- and HC groups showed decreased gyrification only (p < .05, Bonferroni corrected). In the C+ group, changes in right paracentral gyrification and crystalized composite scores were negatively correlated (R = -0.76, p = .01).

CONCLUSIONS

Altered gyrification could be the neural correlate of cognitive changes in older chemotherapy-treated long-term breast cancer survivors.

Insight into brain sex differences of typically developed infants and brain pathologies: A systematic review

The continually advancing landscape of neuroscientific and imaging research has broadened our comprehension of sex differences encoded in the human brain, expanding from the hypothalamus and sexual behaviour to encompass the entire brain, including its diverse lobes, structures, and functions. However, less is known about sex differences in the brains of neonates and infants, despite their relevance to various sex-linked diseases that develop early in life. In this review, we provide a synopsis of the literature evidence on sex differences in the brains of neonates and infants at the morphological, structural and network levels. We also briefly overview the present evidence on the sex bias in some brain disorders affecting infants and neonates.

Gender Incongruence and Autistic Traits: Cerebral and Behavioral Underpinnings

Gender dysphoria and autism spectrum disorder (ASD) co-occur at high rates. Yet, it is unknown whether gender dysphoria and ASD are associated with common or distinct neurobiological correlates or how they relate to experiences of gender-related body incongruence. Using the Social Responsiveness Scale, we assessed autistic traits in 99 transgender and 99 cisgender individuals and investigated their associations with gender-related body incongruence, measured via a visually based "Body Morph" test, and with cortical thickness in the brain. Autistic traits were significantly higher among transgender individuals, and those with higher autistic traits had higher body incongruence scoring. Among transgender individuals, higher autistic traits were linked with a thinner cortex bilaterally in the temporal pole and the superior and inferior temporal gyri. Autistic traits were only partly associated with cortical morphology patterns previously reported in transgender individuals; instead, they were primarily linked to temporal lobe areas mediating social cognition. While replicating the previous literature on the increased prevalence of autistic traits among transgender individuals, this study reports specific regions in the brains of transgender individuals where cortical thickness is associated with autistic traits.

Ventral temporal and posteromedial sulcal morphology in autism spectrum disorder

Two parallel research tracks link the morphology of small and shallow indentations, or sulci, of the cerebral cortex with functional features of the cortex and human cognition, respectively. The first track identified a relationship between the mid-fusiform sulcus (MFS) in ventral temporal cortex (VTC) and cognition in individuals with Autism Spectrum Disorder (ASD). The second track identified a new sulcus, the inframarginal sulcus (IFRMS), that serves as a tripartite landmark within the posteromedial cortex (PMC). As VTC and PMC are structurally and functionally different in ASD, here, we integrated these two tracks and tested if there are morphological differences in VTC and PMC sulci in a sample of young (5-17 years old) male participants (50 participants with ASD and 50 neurotypical controls). Our approach replicates and extends recent findings in four ways. First, regarding replication, the standard deviation (STD) of MFS cortical thickness (CT) was increased in ASD. Second, MFS length was shorter in ASD. Third, the CT STD effect extended to other VTC and to PMC sulci. Fourth, additional morphological features of VTC sulci (depth, surface area, gray matter volume) and PMC sulci (mean CT) were decreased in ASD, including putative tertiary sulci, which emerge last in gestation and continue to develop after birth. To our knowledge, this study is the most extensive comparison of the sulcal landscape (including putative tertiary sulci) in multiple cortical expanses between individuals with ASD and NTs based on manually defined sulci at the level of individual hemispheres, providing novel targets for future studies of neurodevelopmental disorders more broadly.

Common and distinct cortical thickness alterations in youth with autism spectrum disorder and attention-deficit/hyperactivity disorder

BACKGROUND

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are neurodevelopmental disorders with overlapping behavioral features and genetic etiology. While brain cortical thickness (CTh) alterations have been reported in ASD and ADHD separately, the degree to which ASD and ADHD are associated with common and distinct patterns of CTh changes is unclear.

METHODS

We searched PubMed, Web of Science, Embase, and Science Direct from inception to 8 December 2023 and included studies of cortical thickness comparing youth (age less than 18) with ASD or ADHD with typically developing controls (TDC). We conducted a comparative meta-analysis of vertex-based studies to identify common and distinct CTh alterations in ASD and ADHD.

RESULTS

Twelve ASD datasets involving 458 individuals with ASD and 10 ADHD datasets involving 383 individuals with ADHD were included in the analysis. Compared to TDC, ASD showed increased CTh in bilateral superior frontal gyrus, left middle temporal gyrus, and right superior parietal lobule (SPL) and decreased CTh in right temporoparietal junction (TPJ). ADHD showed decreased CTh in bilateral precentral gyri, right postcentral gyrus, and right TPJ relative to TDC. Conjunction analysis showed both disorders shared reduced TPJ CTh located in default mode network (DMN). Comparative analyses indicated ASD had greater CTh in right SPL and TPJ located in dorsal attention network and thinner CTh in right TPJ located in ventral attention network than ADHD.

CONCLUSIONS

These results suggest shared thinner TPJ located in DMN is an overlapping neurobiological feature of ASD and ADHD. This alteration together with SPL alterations might be related to altered biological motion processing in ASD, while abnormalities in sensorimotor systems may contribute to behavioral control problems in ADHD. The disorder-specific thinner TPJ located in disparate attention networks provides novel insight into distinct symptoms of attentional deficits associated with the two neurodevelopmental disorders.

TRIAL REGISTRATION

PROSPERO CRD42022370620. Registered on November 9, 2022.

Relationship between autism and brain cortex surface area: genetic correlation and a two-sample Mendelian randomization study

BACKGROUND

Alterations in surface area (SA) in specific regions of the cortex have been reported in many individuals with autism spectrum disorder (ASD), however, the genetic background between ASD and SA is still unclear. This study estimated the genetic correlation and causal effect of ASD and cortical SA.

METHODS

Summarized data of genome-wide association studies (GWAS) were separately downloaded from the Psychiatric Genomics Consortium (18,381 cases of ASD, and 27,969 controls) and the Enhancing Neuroimaging Genetics through Meta-Analysis Consortium (33,992 participants of Europeans). We used Linkage disequilibrium score regression (LDSC) and Heritability Estimation from Summary Statistics (HESS) to calculate the heritability of each trait. As for the genetic correlation between ASD and SA, LDSC was used for global correlation and HESS was used to examine the local genetic covariance further. We used three Mendelian randomization (MR) methods, Inverse-variance weighted, MR-Egger, and weighted median to estimate the causal relationship.

RESULTS

LDSC observed a nominal significant genetic correlation (rg = 0.1229, P-value = 0.0346) between ASD and SA of the rostral anterior cingulate gyrus whereas analysis through HESS did not reveal any significant loci having genetic covariance. Based on MR results, statistically meaningful estimations were found in the following areas, postcentral cortex (β (SE) = 21.82 (7.84) mm, 95% CI: 6.46 to 37.19 mm, PIVW = 5.38 × 10- 3, PFDR = 3.09 × 10- 2), posterior cingulate gyrus (β (SE) = 6.23 (2.69) mm, 95% CI: 0.96 to 11.49 mm, PIVW = 2.05 × 10- 2, PFDR = 4.26 × 10- 2), supramarginal gyrus (β (SE) = 19.25 (8.43) mm, 95% CI: 29.29 to 35.77 mm, PIVW = 2.24 × 10- 2, PFDR = 4.31 × 10- 2).

CONCLUSION

Our results provided genetic evidence to support the opinion that individuals with ASD tend to develop differences in cortical SA of special areas. The findings contributed to understanding the genetic relationship between ASD and cortical SA.

Volume-based and Surface-Based Methods in Autism Compared with Healthy Controls Are Free surfer and CAT12 in Agreement?

Objectives

Autism Spectrum Disorder (ASD) encompasses a range of neurodevelopmental disorders, and early detection is crucial. This study aims to identify the Regions of Interest (ROIs) with significant differences between healthy controls and individuals with autism, as well as evaluate the agreement between FreeSurfer 6 (FS6) and Computational Anatomy Toolbox (CAT12) methods.

