Changes in the sulcal size associated with autism spectrum disorder revealed by sulcal morphometry

Cortical Sulcal Abnormalities Revealed by Sulcal Morphometry in Patients with Chronic and Episodic Migraine

Purpose

Previous studies have reported mixed results regarding the importance of cortical abnormalities in patients with migraines. However, cortical sulci, as a component of the cerebral cortex, have not been specifically investigated in migraine patients. Therefore, we aim to evaluate alterations in cortical sulcal morphology among patients with chronic migraine (CM), episodic migraine (EM), and healthy controls (HCs).

Patients and Methods

In this cross-sectional study, structural magnetic resonance images were acquired from 35 patients with CM, 35 with EM, and 35 HCs. Cortical sulci were identified and reconstructed using the BrainVisa 5.0.4 software. We focused on regions involved in pain processing in which abnormal cortical structure were identified in previous neuroimaging studies. Morphometric analysis was performed to calculate sulcal parameters including mean depth, cortical thickness, and opening width. Partial correlation analyses of clinical characteristics and sulcal parameters were performed for CM, EM and the combined migraine (CM + EM) groups.

Results

In comparison with HCs, both CM and EM groups showed increased opening width in bilateral insula. In comparison with HC and EM groups, CM patients showed increased cortical thickness in bilateral superior postcentral sulcus, bilateral median frontal sulcus and left superior parietal sulcus, as well as increased mean depth in the left anterior callosomarginal fissure and decreased mean depth in bilateral superior frontal sulcus and left median frontal sulcus. Migraine frequency and disease duration were both correlated with cortical thickness in bilateral superior postcentral sulcus.

Conclusion

Abnormal sulcal morphometry primarily affected areas associated with pain processing in patients with migraine, with CM exhibiting more extensive abnormalities in areas related to sensory and affective processing. These changes may contribute to understanding the pathology of EM and CM.

ABLE: Automated Brain Lines Extraction Based on Laplacian Surface Collapse

The archetypical folded shape of the human cortex has been a long-standing topic for neuroscientific research. Nevertheless, the accurate neuroanatomical segmentation of sulci remains a challenge. Part of the problem is the uncertainty of where a sulcus transitions into a gyrus and vice versa. This problem can be avoided by focusing on sulcal fundi and gyral crowns, which represent the topological opposites of cortical folding. We present Automated Brain Lines Extraction (ABLE), a method based on Laplacian surface collapse to reliably segment sulcal fundi and gyral crown lines. ABLE is built to work on standard FreeSurfer outputs and eludes the delineation of anastomotic sulci while maintaining sulcal fundi lines that traverse the regions with the highest depth and curvature. First, it segments the cortex into gyral and sulcal surfaces; then, each surface is spatially filtered. A Laplacian-collapse-based algorithm is applied to obtain a thinned representation of the surfaces. This surface is then used for careful detection of the endpoints of the lines. Finally, sulcal fundi and gyral crown lines are obtained by eroding the surfaces while preserving the connectivity between the endpoints. The method is validated by comparing ABLE with three other sulcal extraction methods using the Human Connectome Project (HCP) test-retest database to assess the reproducibility of the different tools. The results confirm ABLE as a reliable method for obtaining sulcal lines with an accurate representation of the sulcal topology while ignoring anastomotic branches and the overestimation of the sulcal fundi lines. ABLE is publicly available via https://github.com/HGGM-LIM/ABLE .

Identifying neuroanatomical and behavioral features for autism spectrum disorder diagnosis in children using machine learning

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that can cause significant social, communication, and behavioral challenges. Diagnosis of ASD is complicated and there is an urgent need to identify ASD-associated biomarkers and features to help automate diagnostics and develop predictive ASD models. The present study adopts a novel evolutionary algorithm, the conjunctive clause evolutionary algorithm (CCEA), to select features most significant for distinguishing individuals with and without ASD, and is able to accommodate datasets having a small number of samples with a large number of feature measurements. The dataset is unique and comprises both behavioral and neuroimaging measurements from a total of 28 children from 7 to 14 years old. Potential biomarker candidates identified include brain volume, area, cortical thickness, and mean curvature in specific regions around the cingulate cortex, frontal cortex, and temporal-parietal junction, as well as behavioral features associated with theory of mind. A separate machine learning classifier (i.e., k-nearest neighbors algorithm) was used to validate the CCEA feature selection and for ASD prediction. Study findings demonstrate how machine learning tools might help move the needle on improving diagnostic and predictive models of ASD.

