Background Children born to teenage mothers (<20 years) are at increased risk of psychopathology, partly due atypical brain development. We explored whether this risk is mediated by perinatal complications more frequent in teenage pregnancies and by their impact on perinatal brain maturation indexed by sulcal morphometry. Method Using data from the ABCD study (N=5291 singletons, 9–11 years old), we investigated the associations between maternal age, child psychopathology risks (CBCL), sulcal morphometry (sulcal surface, width, length and mean depth) and perinatal complications through mixed modeling, mediation analysis and structural equation modeling. Results Maternal age was negatively associated with CBCL scores, indicating higher risks of psychopathology in children born to teenage mothers. Severe anemia, nausea, unplanned pregnancy, tobacco/marijuana use, and urinary tract infection partially mediate this association. Consistently, SEM showed that maternal age’s association with offspring psychopathology risk was mediated by perinatal adversities that were more prevalent in teenage pregnancies.Maternal age was associated with sulcal morphometry, consistent with variations in perinatal brain maturation. In boys, perinatal adversity linked to teenage pregnancies was associated with wider frontal and sub-parietal sulci, which mediated higher CBCL scores in boys born to teenage mother. In girls, maternal age was positively associated with occipito-temporal sulcus length; however, sulcal morphometry was not associated with perinatal adversity in teenage pregnancies and did not mediate psychopathology risks. Conclusion Overall, this study suggests that teenage motherhood is linked to early brain development and psychopathology risks in offspring partly through the perinatal adversities that are more commonly associated with it. Plain Language Summary Children born to teenage mothers face increased psychopathology risk during childhood. This association was partly explained by pregnancy-related adversities more common in teenage pregnancies, such as unplanned pregnancy, urinary tract infections, and substance use. These perinatal adversities were associated with markers of perinatal brain maturation, partly accounting for later mental health risks. This increased risk was not reducible to socioeconomic disadvantage, environmental hardship, or familial context, suggesting that perinatal complications associated with teenage pregnancy may contribute to child vulnerability through a distinct developmental pathway. These findings underline the importance of targeted prenatal monitoring for teenage mothers.

Gyrification, the intricate folding of the brain's cortex, begins mid-gestation and surges dramatically throughout the perinatal period. Yet, a critical factor has been largely overlooked in neurodevelopmental research: the profound impact of birth on brain structure. Leveraging the largest known perinatal MRI dataset-819 sessions spanning 21 to 45 postconceptional weeks-we reveal a burst in gyrification immediately following birth (~37 weeks post-conception), amounting to half the entire gyrification expansion occurring during the fetal period. Using state-of-the-art, homogenized imaging processing tools across varied acquisition protocols, and applying a regression discontinuity design approach that is novel to neuroimaging, we provide the first evidence of a sudden, birth-triggered shift in cortical development. Investigation of additional cortical features confirms that this effect is uniquely confined to gyrification. This finding sheds light onto the understanding of early brain development, suggesting that the neurobiological consequences of birth may hold significant behavioral and physiological relevance.

ABSTRACT The perinatal period involves transitioning from an intra- to an extrauterine environment, which requires a complex adaptation of the brain. This period is marked with dynamic and multifaceted cortical changes in both structure and function. Most studies to date have focused either on the fetal or postnatal period, independently. To the best of our knowledge, this is the first neurodevelopmental study targeting the cortical trajectory of typically developing perinatal subjects, combining MRIs from both fetal and postnatal participants. Prior to analysis, preprocessing and segmentation parameters were harmonized across all subjects in order to overcome methodological limitations that arise when studying such different populations. We conducted a normative modeling analysis on a sample of 607 subjects, age ranged 24 to 45 weeks post-conception, to observe changes that arise as participants traverse the birth barrier. We observed that the trajectories of global surface area and several volumetric features, including total gray matter, white matter, brainstem, cerebellum and hippocampi, follow distinct but continuous patterns during this transition. We further report three features presenting a discontinuity in their neurodevelopmental trajectories as participants traverse from a fetal to a postnatal environment: the extra-cerebrospinal fluid volume, the ventricular volume and global gyrification. The current study demonstrates the presence of unique neurodevelopmental patterns for several structural features during the perinatal period, and confirms that not all features are affected in the same way as they cross the birth barrier. SIGNIFICANCE STATEMENT The perinatal phase comprises the fetal and immediate postnatal period, and is generally described as the time surrounding birth. Comprehensively understanding this period is crucial due to the presence of dynamic and multifaceted brain changes. What makes this investigation unique is that it is the first neurodevelopmental study, to the best of our knowledge, focused on the cortical trajectory of typically developing perinatal subjects through the combination of both fetal and postnatal participants into one analysis. We report that certain brain feature trajectories change drastically as fetuses become newborns, while other features remain continuous. These observations are relevant in both the isolation of biomarkers for later cognitive and physiological disorders and in the understanding of typical cerebral development.