Materials & Methods

Surface-based and volume-based features were extracted from FS software and CAT12 toolbox for Statistical Parametric Mapping (SPM) software to estimate ROI-wise biomarkers. These biomarkers were compared between 18 males Typically Developing Controls (TDCs) and 40 male subjects with ASD to assess group differences for each method. Finally, agreement and regression analyses were performed between the two methods for TDCs and ASD groups.

Results

Both methods revealed ROIs with significant differences for each parameter. The Analysis of Covariance (ANCOVA) showed that both TDCs and ASD groups indicated a significant relationship between the two methods (p<0.001). The R2 values for TDCs and ASD groups were 0.692 and 0.680, respectively, demonstrating a moderate correlation between CAT12 and FS6. Bland-Altman graphs showed a moderate level of agreement between the two methods.

Conclusion

The moderate correlation and agreement between CAT12 and FS6 suggest that while some consistency is observed in the results, CAT12 is not a superior substitute for FS6 software. Further research is needed to identify a potential replacement for this method.

Cortical thickness abnormalities in autism spectrum disorder

The pathological mechanism of autism spectrum disorder (ASD) remains unclear. Nowadays, surface-based morphometry (SBM) based on structural magnetic resonance imaging (sMRI) techniques have reported cortical thickness (CT) variations in ASD. However, the findings were inconsistent and heterogeneous. This current meta-analysis conducted a whole-brain vertex-wise coordinate-based meta-analysis (CBMA) on CT studies to explore the most noticeable and robust CT changes in ASD individuals by applying the seed-based d mapping (SDM) program. A total of 26 investigations comprised 27 datasets were included, containing 1,635 subjects with ASD and 1470 HC, along with 94 coordinates. Individuals with ASD exhibited significantly altered CT in several regions compared to HC, including four clusters with thicker CT in the right superior temporal gyrus (STG.R), the left middle temporal gyrus (MTG.L), the left anterior cingulate/paracingulate gyri, the right superior frontal gyrus (SFG.R, medial orbital parts), as well as three clusters with cortical thinning including the left parahippocampal gyrus (PHG.L), the right precentral gyrus (PCG.R) and the left middle frontal gyrus (MFG.L). Adults with ASD only demonstrated CT thinning in the right parahippocampal gyrus (PHG.R), revealed by subgroup meta-analyses. Meta-regression analyses found that CT in STG.R was positively correlated with age. Meanwhile, CT in MFG.L and PHG.L had negative correlations with the age of ASD individuals. These results suggested a complicated and atypical cortical development trajectory in ASD, and would provide a deeper understanding of the neural mechanism underlying the cortical morphology in ASD.

Induction of cerebellar cortical neurogenesis immediately following valproic acid exposure in ferret kits

Introduction

Valproic acid (VPA) is an anticonvulsant/antiepileptic drug that regulates neurogenesis. Its effects vary depending on the timing of exposure and the types of neural progenitors involved. Neonatal exposure to VPA causes autism spectrum disorder-like behaviors in some mammalian species, including ferrets. Ferrets experience the cerebellar cortical histogenesis during early postnatal period. However, no studies have evaluated the effect of VPA on cerebellar corticohistogenesis. The present study aimed to determine the effects of VPA exposure on the developing cerebellar cortex in ferret kits with a particular focus on the cortical neurogenesis.

Methods

The experimental kits each received an intraperitoneal injection of VPA, 200 μg/g body weight, on postnatal days 6 and 7. EdU and BrdU were administered on postnatal days 5 and 7, respectively, to label cells proliferating prior to and following exposure to VPA.

Results

We found that 2 h post BrdU injection, BrdU-labeled cells were abundantly distributed in the internal granular layer (IGL), whereas EdU-labeled cells were primarily relegated to the inner pre-migratory zone of the external granular layer (EGL). The density of BrdU-single-labeled cells was significantly lower in the EGL and significantly higher in the IGL of the VPA-exposed group, as compared to the control group. Immunostaining for doublecortin, a marker of immature neurons, was observed in BrdU-single-labeled cells in the IGL of the VPA-exposed group, which was significantly higher than that observed in the control group. EdU-single-labeled cells that had proliferated prior to VPA exposure were also detected in the IGL. While the cell density remained unchanged, significant changes were observed in the proportions of EdU-single-labeled cells immunostained with marker antigens; higher proportion of PCNA immunostaining, but lower proportion of S100 immunostaining in the VPA-exposed group compared to the control group.

Discussion

These findings suggest the presence of progenitors in the IGL of the developing cerebellar cortex in ferret kits. We called them "internal granular progenitors." The progenitors may proliferate in response to VPA, leading the differentiated lineage more toward neurons than to glial cells. Thus, VPA may facilitate the differentiative division of internal granular progenitors to produce cerebellar granular neurons.

Brain-charting autism and attention deficit hyperactivity disorder reveals distinct and overlapping neurobiology

Background

Autism and attention deficit hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental conditions with complex underlying neurobiology. Despite overlapping presentation and sex-biased prevalence, autism and ADHD are rarely studied together, and sex differences are often overlooked. Normative modelling provides a unified framework for studying age-specific and sex-specific divergences in neurodivergent brain development.

Methods

Here we use normative modelling and a large, multi-site neuroimaging dataset to characterise cortical anatomy associated with autism and ADHD, benchmarked against models of typical brain development based on a sample of over 75,000 individuals. We also examined sex and age differences, relationship with autistic traits, and explored the co-occurrence of autism and ADHD (autism+ADHD).

Results

We observed robust neuroanatomical signatures of both autism and ADHD. Overall, autistic individuals showed greater cortical thickness and volume localised to the superior temporal cortex, whereas individuals with ADHD showed more global effects of cortical thickness increases but lower cortical volume and surface area across much of the cortex. The autism+ADHD group displayed a unique pattern of widespread increases in cortical thickness, and certain decreases in surface area. We also found evidence that sex modulates the neuroanatomy of autism but not ADHD, and an age-by-diagnosis interaction for ADHD only.

Conclusions

These results indicate distinct cortical differences in autism and ADHD that are differentially impacted by age, sex, and potentially unique patterns related to their co-occurrence.

A personalized classification of behavioral severity of autism spectrum disorder using a comprehensive machine learning framework

Autism Spectrum Disorder (ASD) is characterized as a neurodevelopmental disorder with a heterogeneous nature, influenced by genetics and exhibiting diverse clinical presentations. In this study, we dissect Autism Spectrum Disorder (ASD) into its behavioral components, mirroring the diagnostic process used in clinical settings. Morphological features are extracted from magnetic resonance imaging (MRI) scans, found in the publicly available dataset ABIDE II, identifying the most discriminative features that differentiate ASD within various behavioral domains. Then, each subject is categorized as having severe, moderate, or mild ASD, or typical neurodevelopment (TD), based on the behavioral domains of the Social Responsiveness Scale (SRS). Through this study, multiple artificial intelligence (AI) models are utilized for feature selection and classifying each ASD severity and behavioural group. A multivariate feature selection algorithm, investigating four different classifiers with linear and non-linear hypotheses, is applied iteratively while shuffling the training-validation subjects to find the set of cortical regions with statistically significant association with ASD. A set of six classifiers are optimized and trained on the selected set of features using 5-fold cross-validation for the purpose of severity classification for each behavioural group. Our AI-based model achieved an average accuracy of 96%, computed as the mean accuracy across the top-performing AI models for feature selection and severity classification across the different behavioral groups. The proposed AI model has the ability to accurately differentiate between the functionalities of specific brain regions, such as the left and right caudal middle frontal regions. We propose an AI-based model that dissects ASD into behavioral components. For each behavioral component, the AI-based model is capable of identifying the brain regions which are associated with ASD as well as utilizing those regions for diagnosis. The proposed system can increase the speed and accuracy of the diagnostic process and result in improved outcomes for individuals with ASD, highlighting the potential of AI in this area.

