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Background. Repetitive and restricted behaviors and interests (RRBI) are core symptoms of autism with a complex entity and are commonly categorized into ‘motor-driven’ and ‘cognitively-driven’. RRBI symptomatology depends on the individual’s clinical environment limiting the understanding of RRBI physiology, particularly their associated neuroanatomical structures. The complex RRBI heterogeneity needs to explore the whole RRBI spectrum by integrating the clinical context (autistic individuals, their relatives and typical developing (TD) individuals). We hypothesized that different RRBI dimensions would emerge by exploring the whole spectrum of RRBI, and that these dimensions are associated with neuroanatomical signatures - involving cortical & subcortical areas. Method. A sample of 792 individuals composed of 267 autistic subjects, their 370 first-degree relatives and 155 TD individuals was enrolled in the study. We assessed the whole patterns of RRBI in each individual by using the Repetitive Behavior Scale-Revised and the Yale-Brown Obsessive Compulsive Scale. We estimated brain volumes using MRI scanner for a subsample of the subjects (n=152, 42 ASD, 89 relatives and 13 TD). We first investigated the dimensionality of RRBI by performing a principal component analysis on all items of these scales and included all the sampling population. We then explored the relationship between RRBI-derived factors with brain volumes using linear regression models. Results. We identified 3 main factors (with 30.3% of the RRBI cumulative variance): Factor 1 (FA1, 12.7%) reflected mainly the ‘motor-driven’ RRBI symptoms; Factor 2 and 3 (respectively 8.8% and 7.9%) gathered mainly Y-BOCS related items and represented the ‘cognitively-driven’ RRBI symptoms. These three factors were significantly associated with the right/left putamen volumes but with opposite effects: FA1 was negatively associated with an increased volume of the right/left putamen conversely to FA2 & FA3 (all uncorrected pConclusion. Our results suggested 3 coherent RRBI dimensions involving the putamen commonly and other structures according to the RRBI dimension. The exploration of the putamen’s integrative role in RSBI needs to be strengthened in further studies.

Purpose This study aims to explore the overlap between symptoms of depression, anxiety, irritability and aggressiveness in autism spectrum disorder (ASD), to measure specific and idiosyncratic emotional responses. Design/methodology/approach A total of 42 high functioning adolescents and adults, between 12 and 39 years old, meeting the diagnostic and statistical manual of mental disorders – 5 criteria for ASD were selected from the InFoR Autism cohort. Data were analyzed in an exploratory way using Hill and Smith and K-medoids cluster analysis. Findings The authors found an aggregation of anxiety, depression, aggressive behaviors and irritability. Cluster analysis was maximized for two groups with 17 and 25 participants, respectively. The first group was characterized by high levels of symptoms of irritability, aggressiveness, hyperactivity and intermediate levels of anxiety and depression. In the first group, participants had significantly higher levels of autistic symptoms considering the social responsiveness scale and repetitive behavior scale-revised scales (relatives’ reports) suggesting that a particular group of subjects with a high level of ASD specific symptoms may express anxiety and depression in a specific way based on externalizing behaviors in addition to the common mood and anxiety symptoms. Research limitations/implications Improved understanding of the aggregation of externalized symptoms with symptoms of anxiety and mood disorders in ASD should lead to a better understanding of the underlying mechanisms related to emotion dysregulation in ASD. Practical implications Improved knowledge of the symptoms could lead to enhanced detection of psychiatric comorbidities in ASD. Originality/value The study was based on a transdiagnostic approach of psychiatric symptoms in individuals with ASD. Aggregation and clustering analysis was used to explore naive patterns of these psychiatric symptoms.