Only a small number of studies have assessed structural differences between the two hemispheres during childhood and adolescence. However, the existing findings lack consistency or are restricted to a particular brain region, a specific brain feature, or a relatively narrow age range. Here, we investigated associations between brain asymmetry and age as well as sex in one of the largest pediatric samples to date (n = 4265), aged 1-18 years, scanned at 69 sites participating in the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium. Our study revealed that significant brain asymmetries already exist in childhood, but their magnitude and direction depend on the brain region examined and the morphometric measurement used (cortical volume or thickness, regional surface area, or subcortical volume). With respect to effects of age, some asymmetries became weaker over time while others became stronger; sometimes they even reversed direction. With respect to sex differences, the total number of regions exhibiting significant asymmetries was larger in females than in males, while the total number of measurements indicating significant asymmetries was larger in males (as we obtained more than one measurement per cortical region). The magnitude of the significant asymmetries was also greater in males. However, effect sizes for both age effects and sex differences were small. Taken together, these findings suggest that cerebral asymmetries are an inherent organizational pattern of the brain that manifests early in life. Overall, brain asymmetry appears to be relatively stable throughout childhood and adolescence, with some differential effects in males and females.

AbstractNeurodevelopmental disorders (NDDs) constitute a major health issue with >10% of the general worldwide population affected by at least one of these conditions—such as autism spectrum disorders (ASD) and attention deficit hyperactivity disorders (ADHD). Each NDD is particularly complex to dissect for several reasons, including a high prevalence of comorbidities and a substantial heterogeneity of the clinical presentation. At the genetic level, several thousands of genes have been identified (polygenicity), while a part of them was already involved in other psychiatric conditions (pleiotropy). Given these multiple sources of variance, gathering sufficient data for the proper application and evaluation of machine learning (ML) techniques is essential but challenging. In this chapter, we offer an overview of the ML methods most widely used to tackle NDDs’ complexity—from stratification techniques to diagnosis prediction. We point out challenges specific to NDDs, such as early diagnosis, that can benefit from the recent advances in the ML field. These techniques also have the potential to delineate homogeneous subgroups of patients that would enable a refined understanding of underlying physiopathology. We finally survey a selection of recent papers that we consider as particularly representative of the opportunities offered by contemporary ML techniques applied to large open datasets or that illustrate the challenges faced by current approaches to be addressed in the near future.

Background: Analyzing cortical folding may provide insight into the biological underpinnings of neuro-developmental diseases. A neurodevelopmental subtype of bipolar disorders (BD-ND) has been characterized by the combination of early age of onset and psychotic features. We investigate potential cortical morphology differences associated with this subtype. We analyze, for the first time in bipolar disorders, the sulcal pits, the deepest points in each fold of the cerebral cortex.Methods: We extracted the sulcal pits from anatomical MRI among 512 participants gathered from 7 scanning sites. We compared the number of sulcal pits in each hemisphere as well as their regional occurrence and depth between the BD-ND subgroup (N = 184), a subgroup without neurodevelopmental features (BD, N = 77) and a group of healthy controls (HC, N = 251).Results: In whole brain analysis, BD-ND group have a higher number of sulcal pits in comparison to the BD group. The local analysis revealed, after correction for multiple testing, a higher occurrence of sulcal pits in the left premotor cortex among the BD-ND subgroup compared to the BD and the HC groups.Conclusion: Our findings confirm that BD-ND is associated with a specific brain morphology revealed by the analysis of sulcal pits. These markers may help to better understand neurodevelopment in mood disorder and stratify patients according to a pathophysiological hypothesis.