Application of Multimodal MRI in the Early Diagnosis of Autism Spectrum Disorders: A Review

Autism spectrum disorder (ASD) is a neurodevelopmental disorder in children. Early diagnosis and intervention can remodel the neural structure of the brain and improve quality of life but may be inaccurate if based solely on clinical symptoms and assessment scales. Therefore, we aimed to analyze multimodal magnetic resonance imaging (MRI) data from the existing literature and review the abnormal changes in brain structural-functional networks, perfusion, neuronal metabolism, and the glymphatic system in children with ASD, which could help in early diagnosis and precise intervention. Structural MRI revealed morphological differences, abnormal developmental trajectories, and network connectivity changes in the brain at different ages. Functional MRI revealed disruption of functional networks, abnormal perfusion, and neurovascular decoupling associated with core ASD symptoms. Proton magnetic resonance spectroscopy revealed abnormal changes in the neuronal metabolites during different periods. Decreased diffusion tensor imaging signals along the perivascular space index reflected impaired glymphatic system function in children with ASD. Differences in age, subtype, degree of brain damage, and remodeling in children with ASD led to heterogeneity in research results. Multimodal MRI is expected to further assist in early and accurate clinical diagnosis of ASD through deep learning combined with genomics and artificial intelligence.

White and gray matter correlates of theory of mind in autism: a voxel-based morphometry study

Autism spectrum disorder (ASD) is characterized by difficulties in theory of mind (ToM) and social communication. Studying structural and functional correlates of ToM in the brain and how autistic and nonautistic groups differ in terms of these correlates can help with diagnosis and understanding the biological mechanisms of ASD. In this study, we investigated white matter volume (WMV) and gray matter volume (GMV) differences between matching autistic and nonautistic samples, and how these structural features relate to age and ToM skills, indexed by the Reading the Mind in the Eyes (RMIE) measure. The results showed widespread GMV and WMV differences between the two groups in regions crucial for social processes. The autistic group did not express the typically observed negative GMV and positive WMV correlations with age at the same level as the nonautistic group, pointing to abnormalities in developmental structural changes. In addition, we found differences between the two groups in how GMV relates to ToM, particularly in the left frontal regions, and how WMV relates to ToM, mostly in the cingulate and corpus callosum. Finally, GMV in the left insula, a region that is part of the salience network, was found to be crucial in distinguishing ToM performance between the two groups.

Altered gyrification in chemotherapy-treated older long-term breast cancer survivors

Purpose

The purpose of this prospective longitudinal study was to evaluate the changes in brain surface gyrification in older long-term breast cancer survivors 5 to 15 years after chemotherapy treatment.

Methods

Older breast cancer survivors aged ≥ 65 years treated with chemotherapy (C+) or without chemotherapy (C-) 5-15 years prior and age & sex-matched healthy controls (HC) were recruited (time point 1 (TP1)) and followed up for 2 years (time point 2 (TP2)). Study assessments for both time points included neuropsychological (NP) testing with the NIH Toolbox cognition battery and cortical gyrification analysis based on brain MRI.

Results

The study cohort with data for both TP1 and TP2 consisted of the following: 10 participants for the C+ group, 12 participants for the C- group, and 13 participants for the HC group. The C+ group had increased gyrification in 6 local gyrus regions including the right fusiform, paracentral, precuneus, superior, middle temporal gyri and left pars opercularis gyrus, and it had decreased gyrification in 2 local gyrus regions from TP1 to TP2 (p < 0.05, Bonferroni corrected). The C- and HC groups showed decreased gyrification only (p < 0.05, Bonferroni corrected). In C+ group, changes in right paracentral gyrification and crystalized composite scores were negatively correlated (R = -0.76, p = 0.01).

Conclusions

Altered gyrification could be the neural correlate of cognitive changes in older chemotherapy-treated long-term breast cancer survivors.

Altered cortical gyrification, sulcal depth, and fractal dimension in the autism spectrum disorder comorbid attention-deficit/hyperactivity disorder than the autism spectrum disorder

Autism spectrum disorder (ASD) frequently occurs accompanied by attention-deficit/hyperactivity disorder (ADHD), which catches increasing attention. The comorbid diagnosis of ASD with ADHD (ASD + ADHD) is permitted in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-V). However, compared to autism spectrum disorder without other symptoms (ASD-only), the special neural underpinnings in ASD+ADHD remain unclear. Therefore, this study aimed to uncover the differences in cortical complexity between ASD + ADHD and ASD-only patients. A total of 114 ASD participants (i.e. containing 40 ASD + ADHD and 74 ASD-only participants) with T1-weighted magnetic resonance images were collected from the Autism Brain Imaging Data Exchange II. Afterward, a surface-based morphometry method was carried out to compare the cortical complexity (i.e. gyrification index, fractal dimension, and sulcal depth) between the ASD + ADHD and ASD-only cohorts. Results showed the increased fractal dimension in the right fusiform gyrus of the ASD + ADHD cohort in comparison to the ASD-only cohort. Moreover, the ASD + ADHD cohort exhibited increased sulcal depth in the left middle temporal gyrus/inferior temporal gyrus and right middle temporal gyrus compared to the ASD-only cohort. Last but not least, the increased gyrification index in the insula/postcentral gyrus was observed in the ASD + ADHD cohort in comparison to the ASD-only cohort. Overall, the present study contributes to the delineation of particular structural abnormalities in ASD + ADHD than ASD-only, enriching the evidence of the combined phenotype of ASD + ADHD.

The Link Between Autism and Sex-Related Neuroanatomy, and Associated Cognition and Gene Expression

OBJECTIVE

The male preponderance in prevalence of autism is among the most pronounced sex ratios across neurodevelopmental conditions. The authors sought to elucidate the relationship between autism and typical sex-differential neuroanatomy, cognition, and related gene expression.

METHODS

Using a novel deep learning framework trained to predict biological sex based on T₁-weighted structural brain images, the authors compared sex prediction model performance across neurotypical and autistic males and females. Multiple large-scale data sets comprising T₁-weighted MRI data were employed at four stages of the analysis pipeline: 1) pretraining, with the UK Biobank sample (>10,000 individuals); 2) transfer learning and validation, with the ABIDE data sets (1,412 individuals, 5-56 years of age); 3) test and discovery, with the EU-AIMS/AIMS-2-TRIALS LEAP data set (681 individuals, 6-30 years of age); and 4) specificity, with the NeuroIMAGE and ADHD200 data sets (887 individuals, 7-26 years of age).

RESULTS

Across both ABIDE and LEAP, features positively predictive of neurotypical males were on average significantly more predictive of autistic males (ABIDE: Cohen's d=0.48; LEAP: Cohen's d=1.34). Features positively predictive of neurotypical females were on average significantly less predictive of autistic females (ABIDE: Cohen's d=1.25; LEAP: Cohen's d=1.29). These differences in sex prediction accuracy in autism were not observed in individuals with ADHD. In autistic females, the male-shifted neurophenotype was further associated with poorer social sensitivity and emotional face processing while also associated with gene expression patterns of midgestational cell types.

CONCLUSIONS

The results demonstrate an increased resemblance in both autistic male and female individuals' neuroanatomy with male-characteristic patterns associated with typically sex-differential social cognitive features and related gene expression patterns. The findings hold promise for future research aimed at refining the quest for biological mechanisms underpinning the etiology of autism.

Gray matter microstructure differences in autistic males: A gray matter based spatial statistics study

BACKGROUND

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition. Understanding the brain's microstructure and its relationship to clinical characteristics is important to advance our understanding of the neural supports underlying ASD. In the current work, we implemented Gray-Matter Based Spatial Statistics (GBSS) to examine and characterize cortical microstructure and assess differences between typically developing (TD) and autistic males.