International audience; AbstractAim: To identify easily accessible neuroanatomical abnormalities useful for diagnosing fetal alcohol spectrum disorders (FASD) in fetal alcohol syndrome (FAS) but more importantly for the probabilistic diagnosis of non-­syndromic forms (NS-­FASD).Method: We retrospectively collected monocentric data from 52 individuals with FAS, 37 with NS-­FASD, and 94 paired typically developing individuals (6–­20 years, 99 males, 84 females). On brain T1-­weighted magnetic resonance imaging, we measured brain size, corpus callosum length and thicknesses, vermis height, then evaluated vermis foliation (Likert scale). For each parameter, we established variations with age and brain size in comparison individuals (growth and scaling charts), then identified participants with abnormal measurements (

MRI has been extensively used to identify anatomical and functional differences in Autism Spectrum Disorder (ASD). Yet, many of these findings have proven difficult to replicate because studies rely on small cohorts and are built on many complex, undisclosed, analytic choices. We conducted an international challenge to predict ASD diagnosis from MRI data, where we provided preprocessed anatomical and functional MRI data from > 2,000 individuals. Evaluation of the predictions was rigorously blinded. 146 challengers submitted prediction algorithms, which were evaluated at the end of the challenge using unseen data and an additional acquisition site. On the best algorithms, we studied the importance of MRI modalities, brain regions, and sample size. We found evidence that MRI could predict ASD diagnosis: the 10 best algorithms reliably predicted diagnosis with AUC∼0.80 – far superior to what can be currently obtained using genotyping data in cohorts 20-times larger. We observed that functional MRI was more important for prediction than anatomical MRI, and that increasing sample size steadily increased prediction accuracy, providing an efficient strategy to improve biomarkers. We also observed that despite a strong incentive to generalise to unseen data, model development on a given dataset faces the risk of overfitting: performing well in cross-validation on the data at hand, but not generalising. Finally, we were able to predict ASD diagnosis on an external sample added after the end of the challenge (EU-AIMS), although with a lower prediction accuracy (AUC=0.72). This indicates that despite being based on a large multisite cohort, our challenge still produced biomarkers fragile in the face of dataset shifts.

Le confinement survenu en mars 2020 en France, lie a la pandemie de la Covid-19 a eu pour consequence de perturber l’acces aux soins ainsi que les habitudes de la plupart des familles. Pour les parents d’enfant presentant un trouble du neurodeveloppement (tnd), par exemple un trouble du spectre de l’autisme (tsa) ou un trouble du deficit de l’attention et de l’hyperactivite (tdah), les modifications des routines ont aggrave certaines difficultes preexistantes. La necessite d’assurer la continuite des soins tout en respectant les nouvelles contraintes sanitaires a favorise un recours accru a la telemedecine, notamment en psychiatrie de l’enfant. Par ailleurs, pour repondre aux nouvelles difficultes auxquelles les familles confinees ont du faire face, le centre d’excellence Inovand a propose certaines pratiques innovantes. Cet article est une retrospective de ces nouvelles activites conduites par le service durant la periode de confinement. Celles-ci ont consiste a :– creer des fiches techniques et didactiques, repondant a differentes problematiques auxquelles les familles concernees par un tnd ont ete confrontees. Le tout regroupe sur un site Internet ;– organiser un dispositif d’evaluation diagnostique a distance qui a permis d’eviter l’arret brutal d’une grande partie des activites du service ;– elaborer un dispositif d’intervention a distance, sous forme de groupes d’echange et de soutien entre parents.Il semble, au terme de l’experience, que ces solutions de telemedecine mises en place en urgence et de facon transitoire auraient vocation a etre perennisees, car elles offrent un complement aux pratiques habituelles.