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.

A Longitudinal Study of Local Gyrification Index in Young Boys With Autism Spectrum Disorder

Local gyrification index (LGI), a metric quantifying cortical folding, was evaluated in 105 boys with autism spectrum disorder (ASD) and 49 typically developing (TD) boys at 3 and 5 years-of-age. At 3 years-of-age, boys with ASD had reduced gyrification in the fusiform gyrus compared with TD boys. A longitudinal evaluation from 3 to 5 years revealed that while TD boys had stable/decreasing LGI, boys with ASD had increasing LGI in right inferior temporal gyrus, right inferior frontal gyrus, right inferior parietal lobule, and stable LGI in left lingual gyrus. LGI was also examined in a previously defined neurophenotype of boys with ASD and disproportionate megalencephaly. At 3 years-of-age, this subgroup exhibited increased LGI in right dorsomedial prefrontal cortex, cingulate cortex, and paracentral cortex, and left cingulate cortex and superior frontal gyrus relative to TD boys and increased LGI in right paracentral lobule and parahippocampal gyrus, and left precentral gyrus compared with boys with ASD and normal brain size. In summary, this study identified alterations in the pattern and development of LGI during early childhood in ASD. Distinct patterns of alterations in subgroups of boys with ASD suggests that multiple neurophenotypes exist and boys with ASD and disproportionate megalencephaly should be evaluated separately.

The Neurodevelopment of Autism from Infancy Through Toddlerhood

Autism spectrum disorder (ASD) emerges during early childhood and is marked by a relatively narrow window in which infants transition from exhibiting normative behavioral profiles to displaying the defining features of the ASD phenotype in toddlerhood. Prospective brain imaging studies in infants at high familial risk for autism have revealed important insights into the neurobiology and developmental unfolding of ASD. In this article, we review neuroimaging studies of brain development in ASD from birth through toddlerhood, relate these findings to candidate neurobiological mechanisms, and discuss implications for future research and translation to clinical practice.

Local Cortical Gyrification is Increased in Children With Autism Spectrum Disorders, but Decreases Rapidly in Adolescents

Extensive MRI evidence indicates early brain overgrowth in autism spectrum disorders (ASDs). Local gyrification may reflect the distribution and timing of aberrant cortical expansion in ASDs. We examined MRI data from (Study 1) 64 individuals with ASD and 64 typically developing (TD) controls (7-19 years), and from (Study 2) an independent sample from the Autism Brain Imaging Data Exchange (n = 31/group). Local Gyrification Index (lGI), cortical thickness (CT), and surface area (SA) were measured. In Study 1, differences in lGI (ASD > TD) were found in left parietal and temporal and right frontal and temporal regions. lGI decreased bilaterally with age, but more steeply in ASD in left precentral, right lateral occipital, and middle frontal clusters. CT differed between groups in right perisylvian cortex (TD > ASD), but no differences were found for SA. Partial correlations between lGI and CT were generally negative, but associations were weaker in ASD in several clusters. Study 2 results were consistent, though less extensive. Altered gyrification may reflect unique information about the trajectory of cortical development in ASDs. While early overgrowth tends to be undetectable in later childhood in ASDs, findings may indicate that a trace of this developmental abnormality could remain in a disorder-specific pattern of gyrification.