METHODS

A multi-shell diffusion MRI (dMRI) protocol was acquired from 83 TD and 70 autistic males (5-to-21-years) and fit to the DTI and NODDI models. GBSS was performed for voxelwise analysis of cortical gray matter (GM). General linear models were used to investigate group differences, while age-by-group interactions assessed age-related differences between groups. Within the ASD group, relationships between cortical microstructure and measures of autistic symptoms were investigated.

RESULTS

All dMRI measures were significantly associated with age across the GM skeleton. Group differences and age-by-group interactions are reported. Group-wise increases in neurite density in autistic individuals were observed across frontal, temporal, and occipital regions of the right hemisphere. Significant age-by-group interactions of neurite density were observed within the middle frontal gyrus, precentral gyrus, and frontal pole. Negative relationships between neurite dispersion and the ADOS-2 Calibrated Severity Scores (CSS) were observed within the ASD group.

DISCUSSION

Findings demonstrate group and age-related differences between groups in neurite density in ASD across right-hemisphere brain regions supporting cognitive processes. Results provide evidence of altered neurodevelopmental processes affecting GM microstructure in autistic males with implications for the role of cortical microstructure in the level of autistic symptoms.

CONCLUSION

Using dMRI and GBSS, our findings provide new insights into group and age-related differences of the GM microstructure in autistic males. Defining where and when these cortical GM differences arise will contribute to our understanding of brain-behavior relationships of ASD and may aid in the development and monitoring of targeted and individualized interventions.

Evaluation of brain structure abnormalities in children with autism spectrum disorder (ASD) using structural magnetic resonance imaging

Background

Autism spectrum disorder (ASD) is a group of developmental disorders of the nervous system. Since the core cause of many of the symptoms of autism spectrum disorder is due to changes in the structure of the brain, the importance of examining the structural abnormalities of the brain in these disorder becomes apparent. The aim of this study is evaluation of brain structure abnormalities in children with autism spectrum disorder (ASD) using structural magnetic resonance imaging (sMRI). sMRI images of 26 autistic and 26 Healthy control subjects in the range of 5–10 years are selected from the ABIDE database. For a better assessment of structural abnormalities, the surface and volume features are extracted together from this images. Then, the extracted features from both groups were compared with the sample t test and the features with significant differences between the two groups were identified.

Results

The results of volume-based features indicate an increase in total brain volume and white matter and a change in white and gray matter volume in brain regions of Hammers atlas in the autism group. In addition, the results of surface-based features indicate an increase in mean and standard deviation of cerebral cortex thickness and changes in cerebral cortex thickness, sulcus depth, surface complexity and gyrification index in the brain regions of the Desikan–Killany cortical atlas.

Conclusions

Identifying structurally abnormal areas of the brain and examining their relationship to the clinical features of Autism Spectrum Disorder can pave the way for the correct and early detection of this disorder using structural magnetic resonance imaging. It is also possible to design treatment for autistic people based on the abnormal areas of the brain, and to see the effectiveness of the treatment using imaging.

Brain Structural Covariance Network in Asperger Syndrome Differs From Those in Autism Spectrum Disorder and Healthy Controls

Introduction

Autism is a heterogeneous neurodevelopmental disorder associated with social, cognitive and behavioral impairments. These impairments are often reported along with alteration of the brain structure such as abnormal changes in the grey matter (GM) density. However, it is not yet clear whether these changes could be used to differentiate various subtypes of autism spectrum disorder (ASD).

Method

We compared the regional changes of GM density in ASD, Asperger's Syndrome (AS) individuals and a group of healthy controls (HC). In addition to regional changes itself, the amount of GM density changes in one region as compared to other brain regions was also calculated. We hypothesized that this structural covariance network could differentiate the AS individuals from the ASD and HC groups. Therefore, statistical analysis was performed on the MRI data of 70 male subjects including 26 ASD (age=14-50, IQ=92-132), 16 AS (age=7-58, IQ=93-133) and 28 HC (age=9-39, IQ=95-144).

Result

The one-way ANOVA on the GM density of 116 anatomically separated regions showed significant differences among the groups. The pattern of structural covariance network indicated that covariation of GM density between the brain regions is altered in ASD.

Conclusion

This changed structural covariance could be considered as a reason for less efficient segregation and integration of information in the brain that could lead to cognitive dysfunctions in autism. We hope these findings could improve our understanding about the pathobiology of autism and may pave the way towards a more effective intervention paradigm.

Brain morphometric abnormalities and their associations with affective symptoms in males with methamphetamine use disorder during abstinence

Background

Methamphetamine (METH) use induces neurotoxic effects in brain structures and affective symptoms that persist during abstinence. However, the brain morphometry of individuals with METH use disorder (MUD) remains unclear, as well as their associations with affective symptoms during abstinence.

Methods

Forty-eight abstinent males with MUD and 66 age-, sex-, and education-matched healthy controls (HCs) underwent high-resolution T1-weighted magnetic resonance imaging. Cortical thickness, surface area, volume, local gyrification index (LGI), and subcortical volume were obtained with FreeSurfer software. Brain morphometry differences between groups and their associations with affective symptoms and drug abuse history within the males with MUD were examined, with intracranial volume, age, and years of education as covariates.

Results

Compared with the HCs, the individuals with MUD showed a significantly higher LGI in the right cuneus gyrus, left lingual gyrus, bilateral supramarginal gyrus, right inferior parietal gyrus (IPG), and right dorsal anterior cingulate cortex (clusterwise p < 0.05, Monte Carlo-corrected), as well as a smaller volume of the left nucleus accumbens (NAcc) (p < 0.05, FDR-corrected). However, there were no significant group differences in cortical thickness, area or volume. In addition, the LGI in the right IPG was positively associatedwith the severity of depression and anxiety symptoms in MUDs (p < 0.05, FDR-corrected).

Conclusion

Brain morphometric abnormalities in abstinent males with MUD were characterized by hypergyrification across multiple mid-posterior brain regions anda smaller volume of the left NAcc.Gyrification of the right IPG may be a potential neural substrate underlying the affective symptoms experienced by MUDs during abstinence.

Prenatal and early-life environmental factors, family demographics and cortical brain anatomy in 5-year-olds: an MRI study from FinnBrain Birth Cohort

The human brain develops dynamically during early childhood, when the child is sensitive to both genetic programming and extrinsic exposures. Recent studies have found links between prenatal and early life environmental factors, family demographics and the cortical brain morphology in newborns measured by surface area, volume and thickness. Here in this magnetic resonance imaging study, we evaluated whether a similar set of variables associates with cortical surface area and volumes measured in a sample of 170 healthy 5-year-olds from the FinnBrain Birth Cohort Study. We found that child sex, maternal pre-pregnancy body mass index, 5 min Apgar score, neonatal intensive care unit admission and maternal smoking during pregnancy associated with surface areas. Furthermore, child sex, maternal age and maternal level of education associated with brain volumes. Expectedly, many variables deemed important for neonatal brain anatomy (such as birth weight and gestational age at birth) in earlier studies did not associate with brain metrics in our study group of 5-year-olds, which implies that their effects on brain anatomy are age-specific. Future research may benefit from including pre- and perinatal covariates in the analyses when such data are available. Finally, we provide evidence for right lateralization for surface area and volumes, except for the temporal lobes which were left lateralized. These subtle differences between hemispheres are variable across individuals and may be interesting brain metrics in future studies.

The longitudinal bidirectional relationship between autistic traits and brain morphology from childhood to adolescence: a population-based cohort study

Objective

Autistic traits are associated with alterations in brain morphology. However, the anatomic location of these differences and their developmental trajectories are unclear. The primary objective of this longitudinal study was to explore the bidirectional relationship between autistic traits and brain morphology from childhood to adolescence.

Method

Participants were drawn from a population-based cohort. Cross-sectional and longitudinal analyses included 1950 (mean age 13.5) and 304 participants (mean ages 6.2 and 13.5), respectively. Autistic traits were measured with the Social Responsiveness Scale. Global brain measures and surface-based measures of gyrification, cortical thickness and surface area were obtained from T₁-weighted MRI scans. Cross-sectional associations were assessed using linear regression analyses. Cross-lagged panel models were used to determine the longitudinal bidirectional relationship between autistic traits and brain morphology.