Background. Sensory processing atypicalities are part of the core symptoms of autism spectrum disorder (ASD) and could result from an excitation/inhibition imbalance. Yet, the convergence level of phenotypic sensory processing atypicalities with genetic alterations in GABA-ergic and glutamatergic pathways remains poorly understood. This study aimed to characterize the distribution of hypo/hyper-sensory profile among individuals with ASD and investigate the role of deleterious mutations in GABAergic and glutamatergic pathways related genes in sensory processing atypicalities. Method. From the Short Sensory Profile (SSP) questionnaire, we defined and explored a score – the differential Short Sensory Profile (dSSP) - as a normalized and centralized hypo/hypersensitivity ratio for 1136 participants (533 with ASD, 210 first-degree relatives, and 267 controls) from two independent study samples (PARIS and LEAP). We also performed an unsupervised item-based clustering analysis on SSP items scores to validate this new categorization in terms of hypo and hyper sensitivity. We then explored the link between the dSSP score and the burden of deleterious mutations in a subset of individuals for which whole-genome sequencing data were available. Results. We observed a mean dSSP score difference between ASD and controls, driven mostly by a high dSSP score variability among groups (PARIS: p2 = 0.0001, LEAP: p2 = 0.02; LEAP: p=0.01, η2 = 0.01). Clusters were similarly characterized by hypo- and hyper-sensitivity items in both study samples (Cramer's V from 0.64 to 0.69, pLimitations. The major limitation was the dSSP score difficulty to discriminate subjects with a similar quantum of hypo- and hyper- sensory symptoms to those with no such symptoms, resulting both in a similar ratio score of 0.Conclusion. The dSSP score could be a relevant clinical score of the hypo/hyper-sensory individual profile in subjects with ASD. Combined with additional sensory domain characteristics, genetics and endophenotypic substrates, the dSSP score will offer new avenues to explore the underlying neurobiological mechanisms of sensory processing atypicalities in ASD.

International audience; Repetitive behaviors (RB) represent a wide spectrum of symptoms ranging from sensory-motor stereotypies to complex cognitive rituals, frequently dichotomized as low- and high-order sub-groups of symptoms. Even though these subgroups are considered as phenomenologically distinct in autism spectrum disorder (ASD) and obsessive-compulsive disorder (OCD), brain imaging and genetic studies suggest that they have common mechanisms and pathways. This discrepancy may be explained by the frequent intellectual disability reported in ASD, which blurs the RB expressivity. Given the high heritability of RB, that is, the diversity of symptoms expressed in the relatives are dependent on those expressed in their probands, we hypothesize that if RB expressed in ASD or OCD are two distinct entities, then the RB expressed in relatives will also reflect these two dimensions. We thus conduct a linear discriminant analysis on RB in both the relatives of probands with ASD and OCD and subjects from the general population (n = 1023). The discriminant analysis results in a classification of 81.1% of the controls (p

Inconsistencies across studies investigating subcortical correlates of autism spectrum disorder (ASD) may stem from small sample size, sample heterogeneity, and omitting or linearly adjusting for total brain volume (TBV). To properly adjust for TBV, brain allometry—the nonlinear scaling relationship between regional volumes and TBV—was considered when examining subcortical volumetric differences between typically developing (TD) and ASD individuals. Autism Brain Imaging Data Exchange I (ABIDE I; N = 654) data was analyzed with two methodological approaches: univariate linear mixed effects models and multivariate multiple group confirmatory factor analyses. Analyses were conducted on the entire sample and in subsamples based on age, sex, and full scale intelligence quotient (FSIQ). A similar ABIDE I study was replicated and the impact of different TBV adjustments on neuroanatomical group differences was investigated. No robust subcortical allometric or volumetric group differences were observed in the entire sample across methods. Exploratory analyses suggested that allometric scaling and volume group differences may exist in certain subgroups defined by age, sex, and/or FSIQ. The type of TBV adjustment influenced some reported volumetric and scaling group differences. This study supports the absence of robust volumetric differences between ASD and TD individuals in the investigated volumes when adjusting for brain allometry, expands the literature by finding no group difference in allometric scaling, and further suggests that differing TBV adjustments contribute to the variability of reported neuroanatomical differences in ASD., To properly adjust for TBV, brain allometry—the nonlinear scaling relationship between regional volumes and TBV—was considered when examining subcortical volumetric differences between typically developing and ASD individuals. No robust subcortical allometric or volumetric group differences were observed in the entire sample across the univariate linear mixed effects models and the multivariate multiple group confirmatory factor analyses.