Subtyping cognitive profiles in Autism Spectrum Disorder using a Functional Random Forest algorithm

DSM-5 Autism Spectrum Disorder (ASD) comprises a set of neurodevelopmental disorders characterized by deficits in social communication and interaction and repetitive behaviors or restricted interests, and may both affect and be affected by multiple cognitive mechanisms. This study attempts to identify and characterize cognitive subtypes within the ASD population using our Functional Random Forest (FRF) machine learning classification model. This model trained a traditional random forest model on measures from seven tasks that reflect multiple levels of information processing. 47 ASD diagnosed and 58 typically developing (TD) children between the ages of 9 and 13 participated in this study. Our RF model was 72.7% accurate, with 80.7% specificity and 63.1% sensitivity. Using the random forest model, the FRF then measures the proximity of each subject to every other subject, generating a distance matrix between participants. This matrix is then used in a community detection algorithm to identify subgroups within the ASD and TD groups, and revealed 3 ASD and 4 TD putative subgroups with unique behavioral profiles. We then examined differences in functional brain systems between diagnostic groups and putative subgroups using resting-state functional connectivity magnetic resonance imaging (rsfcMRI). Chi-square tests revealed a significantly greater number of between group differences (p < .05) within the cingulo-opercular, visual, and default systems as well as differences in inter-system connections in the somato-motor, dorsal attention, and subcortical systems. Many of these differences were primarily driven by specific subgroups suggesting that our method could potentially parse the variation in brain mechanisms affected by ASD.

Extraction of sulcal medial surface and classification of Alzheimer's disease using sulcal features

BACKGROUND

Recent advancements in medical imaging have resulted in a significant growth in diagnostic possibilities of neurodegenerative disorders. Neuroanatomical abnormalities of the cerebral cortex in Alzheimer's disease (AD), the most frequent type of dementia in the elderly, can be observed in morphology analysis of cortical sulci, and used to distinguish between cognitively normal (CN) subjects and subjects with AD.

OBJECTIVE

The purpose of this paper was to extract sulcal features by means of computing a sulcal medial surface for AD/CN classification.

METHODS

24 distinct sulci per subject were extracted from 210 subjects from the ADNI database by the BrainVISA sulcal identification pipeline. Sulcal medial surface features (depth, length, mean and Gaussian curvature, surface area) were computed for AD/CN classification with a support vector machine (SVM).

RESULTS

The obtained 10-fold cross-validated classification accuracy was 87.9%, sensitivity 90.0%, and specificity 86.7%, based on ten features. The area under the receiver operating characteristic curve (AUC) was 0.89.

CONCLUSIONS

The sulcal medial surface features can be used as biomarkers for cortical neuroanatomical abnormalities in AD. All the features were located in the left hemisphere, which had previously been reported to be more severely affected in AD and to lose grey matter faster than the right hemisphere.

Interacting with the National Database for Autism Research (NDAR) via the LONI Pipeline workflow environment

Under the umbrella of the National Database for Clinical Trials (NDCT) related to mental illnesses, the National Database for Autism Research (NDAR) seeks to gather, curate, and make openly available neuroimaging data from NIH-funded studies of autism spectrum disorder (ASD). NDAR has recently made its database accessible through the LONI Pipeline workflow design and execution environment to enable large-scale analyses of cortical architecture and function via local, cluster, or "cloud"-based computing resources. This presents a unique opportunity to overcome many of the customary limitations to fostering biomedical neuroimaging as a science of discovery. Providing open access to primary neuroimaging data, workflow methods, and high-performance computing will increase uniformity in data collection protocols, encourage greater reliability of published data, results replication, and broaden the range of researchers now able to perform larger studies than ever before. To illustrate the use of NDAR and LONI Pipeline for performing several commonly performed neuroimaging processing steps and analyses, this paper presents example workflows useful for ASD neuroimaging researchers seeking to begin using this valuable combination of online data and computational resources. We discuss the utility of such database and workflow processing interactivity as a motivation for the sharing of additional primary data in ASD research and elsewhere.

Abnormalities of cortical structures in adolescent-onset conduct disorder

BACKGROUND

Converging evidence has revealed both functional and structural abnormalities in adolescents with early-onset conduct disorder (EO-CD). The neurological abnormalities underlying EO-CD may be different from that of adolescent-onset conduct disorder (AO-CD) patients. However, the cortical structure in AO-CD patients remains largely unknown. The aim of the present study was to investigate the cortical alterations in AO-CD patients.