Results

Cross-sectionally, higher levels of autistic traits in adolescents are associated with lower gyrification in the pars opercularis, insula and superior temporal cortex; smaller surface area in the middle temporal and postcentral cortex; larger cortical thickness in the superior frontal cortex; and smaller cerebellum cortex volume. Longitudinally, both autistic traits and brain measures were quite stable, with neither brain measures predicting changes in autistic traits, nor vice-versa.

Limitations

Autistic traits were assessed at only two time points, and thus we could not distinguish within- versus between-person effects. Furthermore, two different MRI scanners were used between baseline and follow-up for imaging data acquisition.

Conclusions

Our findings point to early changes in brain morphology in children with autistic symptoms that remain quite stable over time. The observed relationship did not change substantially after excluding children with high levels of autistic traits, bolstering the evidence for the extension of the neurobiology of autistic traits to the general population.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13229-022-00504-7.

Feasibility of FreeSurfer Processing for T1-Weighted Brain Images of 5-Year-Olds: Semiautomated Protocol of FinnBrain Neuroimaging Lab

Pediatric neuroimaging is a quickly developing field that still faces important methodological challenges. Pediatric images usually have more motion artifact than adult images. The artifact can cause visible errors in brain segmentation, and one way to address it is to manually edit the segmented images. Variability in editing and quality control protocols may complicate comparisons between studies. In this article, we describe in detail the semiautomated segmentation and quality control protocol of structural brain images that was used in FinnBrain Birth Cohort Study and relies on the well-established FreeSurfer v6.0 and ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) consortium tools. The participants were typically developing 5-year-olds [n = 134, 5.34 (SD 0.06) years, 62 girls]. Following a dichotomous quality rating scale for inclusion and exclusion of images, we explored the quality on a region of interest level to exclude all regions with major segmentation errors. The effects of manual edits on cortical thickness values were relatively minor: less than 2% in all regions. Supplementary Material cover registration and additional edit options in FreeSurfer and comparison to the computational anatomy toolbox (CAT12). Overall, we conclude that despite minor imperfections FreeSurfer can be reliably used to segment cortical metrics from T1-weighted images of 5-year-old children with appropriate quality assessment in place. However, custom templates may be needed to optimize the results for the subcortical areas. Through visual assessment on a level of individual regions of interest, our semiautomated segmentation protocol is hopefully helpful for investigators working with similar data sets, and for ensuring high quality pediatric neuroimaging data.

Neurogenesis of Subventricular Zone Progenitors in the Premature Cortex of Ferrets Facilitated by Neonatal Valproic Acid Exposure

The present study evaluated the neurogenesis of neonatal valproic acid (VPA) exposure on subventricular zone progenitors of the developing cerebral cortex in ferrets. VPA was injected at a dose of 200 µg/g of body weight into ferret infants on postnatal days 6 and 7. Two different thymidine analogues, 5-ethynyl-2′-deoxyuridine (EdU) and 5-bromo-2′-deoxyuridine (BrdU), were injected with a 48 h interval to label proliferating cells before and after VPA exposure. Two hours after BrdU injection, BrdU single- and EdU/BrdU double-labeled cells, but not EdU single-labeled cells, were significantly denser in both the inner and outer subventricular zones of VPA-exposed infants than in control infants. Notably, more than 97% of BrdU single- and EdU/BrdU double-labeled cells were immunopositive for Pax6, a stable marker for basal radial glia (bRG), in both groups. In contrast, the percentage of cells positively immunostained for Cux1, a postmitotic marker for upper-layer cortical neurons, in both EdU single- and BrdU single-labeled cells, was significantly higher in VPA-exposed infants than in control infants. These findings suggest that neonatal VPA exposure facilitates bRG proliferation, including self-renewal, followed by their differentiation into upper layer cortical neurons in the premature cortex of ferrets.

Research-Based Intervention (RBI) for Autism Spectrum Disorder: Looking beyond Traditional Models and Outcome Measures for Clinical Trials

The rising prevalence of Autism Spectrum Disorders (ASD) has led to a quickly increasing need for effective interventions. Several criteria and measures have been developed to critically assess these interventions with particular focus on the evaluation of the efficacy. Given the huge diversity of ASD symptoms and the different levels of severity across individuals, identifying a one size fits all intervention approach is challenging, and the question What works and for whom? Remains still unanswered. Why do we seem to be dragging our feet on this fundamental issue? The main aim of this paper is to answer this question through four non-alternative points. First, there are a scarce number of studies with a solid methodology. Secondly, most trials on intervention efficacy for ASD are designed exclusively in terms of behavioral outcomes. Thirdly, there is a reduced use of biologically oriented outcome measures. Fourthly, in most clinical trials, appropriate practices emerging from research evidence are not systematically applied. A strong effort to improve the methodology of clinical trials is mandatory for the future of autism research. The development of a research-based intervention (RBI) perspective aimed at better integrating: (a) evidence-based approaches; (b) more sensitive behavioral outcome measures; and (c) biomarkers, with the aim of increasing a more detailed clustering of phenotypes, may strongly improve our approach to a precision medicine.

Region-specific associations between gamma-aminobutyric acid A receptor binding and cortical thickness in high-functioning autistic adults

The neurobiology of autism has been shown to involve alterations in cortical morphology and gamma-aminobutyric acid A (GABA_A ) receptor density. We hypothesized that GABA_A receptor binding potential (GABA_A R BP_ND ) would correlate with cortical thickness, but their correlations would differ between autistic adults and typically developing (TD) controls. We studied 50 adults (23 autism, 27 TD, mean age of 27 years) using magnetic resonance imaging to measure cortical thickness, and [¹⁸ F]flumazenil positron emission tomography imaging to measure GABA_A R BP_ND . We determined the correlations between cortical thickness and GABA_A R BP_ND by cortical lobe, region-of-interest, and diagnosis of autism spectrum disorder (ASD). We also explored potential sex differences in the relationship between cortical thickness and autism characteristics, as measured by autism spectrum quotient (AQ) scores. Comparing autism and TD groups, no significant differences were found in cortical thickness or GABA_A R BP_ND . In both autism and TD groups, a negative relationship between cortical thickness and GABA_A R BP_ND was observed in the frontal and occipital cortices, but no relationship was found in the temporal or limbic cortices. A positive correlation was seen in the parietal cortex that was only significant for the autism group. Interestingly, in an exploratory analysis, we found sex differences in the relationships between cortical thickness and GABA_A R BP_ND , and cortical thickness and AQ scores in the left postcentral gyrus. LAY SUMMARY: The thickness of the brain cortex and the density of the receptors associated with inhibitory neurotransmitter GABA have been hypothesized to underlie the neurobiology of autism. In this study, we found that these biomarkers correlate positively in the parietal cortex, but negatively in the frontal and occipital cortical regions of the brain. Furthermore, we collected preliminary evidence that the correlations between cortical thickness and GABA receptor density are sexdependent in a brain region where sensory inputs are registered.

Foreign Language Learning in Older Adults: Anatomical and Cognitive Markers of Vocabulary Learning Success

In recent years, foreign language learning (FLL) has been proposed as a possible cognitive intervention for older adults. However, the brain network and cognitive functions underlying FLL has remained largely unconfirmed in older adults. In particular, older and younger adults have markedly different cognitive profile—while older adults tend to exhibit decline in most cognitive domains, their semantic memory usually remains intact. As such, older adults may engage the semantic functions to a larger extent than the other cognitive functions traditionally considered the most important (e.g., working memory capacity and phonological awareness). Using anatomical measurements and a cognitive test battery, the present study examined this hypothesis in twenty cognitively normal older adults (58–69 years old), who participated in a two-month Italian learning programme. Results showed that the immediate learning success and long-term retention of Italian vocabularies were most consistently predicted by the anatomical measures of the left pars orbitalis and left caudal middle frontal cortex, which are implicated in semantic and episodic memory functions. Convergent evidence was also found based on the pattern of cognitive associations. Our results are consistent with a prominent role of semantic and episodic memory functions in vocabulary learning in older learners.