Attention Deficit and Hyperactive Disorder (ADHD) and Autism Spectrum Disorders (ASD) are frequent comorbid neurodevelopmental conditions and the overlap between both disorders remains to be delineated. A more complete understanding of the shared genetic and environmental factors is needed. Using a family-based method, we evaluated the risk of ADHD in a group of relatives with an ASD proband (ASD-) and a group of relatives with an ASD and ADHD proband (ASD+). We enrolled 1245 individuals in the study: 499 probands, their 746 first-degree relatives and 140 controls. We used a multivariate generalized estimating equation (GEE) model, in which the dependent variable was the ADHD diagnosis in the relatives and the independent variable the ASD+ or ASD- in probands. We adjusted for sociodemographic factors (age, sex, IQ) and for the nature of the familial relationship with the affected proband (parent or sibling). Among the probands, there were 287 ASD- and 212 ASD+ individuals. ADHD was more frequent in relatives (19%) than in the control group (7%) (p = 0.001). The risk of ADHD was higher in the ASD+ relatives group than in the ASD- relatives group (GEE model OR 1.58 [95% CI 1.04-2.38], p = 0.032). This result was found in parents (OR 1.96 [95% CI 1.14-3.36], but not in siblings (OR 1.28 [95% CI 0.84-1.94], p = 0.434). Our study provides a representative estimate of the family distribution of ADHD in relatives of ASD probands but supports the modest effect of shared genetic and environmental factors between both disorders.

Community-based studies have consistently shown a sex ratio heavily skewed towards males in autism spectrum disorders (ASD). The factors underlying this predominance of males are largely unknown, but the way girls score on standardized categorical diagnostic tools might account for the underrecognition of ASD in girls. Despite the existence of different norms for boys and girls with ASD on several major screening tests, the algorithm of the Autism Diagnosis Interview-Revised (ADI-R) has not been reformulated. The aim of our study was to investigate which ADI-R items discriminate between males and females, and to evaluate their weighting in the final diagnosis of autism. We then conducted discriminant analysis (DA) on a sample of 594 probands including 129 females with ASD, recruited by the Paris Autism Research International Sibpair (PARIS) Study. A replication analysis was run on an independent sample of 1716 probands including 338 females with ASD, recruited through the Autism Genetics Resource Exchange (AGRE) program. Entering the raw scores for all ADI-R items as independent variables, the DA correctly classified 78.9% of males and 72.9% of females (P

The contrast of the interface between the neocortical grey matter and the white matter is emerging as an important neuroimaging phenotype for several brain disorders. To date, a single in vivo study has analysed the cortical grey-to-white matter percent contrast (GWPC) on Magnetic Resonance Imaging (MRI), and has shown a significant decrease of this contrast in several areas in individuals with Autism Spectrum Disorder (ASD). Our goal was to replicate this study across a larger cohort, using the multicenter data from the Autism Brain Imaging Data Exchange 1 and 2 gathering data from 2,148 subjects. Multiple linear regression was used to study the effect of the diagnosis of ASD on the GWPC. Contrary to the first study, we found a statistically significant increase of GWPC among individuals with ASD in left auditory and bilateral visual sensory areas, as well as in the left primary motor cortex. These results were still statistically significant after inclusion of cortical thickness as covariate. There are numerous reports of sensory-motor atypicalities in patients with ASD, which may be the reason for the differences in GWPC that we observed. Further investigation could help us determine the potential role of a defect or a delay in intra-cortical myelination of sensory-motor regions in ASD. Code: https://github.com/neuroanatomy/GWPC.

Despite the high clinical burden, little is known about pathophysiology underlying autism spectrum disorder (ASD). Recent resting-state functional magnetic resonance imaging (rs-fMRI) studies have found atypical synchronization of brain activity in ASD. However, no consensus has been reached on the nature and clinical relevance of these alterations. Here, we addressed these questions in four large ASD cohorts. Using rs-fMRI, we identified functional connectivity alterations associated with ASD. We tested for associations of these imaging phenotypes with clinical and demographic factors such as age, sex, medication status, and clinical symptom severity. Our results showed reproducible patterns of ASD-associated functional hyper- and hypoconnectivity. Hypoconnectivity was primarily restricted to sensory-motor regions, whereas hyperconnectivity hubs were predominately located in prefrontal and parietal cortices. Shifts in cortico-cortical between-network connectivity from outside to within the identified regions were shown to be a key driver of these abnormalities. This reproducible pathophysiological phenotype was partially associated with core ASD symptoms related to communication and daily living skills and was not affected by age, sex, or medication status. Although the large effect sizes in standardized cohorts are encouraging with respect to potential application as a treatment and for patient stratification, the moderate link to clinical symptoms and the large overlap with healthy controls currently limit the usability of identified alterations as diagnostic or efficacy readout.