METHOD

We investigated T1-weighted brain images from AO-CD patients and age-, gender- and intelligence quotient-matched controls. Cortical structures including thickness, folding and surface area were measured using the surface-based morphometric method. Furthermore, we assessed impulsivity and antisocial symptoms using the Barratt Impulsiveness Scale (BIS) and the Antisocial Process Screening Device (APSD).

RESULTS

Compared with the controls, we found significant cortical thinning in the paralimbic system in AO-CD patients. For the first time, we observed cortical thinning in the precuneus/posterior cingulate cortex (PCC) in AO-CD patients which has not been reported in EO-CD patients. Prominent folding abnormalities were found in the paralimbic structures and frontal cortex while diminished surface areas were shown in the precentral and inferior temporal cortex. Furthermore, cortical thickness of the paralimbic structures was found to be negatively correlated with impulsivity and antisocial behaviors measured by the BIS and APSD, respectively.

CONCLUSIONS

The present study indicates that AO-CD is characterized by cortical structural abnormalities in the paralimbic system, and, in particular, we highlight the potential role of deficient structures including the precuneus and PCC in the etiology of AO-CD.

The Roots of Autism and ADHD Twin Study in Sweden (RATSS)

Neurodevelopmental disorders affect a substantial minority of the general population. Their origins are still largely unknown, but a complex interplay of genetic and environmental factors causing disturbances of the central nervous system's maturation and a variety of higher cognitive skills is presumed. Only limited research of rather small sample size and narrow scope has been conducted in neurodevelopmental disorders using a twin-differences design. The Roots of Autism and ADHD Twin Study in Sweden (RATSS) is an ongoing project targeting monozygotic twins discordant for categorical or dimensional autistic and inattentive/hyperactive-impulsive phenotypes as well as other neurodevelopmental disorders, and typically developing twin controls. Included pairs are 9 years of age or older, and comprehensively assessed for psychopathology, medical history, neuropsychology, and dysmorphology, as well as structural, functional, and molecular brain imaging. Specimens are collected for induced pluripotent (iPS) and neuroepithelial stem cells, genetic, gut bacteria, protein-/monoamine, and electron microscopy analyses. RATSS's objective is to generate a launch pad for novel surveys to understand the complexity of genotype-environment-phenotype interactions in autism spectrum disorder and attention-deficit hyperactivity disorder (ADHD). By October 2013, RATSS had collected data from 55 twin pairs, among them 10 monozygotic pairs discordant for autism spectrum disorder, seven for ADHD, and four for other neurodevelopmental disorders. This article describes the design, recruitment, data collection, measures, collected pairs' characteristics, as well as ongoing and planned analyses in RATSS. Potential gains of the study comprise the identification of environmentally mediated biomarkers, the emergence of candidates for drug development, translational modeling, and new leads for prevention of incapacitating outcomes.

Atypical sulcal anatomy in young children with autism spectrum disorder

Autism spectrum disorder is associated with an altered early brain development. However, the specific cortical structure abnormalities underlying this disorder remain largely unknown. Nonetheless, atypical cortical folding provides lingering evidence of early disruptions in neurodevelopmental processes and identifying changes in the geometry of cortical sulci is of primary interest for characterizing these structural abnormalities in autism and their evolution over the first stages of brain development. Here, we applied state-of-the-art sulcus-based morphometry methods to a large highly-selective cohort of 73 young male children of age spanning from 18 to 108 months. Moreover, such large cohort was selected through extensive behavioral assessments and stringent inclusion criteria for the group of 59 children with autism. After manual labeling of 59 different sulci in each hemisphere, we computed multiple shape descriptors for each single sulcus element, hereby separating the folding measurement into distinct factors such as the length and depth of the sulcus. We demonstrated that the central, intraparietal and frontal medial sulci showed a significant and consistent pattern of abnormalities across our different geometrical indices. We also found that autistic and control children exhibited strikingly different relationships between age and structural changes in brain morphology. Lastly, the different measures of sulcus shapes were correlated with the CARS and ADOS scores that are specific to the autistic pathology and indices of symptom severity. Inherently, these structural abnormalities are confined to regions that are functionally relevant with respect to cognitive disorders in ASD. In contrast to those previously reported in adults, it is very unlikely that these abnormalities originate from general compensatory mechanisms unrelated to the primary pathology. Rather, they most probably reflect an early disruption on developmental trajectory that could be part of the primary pathology.