The Role of Structure MRI in Diagnosing Autism

This study proposes a Computer-Aided Diagnostic (CAD) system to diagnose subjects with autism spectrum disorder (ASD). The CAD system identifies morphological anomalies within the brain regions of ASD subjects. Cortical features are scored according to their contribution in diagnosing a subject to be ASD or typically developed (TD) based on a trained machine-learning (ML) model. This approach opens the hope for developing a new CAD system for early personalized diagnosis of ASD. We propose a framework to extract the cerebral cortex from structural MRI as well as identifying the altered areas in the cerebral cortex. This framework consists of the following five main steps: (i) extraction of cerebral cortex from structural MRI; (ii) cortical parcellation to a standard atlas; (iii) identifying ASD associated cortical markers; (iv) adjusting feature values according to sex and age; (v) building tailored neuro-atlases to identify ASD; and (vi) artificial neural networks (NN) are trained to classify ASD. The system is tested on the Autism Brain Imaging Data Exchange (ABIDE I) sites achieving an average balanced accuracy score of 97±2%. This paper demonstrates the ability to develop an objective CAD system using structure MRI and tailored neuro-atlases describing specific developmental patterns of the brain in autism.

RhoGEF Trio Regulates Radial Migration of Projection Neurons via Its Distinct Domains

The radial migration of cortical pyramidal neurons (PNs) during corticogenesis is necessary for establishing a multilayered cerebral cortex. Neuronal migration defects are considered a critical etiology of neurodevelopmental disorders, including autism spectrum disorders (ASDs), schizophrenia, epilepsy, and intellectual disability (ID). TRIO is a high-risk candidate gene for ASDs and ID. However, its role in embryonic radial migration and the etiology of ASDs and ID are not fully understood. In this study, we found that the in vivo conditional knockout or in utero knockout of Trio in excitatory precursors in the neocortex caused aberrant polarity and halted the migration of late-born PNs. Further investigation of the underlying mechanism revealed that the interaction of the Trio N-terminal SH3 domain with Myosin X mediated the adherence of migrating neurons to radial glial fibers through regulating the membrane location of neuronal cadherin (N-cadherin). Also, independent or synergistic overexpression of RAC1 and RHOA showed different phenotypic recoveries of the abnormal neuronal migration by affecting the morphological transition and/or the glial fiber-dependent locomotion. Taken together, our findings clarify a novel mechanism of Trio in regulating N-cadherin cell surface expression via the interaction of Myosin X with its N-terminal SH3 domain. These results suggest the vital roles of the guanine nucleotide exchange factor 1 (GEF1) and GEF2 domains in regulating radial migration by activating their Rho GTPase effectors in both distinct and cooperative manners, which might be associated with the abnormal phenotypes in neurodevelopmental disorders.

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.

Common and Distinct Disruptions of Cortical Surface Morphology Between Autism Spectrum Disorder Children With and Without SHANK3 Deficiency

SH3 and Multiple Ankyrin Repeat Domains 3 (SHANK3)-caused autism spectrum disorder (ASD) may present a unique opportunity to clarify the heterogeneous neuropathological mechanisms of ASD. However, the specificity and commonality of disrupted large-scale brain organization in SHANK3-deficient children remain largely unknown. The present study combined genetic tests, neurobehavioral evaluations, and magnetic resonance imaging, aiming to explore the disruptions of both local and networked cortical structural organization in ASD children with and without SHANK3 deficiency. Multiple surface morphological parameters such as cortical thickness (CT) and sulcus depth were estimated, and the graph theory was adopted to characterize the topological properties of structural covariance networks (SCNs). Finally, a correlation analysis between the alterations in brain morphological features and the neurobehavioral evaluations was performed. Compared with typically developed children, increased CT and reduced nodal degree were found in both ASD children with and without SHANK3 defects mainly in the lateral temporal cortex, prefrontal cortex (PFC), temporo-parietal junction (TPJ), superior temporal gyrus (STG), and limbic/paralimbic regions. Besides commonality, our findings showed some distinct abnormalities in ASD children with SHANK3 defects compared to those without. Locally, more changes in the STG and orbitofrontal cortex were exhibited in ASD children with SHANK3 defects, while more changes in the TPJ and inferior parietal lobe (IPL) in those without SHANK3 defects were observed. For the SCNs, a trend toward regular network topology was observed in ASD children with SHANK3 defects, but not in those without. In addition, ASD children with SHANK3 defects showed more alterations of nodal degrees in the anterior and posterior cingulate cortices and right insular, while there were more disruptions in the sensorimotor areas and the left insular and dorsomedial PFC in ASD without SHANK3 defects. Our findings indicate dissociable disruptions of local and networked brain morphological features in ASD children with and without SHANK3 deficiency. Moreover, this monogenic study may provide a valuable path for parsing the heterogeneity of brain disturbances in ASD.

A systematic review of brain MRI findings in monogenic disorders strongly associated with autism spectrum disorder

BACKGROUND

Research on monogenic forms of autism spectrum disorder (autism) can inform our understanding of genetic contributions to the autism phenotype; yet, there is much to be learned about the pathways from gene to brain structure to behavior. This systematic review summarizes and evaluates research on brain magnetic resonance imaging (MRI) findings in monogenic conditions that have strong association with autism. This will improve understanding of the impact of genetic variability on brain structure and related behavioral traits in autism.

METHODS

The search strategy for this systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Risk of bias (ROB) assessment was completed on included studies using the Newcastle-Ottawa Scales.

RESULTS

Of 4,287 studies screened, 69 were included pertaining to 13 of the top 20 genes with the strongest association with autism. The greatest number of studies related to individuals with PTEN variants and autism. Brain MRI abnormalities were reported for 12 of the 13 genes studied, and in 51.7% of participants across all 13 genes, including 100% of participants with ARID1B variants. Specific MRI findings were highly variable, with no clear patterns emerging within or between the 13 genes, although white matter abnormalities were the most common. Few studies reported specific details about methods for acquisition and processing of brain MRI, and descriptors for brain abnormalities were variable. ROB assessment indicated high ROB for all studies, largely due to small sample sizes and lack of comparison groups.

CONCLUSIONS

Brain abnormalities are common in this population of individuals, in particular, children; however, a range of different brain abnormalities were reported within and between genes. Directions for future neuroimaging research in monogenic autism are suggested.

Cortical Gyrification Morphology in ASD and ADHD: Implication for Further Similarities or Disorder-Specific Features?

Shared etiological pathways are suggested in ASD and ADHD given high rates of comorbidity, phenotypic overlap and shared genetic susceptibility. Given the peak of cortical gyrification expansion and emergence of ASD and ADHD symptomology in early development, we investigated gyrification morphology in 539 children and adolescents (6–17 years of age) with ASD (n=197) and ADHD (n=96) compared to typically developing controls (n=246) using the local Gyrification Index (lGI) to provide insight into contributing etiopathological factors in these two disorders. We also examined IQ effects and functional implications of gyrification by exploring the relation between lGI and ASD and ADHD symptomatology beyond diagnosis. General Linear Models yielded no group differences in lGI, and across groups, we identified an age-related decrease of lGI and greater lGI in females compared to males. No diagnosis-by-age interactions were found. Accounting for IQ variability in the model (n=484) yielded similar results. No significant associations were found between lGI and social communication deficits, repetitive and restricted behaviours, inattention or adaptive functioning. By examining both disorders and controls using shared methodology, we found no evidence of atypicality in gyrification as measured by the lGI in these conditions.

Autonomic responses to facial expression tasks in children with autism spectrum disorders: Cross-section study

BACKGROUND

The autonomic nervous system has an influence on emotions and behavior modulation, however, the relationship between autonomic modulation impairment and the autism spectrum disorder (ASD) is yet to be fully described.