Background Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life. Methods Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed. Results Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth. Conclusions Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy.

Small average differences in the left-right asymmetry of cerebral cortical thickness have been reported in individuals with autism spectrum disorder (ASD) compared to typically developing controls, affecting widespread cortical regions. The possible impacts of these regional alterations in terms of structural network effects have not previously been characterized. Inter-regional morphological covariance analysis can capture network connectivity between different cortical areas at the macroscale level. Here, we used cortical thickness data from 1455 individuals with ASD and 1560 controls, across 43 independent datasets of the ENIGMA consortium’s ASD Working Group, to assess hemispheric asymmetries of intra-individual structural covariance networks, using graph theory-based topological metrics. Compared with typical features of small-world architecture in controls, the ASD sample showed significantly altered average asymmetry of networks involving the fusiform, rostral middle frontal, and medial orbitofrontal cortex, involving higher randomization of the corresponding right-hemispheric networks in ASD. A network involving the superior frontal cortex showed decreased right-hemisphere randomization. Based on comparisons with meta-analyzed functional neuroimaging data, the altered connectivity asymmetry particularly affected networks that subserve executive functions, language-related and sensorimotor processes. These findings provide a network-level characterization of altered left-right brain asymmetry in ASD, based on a large combined sample. Altered asymmetrical brain development in ASD may be partly propagated among spatially distant regions through structural connectivity.

IMPORTANCE:Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood. OBJECTIVE:To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia. DESIGN, SETTING, AND PARTICIPANTS:Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244. MAIN OUTCOMES AND MEASURES:Interregional profiles of group difference in cortical thickness between cases and controls. RESULTS:A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders. CONCLUSIONS AND RELEVANCE:In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.

Virtual reality is a new technology that can be used to model an environment with which an individual can interact using all five senses. It is notably used in psychiatry for anxiety disorders and addictions, and its use in eating disorders has been growing in recent years. Indeed, virtual reality offers interesting advantages, such as its ability to personalize any environment, which is also more secure and controllable. Recent studies show promising results in the understanding, evaluation, and therapeutic management of eating disorders. The use of avatars in anorexia nervosa allows for a correct assessment of the perceptual (body image distortion) and cognitive-affective (body dissatisfaction) components of the body image disorder in a similar way to conventional methods, but also for a better understanding of them. Moreover, avatars allow the development of innovative therapeutic protocols and are thus used in the context of exposure therapy. The new body swapping protocol, based on a multisensory illusion, offers particularly promising results in the reduction of body image disorder. For bulimia nervosa and binge eating disorder, virtual reality has made it possible to better characterize the triggering mechanisms of binge eating episodes through studies that have observed different responses to food-related environments and stimuli. At the therapeutic level, virtual reality cue exposure therapy has the most empirical support. Its aim is to reduce or eliminate the anxiety and craving felt by a patient in response to exposure to food or other food-related cues by preventing the patient from consuming food, and results show clear reductions in anxiety, craving and binge eating episodes. While all these results seem to indicate a bright future for virtual reality in eating disorders, further studies are needed to validate the positive impact of its use, but also its limitations. Notably, cyber sickness could alter the smooth running of virtual reality therapy sessions by causing nausea and disorientation. Moreover, it is important to verify that a therapeutic protocol does not lose its effectiveness when it is transposed into virtual reality. However, virtual reality seems to be a therapeutic tool that is better accepted by patients, and even better by adolescents, which is very interesting for eating disorders since adolescents are the most affected. Virtual reality could therefore help motivate patients to pursue treatment and reduce the dropout rate while offering good therapeutic results. Thus, studies conducted in recent years have shown that virtual reality is a promising tool in the understanding, assessment and treatment of eating disorders, and future research should confirm this, particularly in the adolescent population. (C) 2021 L'Encephale, Paris.