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A new single-site cohort of 73 young children (1.5–11 years) with autism and controls

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State-of-the-art methodology used to compare geometrical attributes of sulci

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Combination of automatic extraction of descriptors with manual identification of sulci

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Clearly evidence localized sulcal shape abnormalities in the autism group

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Different relationships between age and structural changes in brain morphology

Decreased frontal gyrification correlates with altered connectivity in children with autism

The structural correlates of functional dysconnectivity in autism spectrum disorders (ASD) have been seldom explored, despite the fact that altered functional connectivity is one of the most frequent neuropathological observations in the disorder. We analyzed cerebral morphometry and structural connectivity using multi-modal imaging for 11 children/adolescents with ASD and 11 matched controls. We estimated regional cortical and white matter volumes, as well as vertex-wise measures of cortical thickness and local Gyrification Index (lGI). Diffusion Tensor Images (DTI) were used to measure Fractional Anisotropy (FA) and tractography estimates of short- and long-range connectivity. We observed four clusters of lGI reduction in patients with ASD, three were located in the right inferior frontal region extending to the inferior parietal lobe, and one was in the right medial parieto-occipital region. Reduced volume was found in the anterior corpus callosum, along with fewer inter-hemispheric frontal streamlines. Despite the spatial correspondence of decreased gyrification and reduced long connectivity, we did not observe any significant relationship between the two. However, a positive correlation between lGI and local connectivity was present in all four clusters in patients with ASD. Reduced gyrification in the inferior fronto-parietal and posterior medial cortical regions lends support for early-disrupted cortical growth in both the mirror neuron system and midline structures responsible for social cognition. Early impaired neurodevelopment in these regions may represent an initial substrate for altered maturation in the cerebral networks that support complex social skills. We also demonstrate that gyrification changes are related to connectivity. This supports the idea that an imbalance between short- and long-range white matter tracts not only impairs the integration of information from multiple neural systems, but also alters the shape of the brain early on in autism.

Analysis of cortical shape in children with simplex autism

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

Revisiting the relationship between autism and schizophrenia: toward an integrated neurobiology

Schizophrenia and autism have been linked since their earliest descriptions. Both are disorders of cerebral specialization originating in the embryonic period. Genetic, molecular, and cytologic research highlights a variety of shared contributory mechanisms that may lead to patterns of abnormal connectivity arising from altered development and topology. Overt behavioral pathology likely emerges during or after neurosensitive periods in which resource demands overwhelm system resources and the individual's ability to compensate using interregional activation fails. We are at the threshold of being able to chart autism and schizophrenia from the inside out. In so doing, the door is opened to the consideration of new therapeutics that are developed based upon molecular, synaptic, and systems targets common to both disorders.

The role of emotion regulation in autism spectrum disorder

OBJECTIVE

Autism spectrum disorder (ASD) is associated with amplified emotional responses and poor emotional control, but little is known about the underlying mechanisms. This article provides a conceptual and methodologic framework for understanding compromised emotion regulation (ER) in ASD.

METHOD

After defining ER and related constructs, methods to study ER were reviewed with special consideration on how to apply these approaches to ASD. Against the backdrop of cognitive characteristics in ASD and existing ER theories, available research was examined to identify likely contributors to emotional dysregulation in ASD.

RESULTS

Little is currently known about ER in youth with ASD. Some mechanisms that contribute to poor ER in ASD may be shared with other clinical populations (e.g., physiologic arousal, degree of negative and positive affect, alterations in the amygdala and prefrontal cortex), whereas other mechanisms may be more unique to ASD (e.g., differences in information processing/perception, cognitive factors [e.g., rigidity], less goal-directed behavior and more disorganized emotion in ASD).

CONCLUSIONS

Although assignment of concomitant psychiatric diagnoses is warranted in some cases, poor ER may be inherent in ASD and may provide a more parsimonious conceptualization for the many associated socioemotional and behavioral problems in this population. Further study of ER in youth with ASD may identify meaningful subgroups of patients and lead to more effective individualized treatments.