AIMS

To evaluate the autonomic responses of children with and without ASD through the non-linear, and linear heart rate variability (HRV) measures, and assess the correlation between these responses, the severity and behavioral symptoms of autism.

METHODS AND PROCEDURES

27 children diagnosed with ASD (EG = experimental group) and 28 matching controls (CG = control group) were evaluated. The HRV was evaluated in 15 min sections at the following moments: I) Resting condition; II) During facial expression tasks; and III) Recovery. The severity and behavioral symptoms of autism were evaluated by the Childhood Autism Rating Scale (CARS) and Autistic Behaviors Checklist (ABC) scales.

OUTCOMES AND RESULTS

The facial expression tasks influenced the activity of the autonomic nervous system in both groups, however the EG experienced more autonomic changes. These changes were mostly evidenced by the non-linear indices. Also, the CARS and ABC scales showed significant correlations with HRV indices.

CONCLUSIONS AND IMPLICATIONS

Children with ASD presented an autonomic modulation impairment, mostly identified by the non-linear indices of HRV. Also, this autonomic impairment is associated with the severity and behavioral symptoms of autism.

Relationship between local gyrification index and age, intelligence quotient, symptom severity with Autism Spectrum Disorder: A large-scale MRI study

Gyrification is one of the most important characteristics in the cerebral cortex and the local gyrification index (LGI) was used to quantify the regional changes in gyrification. The aim of this study was to evaluate LGI alterations in autism spectrum disorder (ASD) individuals in comparison with typically developing (TD) controls and the association of the LGI with age, intelligence quotient (IQ), and symptom severity in a large multicenter dataset. Structural MRI datasets selected from Autism Brain Imaging Data Exchange I and II (ABIDE I and ABIDE II) repository (606 ASD individuals and 765 age-matched TD controls) were used to calculate LGI values. The correlation between the LGI and age, IQ, and other clinical measurements were assessed. No differences in LGI were found between ASD individuals and TD controls after FDR multiple comparison correction, however, LGI decreased with age in both ASD and TD groups. In the TD group, a significant positive correlation was found between the LGI and full IQ (FIQ) in the parahippocampal gyrus, parsopercularis of left hemisphere and entorhinal cortex, parahippocampal, superior temporal gyrus of right hemisphere, but was not observed in the ASD group. Furthermore, a positive correlation between the LGI and Autism Diagnostic Interview-Revised (ADI-R) Repetitive and Restrictive Behaviors (RRB) score was found in the left inferior parietal lobule, lateral occipital cortex, superior frontal gyrus and right superior frontal gyrus, inferior temporal gyrus. In summary, these results demonstrate that the ASD is a truly heterogeneous neurodevelopmental disorder. Future investigations are required that group ASD patients into more homogeneous subtypes.

Neonatal valproic acid exposure produces altered gyrification related to increased parvalbumin-immunopositive neuron density with thickened sulcal floors

Valproic acid (VPA) treatment is associated with autism spectrum disorder in humans, and ferrets can be used as a model to test this; so far, it is not known whether ferrets react to developmental VPA exposure with gyrencephalic abnormalities. The current study characterized gyrification abnormalities in ferrets following VPA exposure during neonatal periods, corresponding to the late stage of cortical neurogenesis as well as the early stage of sulcogyrogenesis. Ferret pups received intraperitoneal VPA injections (200 μg/g of body weight) on postnatal days (PD) 6 and 7. BrdU was administered simultaneously at the last VPA injection. Ex vivo MRI-based morphometry demonstrated significantly lower gyrification index (GI) throughout the cortex in VPA-treated ferrets (1.265 ± 0.027) than in control ferrets (1.327 ± 0.018) on PD 20, when primary sulcogyrogenesis is complete. VPA-treated ferrets showed significantly smaller sulcal-GIs in the rostral suprasylvian sulcus and splenial sulcus but a larger lateral sulcus surface area than control ferrets. The floor cortex of the inner stratum of both the rostral suprasylvian and splenial sulci and the outer stratum of the lateral sulcus showed a relatively prominent expansion. Parvalbumin-positive neuron density was significantly greater in the expanded cortical strata of sulcal floors in VPA-treated ferrets, regardless of the BrdU-labeled status. Thus, VPA exposure during the late stage of cortical neurogenesis may alter gyrification, primarily in the frontal and parietotemporal cortical divisions. Altered gyrification may thicken the outer or inner stratum of the cerebral cortex by increasing parvalbumin-positive neuron density.

Heschl's Gyrus Duplication Pattern in Individuals at Risk of Developing Psychosis and Patients With Schizophrenia

An increased prevalence of duplicated Heschl’s gyrus (HG), which may reflect an early neurodevelopmental pathology, has been reported in schizophrenia (Sz). However, it currently remains unclear whether individuals at risk of psychosis exhibit similar brain morphological characteristics. This magnetic resonance imaging study investigated the distribution of HG gyrification patterns [i.e., single HG, common stem duplication (CSD), and complete posterior duplication (CPD)] and their relationship with clinical characteristics in 57 individuals with an at-risk mental state (ARMS) [of whom 5 (8.8%) later developed Sz], 63 patients with Sz, and 61 healthy comparisons. The prevalence of duplicated HG patterns (i.e., CSD or CPD) bilaterally was significantly higher in the ARMS and Sz groups than in the controls, whereas no significant differences were observed in HG patterns between these groups. The left CSD pattern, particularly in the Sz group, was associated with a verbal fluency deficit. In the ARMS group, left CSD pattern was related to a more severe general psychopathology. The present results suggest that an altered gyrification pattern on the superior temporal plane reflects vulnerability factors associated with Sz, which may also contribute to the clinical features of high-risk individuals, even without the onset of psychosis.

Differences in subcortico-cortical interactions identified from connectome and microcircuit models in autism

The pathophysiology of autism has been suggested to involve a combination of both macroscale connectome miswiring and microcircuit anomalies. Here, we combine connectome-wide manifold learning with biophysical simulation models to understand associations between global network perturbations and microcircuit dysfunctions in autism. We studied neuroimaging and phenotypic data in 47 individuals with autism and 37 typically developing controls obtained from the Autism Brain Imaging Data Exchange initiative. Our analysis establishes significant differences in structural connectome organization in individuals with autism relative to controls, with strong between-group effects in low-level somatosensory regions and moderate effects in high-level association cortices. Computational models reveal that the degree of macroscale anomalies is related to atypical increases of recurrent excitation/inhibition, as well as subcortical inputs into cortical microcircuits, especially in sensory and motor areas. Transcriptomic association analysis based on postmortem datasets identifies genes expressed in cortical and thalamic areas from childhood to young adulthood. Finally, supervised machine learning finds that the macroscale perturbations are associated with symptom severity scores on the Autism Diagnostic Observation Schedule. Together, our analyses suggest that atypical subcortico-cortical interactions are associated with both microcircuit and macroscale connectome differences in autism.

Cortical Gyrification Morphology in Individuals with ASD and ADHD across the Lifespan: A Systematic Review and Meta-Analysis

Autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD) are common neurodevelopmental disorders (NDDs) that may impact brain maturation. A number of studies have examined cortical gyrification morphology in both NDDs. Here we review and when possible pool their results to better understand the shared and potentially disorder-specific gyrification features. We searched MEDLINE, PsycINFO, and EMBASE databases, and 24 and 10 studies met the criteria to be included in the systematic review and meta-analysis portions, respectively. Meta-analysis of local Gyrification Index (lGI) findings across ASD studies was conducted with SDM software adapted for surface-based morphometry studies. Meta-regressions were used to explore effects of age, sex, and sample size on gyrification differences. There were no significant differences in gyrification across groups. Qualitative synthesis of remaining ASD studies highlighted heterogeneity in findings. Large-scale ADHD studies reported no differences in gyrification between cases and controls suggesting that, similar to ASD, there is currently no evidence of differences in gyrification morphology compared with controls. Larger, longitudinal studies are needed to further clarify the effects of age, sex, and IQ on cortical gyrification in these NDDs.