Altered structural brain asymmetry in autism spectrum disorder (ASD) has been reported. However, findings have been inconsistent, likely due to limited sample sizes. Here we investigated 1,774 individuals with ASD and 1,809 controls, from 54 independent data sets of the ENIGMA consortium. ASD was significantly associated with alterations of cortical thickness asymmetry in mostly medial frontal, orbitofrontal, cingulate and inferior temporal areas, and also with asymmetry of orbitofrontal surface area. These differences generally involved reduced asymmetry in individuals with ASD compared to controls. Furthermore, putamen volume asymmetry was significantly increased in ASD. The largest case-control effect size was Cohen’s d = −0.13, for asymmetry of superior frontal cortical thickness. Most effects did not depend on age, sex, IQ, severity or medication use. Altered lateralized neurodevelopment may therefore be a feature of ASD, affecting widespread brain regions with diverse functions. Large-scale analysis was necessary to quantify subtle alterations of brain structural asymmetry in ASD.

Sulcal pits are the points of maximal depth within the folds of the cortical surface. These shape descriptors give a unique opportunity to access to a rich, fine-scale representation of the geometry and the developmental milestones of the cortical surface. However, using sulcal pits analysis at group level requires new numerical tools to establish inter-subject correspondences. Here, we address this issue by taking advantage of the geometrical information carried by sulcal basins that are the local patches of surfaces surrounding each sulcal pit. Our framework consists in two phases. First, we present a new method to generate a population-specific atlas of this sulcal basins organi- zation as a fold-level parcellation of the cortical surface. Then, we address the labeling of individual sulcal pits and corresponding basins with respect to this atlas. To assess their validity, we applied these methodological advances on two different populations of healthy subjects. The first database of 137 adults allowed us to compare our method to the state-of-the-art and the second database of 209 children, aged between 0 and 18 years, illustrates the adaptability and relevance of our method in the context of pediatric data showing strong variations in cortical volume and folding.

The central sulcus is probably one of the most studied folds in the human brain, owing to its clear relationship with primary sensory-motor functional areas. However, due to the difficulty of estimating the trajectories of the U-shape fibres from diffusion MRI, the short structural connectivity of this sulcus remains relatively unknown. In this context, we studied the spatial organization of these U-shape fibres along the central sulcus. Based on high quality diffusion MRI data of 100 right-handed subjects and state-of-the-art pre-processing pipeline, we first define a connectivity space that provides a comprehensive and continuous description of the short-range anatomical connectivity around the central sulcus at both the individual and group levels. We then infer the presence of five major U-shape fibre bundles at the group level in both hemispheres by applying unsupervised clustering in the connectivity space. We propose a quantitative investigation of their position and number of streamlines as a function of hemisphere, sex and functional scores such as handedness and manual dexterity. Main findings of this study are twofold: a description of U-shape short-range connectivity along the central sulcus at group level and the evidence of a significant relationship between the position of three hand related U-shape fibre bundles and the handedness score of subjects.

Humans are commonly motivated towards cooperation and prosociality. In this study, we examined this motivational predisposition in autistic individuals. Using an adaptation of the Cyberball paradigm, we investigated subsequent pro-social behaviour after witnessing social exclusion. Participants witnessed and played a series of Cyberball games, rated their affective state and valued emotional faces with respect to their approachability. Results showed that participants from both groups were aware of the social exclusion. However, while neurotypically developing participants engaged in pro-social behaviour in reaction to the exclusion, autistic participants showed less alterations, in terms of either behaviour or affective state. The current findings suggest a distinct motivational drive and processing of social reward stimuli in autism, which may result in behavioural responses divergent from typical development when engaging in the social world.

Neuroimaging has been extensively used to study brain structure and function in individuals with attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) over the past decades. Two of the main shortcomings of the neuroimaging literature of these disorders are the small sample sizes employed and the heterogeneity of methods used. In 2013 and 2014, the ENIGMA-ADHD and ENIGMA-ASD working groups were respectively, founded with a common goal to address these limitations. Here, we provide a narrative review of the thus far completed and still ongoing projects of these working groups. Due to an implicitly hierarchical psychiatric diagnostic classification system, the fields of ADHD and ASD have developed largely in isolation, despite the considerable overlap in the occurrence of the disorders. The collaboration between the ENIGMA-ADHD and -ASD working groups seeks to bring the neuroimaging efforts of the two disorders closer together. The outcomes of case-control studies of subcortical and cortical structures showed that subcortical volumes are similarly affected in ASD and ADHD, albeit with small effect sizes. Cortical analyses identified unique differences in each disorder, but also considerable overlap between the two, specifically in cortical thickness. Ongoing work is examining alternative research questions, such as brain laterality, prediction of case-control status, and anatomical heterogeneity. In brief, great strides have been made toward fulfilling the aims of the ENIGMA collaborations, while new ideas and follow-up analyses continue that include more imaging modalities (diffusion MRI and resting-state functional MRI), collaborations with other large databases, and samples with dual diagnoses.