Boys with autism spectrum disorder have distinct cortical folding patterns underpinning impaired self-regulation: a surface-based morphometry study

Although impaired self-regulation (dysregulation) in autism spectrum disorder (ASD) garnered increasing awareness, the neural mechanism of dysregulation in ASD are far from conclusive. To complement our previous voxel-based morphometry findings, we estimated the cortical thickness, surface area, and local gyrification index based on the surface-based morphometry from structural MRI images in 85 ASD and 65 typically developing control (TDC) boys, aged 7-17 years. Levels of dysregulation were measured by the sum of T-scores of Attention, Aggression, and Anxiety/Depression subscales on the Child Behavior Checklist. We found both ASD and TDC shared similar relationships between dysregulation and cortical folding patterns in the left superior and inferior temporal gyri and the left premotor cortex. Significant diagnosis by dysregulation interactions in cortical folding patterns were identified over the right middle frontal and right lateral orbitofrontal regions. The statistical significance of greater local gyrification index in ASD than TDC in several brain regions disappeared when the level of dysregulation was considered. The findings of shared and distinct neural correlates underpinning dysregulation between ASD and TDC may facilitate the development of targeted interventions in the future. The present work also demonstrates that inter-subject variations in self-regulation may explain some extents of ASD-associated brain morphometric differences, likely suggesting that dysregulation is one of the yardsticks for dissecting the heterogeneity of ASD.

Anomalous brain gyrification patterns in major psychiatric disorders: a systematic review and transdiagnostic integration

Anomalous patterns of brain gyrification have been reported in major psychiatric disorders, presumably reflecting their neurodevelopmental pathology. However, previous reports presented conflicting results of patients having hyper-, hypo-, or normal gyrification patterns and lacking in transdiagnostic consideration. In this article, we systematically review previous magnetic resonance imaging studies of brain gyrification in schizophrenia, bipolar disorder, major depressive disorder, and autism spectrum disorder at varying illness stages, highlighting the gyral pattern trajectory for each disorder. Patients with each psychiatric disorder may exhibit deviated primary gyri formation under neurodevelopmental genetic control in their fetal life and infancy, and then exhibit higher-order gyral changes due to mechanical stress from active brain changes (e.g., progressive reduction of gray matter volume and white matter integrity) thereafter, representing diversely altered pattern trajectories from those of healthy controls. Based on the patterns of local connectivity and changes in neurodevelopmental gene expression in major psychiatric disorders, we propose an overarching model that spans the diagnoses to explain how deviated gyral pattern trajectories map onto clinical manifestations (e.g., psychosis, mood dysregulation, and cognitive impairments), focusing on the common and distinct gyral pattern changes across the disorders in addition to their correlations with specific clinical features. This comprehensive understanding of the role of brain gyrification pattern on the pathophysiology may help to optimize the prediction and diagnosis of psychiatric disorders using objective biomarkers, as well as provide a novel nosology informed by neural circuits beyond the current descriptive diagnostics.

Cortical gyrification morphology in PTSD: A neurobiological risk factor for severity?

Post-traumatic stress disorder (PTSD) is a prevalent psychiatric disorder, particularly among military personnel and veterans. Cortical gyrification, as a specific metric derived from structural MRI, is an index of the convoluted folding and patterning of the gyri and sulci, and is thought to facilitate the efficiency of local neuronal wiring. It has the potential to act as a neurobiological risk factor for emergent psychiatric disorders – to date, it has been understudied in PTSD. Here, using a local measure of the degree of gyrification (local Gyrification Index, lGI) we investigate cortical gyrification morphology in 48 adult male soldiers with (n = 23) and without (n = 25) a PTSD diagnosis. We also examine the relation between lGI and PTSD severity within the PTSD group. General linear models yielded significant between-group differences with greater lGI found in PTSD in a cluster located in the medial occipito-parietal lobe on the left hemisphere and reduced lGI in a cluster located on the lateral surface of the parietal lobe on the right hemisphere. Brain-behaviour analyses within the PTSD group yielded significant positive associations between lGI and PTSD severity in a cluster located in the frontal cortex of the left hemisphere and scattered clusters located within all lobes of the right hemisphere. After accounting for the effects of comorbid psychiatric symptoms common in PTSD, the associations in the right hemisphere reduced to clusters only located in the frontal lobe, while the cluster in the left hemisphere remained significant. Our results suggest that atypical cortical gyrification in parietal and occipital regions may be implicated in the psychopathology of PTSD diagnosis, and properties of prefrontal gyrification associated with the emergent severity of PTSD after trauma. The importance of these regions in PTSD may be attributed to a pre-existing neurobiological risk factor, or neuromorphological changes after trauma precipitating emergent psychiatric illness. Our brain-behaviour relations provide support for the existing literature by highlighting the importance of the frontal lobe in the pathogenesis of PTSD. Future large-scale longitudinal studies including female participants may infer causal implications of atypical gyrification in PTSD and shed light on the potential effect of sex on this brain metric.

Core-Symptom-Defined Cortical Gyrification Differences in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a heterogeneous disease that is characterized by abnormalities in social communication and interaction as well as repetitive behaviors and restricted interests. Structural brain imaging has identified significant cortical folding alterations in ASD; however, relatively less known is whether the core symptoms are related to neuroanatomical differences. In this study, we aimed to explore core-symptom-anchored gyrification alterations and their developmental trajectories in ASD. We measured the cortical vertex-wise gyrification index (GI) in 321 patients with ASD (aged 7-39 years) and 350 typically developing (TD) subjects (aged 6-33 years) across 8 sites from the Autism Brain Imaging Data Exchange I (ABIDE I) repository and a longitudinal sample (14 ASD and 7 TD, aged 9-14 years in baseline and 12-18 years in follow-up) from ABIDE II. Compared with TD, the general ASD patients exhibited a mixed pattern of both hypo- and hyper- and different developmental trajectories of gyrification. By parsing the ASD patients into three subgroups based on the subscores of the Autism Diagnostic Interview-Revised (ADI-R) scale, we identified core-symptom-specific alterations in the reciprocal social interaction (RSI), communication abnormalities (CA), and restricted, repetitive, and stereotyped patterns of behavior (RRSB) subgroups. We also showed atypical gyrification patterns and developmental trajectories in the subgroups. Furthermore, we conducted a meta-analysis to locate the core-symptom-anchored brain regions (circuits). In summary, the current study shows that ASD is associated with abnormal cortical folding patterns. Core-symptom-based classification can find more subtle changes in gyrification. These results suggest that cortical folding pattern encodes changes in symptom dimensions, which promotes the understanding of neuroanatomical basis, and clinical utility in ASD.

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

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

Cortical gyrification and its relationships with molecular measures and cognition in children with the FMR1 premutation

Neurobiological basis for cognitive development and psychiatric conditions remains unexplored in children with the FMR1 premutation (PM). Knock-in mouse models of PM revealed defects in embryonic cortical development that may affect cortical folding. Cortical-folding complexity quantified using local gyrification index (LGI) was examined in 61 children (age 8–12 years, 19/14 male/female PM carriers, 15/13 male/female controls). Whole-brain vertex-wise analysis of LGI was performed for group comparisons and correlations with IQ. Individuals with aberrant gyrification in 68 cortical areas were identified using Z-scores of LGI (hyper: Z ≥ 2.58, hypo: Z ≤ − 2.58). Significant group-by-sex-by-age interaction in LGI was detected in right inferior temporal and fusiform cortices, which correlated negatively with CGG repeat length in the PM carriers. Sixteen PM boys (hyper/hypo: 7/9) and 10 PM girls (hyper/hypo: 2/5, 3 both) displayed aberrant LGI in 1–17 regions/person while 2 control boys (hyper/hypo: 0/2) and 2 control girls (hyper/hypo: 1/1) met the same criteria in only 1 region/person. LGI in the precuneus and cingulate cortices correlated positively with IQ scores in PM and control boys while negatively in PM girls and no significant correlation in control girls. These findings reveal aberrant gyrification, which may underlie cognitive performance in children with the PM.