Perinatal Magnetic Resonance Imaging has proven to be suitable and efficient for detecting alterations in a growing number of pathologies. Major advances in brain MRI acquisition and processing open the way to quantitative analyses not achievable so far. Recent results highlight the great potential of regional descriptors of the geometry of the cortical surface extracted from anatomical MRI to characterize typical and abnormal maturation trajectories in the perinatal

Diffusion MR images are prone to severe geometric distortions induced by head movement, eddy-current and inhomogeneity of magnetic susceptibility. Various correction methods have been proposed that depend on the choice of the acquisition settings and potentially provide highly different data quality. However, the impact of this choice has not been evaluated in terms of the ratio between scan time and preprocessed data quality. This study aims at investigating the impact of six wellknown preprocessing methods, each associated to specific acquisition settings, on the outcome of diffusion analyses. For this purpose, we developed a comprehensive toolbox called Diffuse which automatically guides the user to the best preprocessing pipeline according to the input data. Using MR images of 20 subjects from the HCP dataset, we compared the six pre-processing pipelines regarding the following criteria: the ability to recover brain's true geometry, the tensor model estimation and derived indices in the white matter, and finally the spatial dispersion of six well known connectivity pathways. As expected the pipeline associated to the longer acquisition fully repeated with reversed phase-encoding (RPE) yielded the higher data quality and was used as a reference to evaluate the other pipelines. In this way, we highlighted several significant aspects of other pre-processing pipelines. Our results first established that eddy-current correction improves the tensor-fitting performance with a localized impact especially in the corpus callosum. Concerning susceptibility distortions, we showed that the use of a field map is not sufficient and involves additional smoothing, yielding to an artificial decrease of tensor-fitting error. Of most importance, our findings demonstrate that, for an equivalent scan time, the acquisition of a b0 volume with RPE ensures a better brain's geometry reconstruction and local improvement of tensor quality, without any smoothing of the image. This was found to be the best scan time/data quality compromise. To conclude, this study highlights and attempts to quantify the strong dependence of diffusion metrics on acquisition settings and preprocessing methods.

Background Left-right asymmetry is an important organizing feature of the healthy brain. Various studies have reported altered structural brain asymmetry in autism spectrum disorder (ASD). However, findings have been inconsistent, likely due to limited sample sizes and low statistical power. Methods We investigated 1,774 subjects with ASD and 1,809 controls, from 54 datasets, for differences in the asymmetry of thickness and surface area of 34 cerebral cortical regions. We also examined global hemispheric measures of cortical thickness and area asymmetry, and volumetric asymmetries of subcortical structures. Data were obtained via the ASD Working Group of the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium. T1-weighted MRI data were processed with a single protocol using FreeSurfer and the Desikan-Killiany atlas. Results ASD was significantly associated with reduced leftward asymmetry of total hemispheric average cortical thickness, compared to controls. Eight regional thickness asymmetries, distributed over the cortex, also showed significant associations with diagnosis after correction for multiple comparisons, for which asymmetry was again generally lower in ASD versus controls. In addition, the medial orbitofrontal surface area was less rightward asymmetric in ASD than controls, and the putamen volume was more leftward asymmetric in ASD than controls. The largest effect size had Cohen’s d = 0.15. Most effects did not depend on age, sex, IQ, or disorder severity. Conclusion Altered lateralized neurodevelopment is suggested in ASD, affecting widespread cortical regions with diverse functions. Large-scale analysis was necessary to reliably detect, and accurately describe, subtle alterations of structural brain asymmetry in this disorder.