International audience; Contactin genes CNTN5 and CNTN6 code for neuronal cell adhesion molecules that promote neurite outgrowth in sensory-motor neuronal pathways. Mutations of CNTN5 and CNTN6 have previously been reported in individuals with autism spectrum disorders (ASDs), but very little is known on their prevalence and clinical impact. In this study, we identified CNTN5 and CNTN6 deleterious variants in individuals with ASD. Among the carriers, a girl with ASD and attention-deficit/hyperactivity disorder was carrying five copies of CNTN5. For CNTN6, both deletions (6/1534 ASD vs 1/8936 controls; P=0.00006) and private coding sequence variants (18/501 ASD vs 535/33480 controls; P=0.0005) were enriched in individuals with ASD. Among the rare CNTN6 variants, two deletions were transmitted by fathers diagnosed with ASD, one stop mutation CNTN6(W923X) was transmitted by a mother to her two sons with ASD and one variant CNTN6(P770L) was found de novo in a boy with ASD. Clinical investigations of the patients carrying CNTN5 or CNTN6 variants showed that they were hypersensitive to sounds (a condition called hyperacusis) and displayed changes in wave latency within the auditory pathway. These results reinforce the hypothesis of abnormal neuronal connectivity in the pathophysiology of ASD and shed new light on the genes that increase risk for abnormal sensory perception in ASD.

BackgroundSleep problems are common and impairing in individuals with autism spectrum disorders (ASD). Evidence synthesis including both subjective (ie, measured with questionnaires) and objective (ie, quantified with neurophysiological tools) sleep alterations in youth with ASD is currently lacking.ObjectiveWe conducted a systematic review and meta-analysis of subjective and objective studies sleep studies in youth with ASD.MethodsWe searched the following electronic databases with no language, date or type of document restriction up to 23 May 2018: PubMed, PsycInfo, Embase+Embase Classic, Ovid Medline and Web of Knowledge. Random-effects models were used. Heterogeneity was assessed with Cochran’s Q and I2 statistics. Publication (small studies) bias was assessed with final plots and the Egger’s test. Study quality was evaluated with the Newcastle Ottawa Scale. Analyses were conducted using Review Manager and Comprehensive Meta-Analysis.FindingsFrom a pool of 3359 non-duplicate potentially relevant references, 47 datasets were included in the meta-analyses. Subjective and objective sleep outcome measures were extracted from 37 and 15 studies, respectively. Only five studies were based on comorbidity free, medication-naïve participants. Compared with typically developing controls, youth with ASD significantly differed in 10/14 subjective parameters and in 7/14 objective sleep parameters. The average quality score in the Newcastle-Ottawa Scale was 5.9/9.Discussion and clinical implicationsA number of subjective and, to a less extent, objective sleep alterations might characterise youth with ASD, but future studies should assess the impact of pharmacological treatment and psychiatric comorbidities.

Despite the high clinical burden little is known about pathophysiology underlying autism spectrum disorder (ASD). Recent resting state functional magnetic resonance imaging (rs-fMRI) studies have found atypical synchronization of brain activity in ASD. However, no consensus has been reached on the nature and clinical relevance of these alterations. Here we address these questions in the most comprehensive, large-scale effort to date comprising evaluation of four large ASD cohorts. We followed a strict exploration and replication procedure to identify core rs-fMRI functional connectivity (degree centrality) alterations associated with ASD as compared to typically developing (TD) controls (ASD: N=841, TD: N=984). We then tested for associations of these imaging phenotypes with clinical and demographic factors such as age, sex, medication status and clinical symptom severity. We find reproducible patterns of ASD-associated functional hyper- and hypo-connectivity with hypo-connectivity being primarily restricted to sensory-motor regions and hyper-connectivity hubs being predominately located in prefrontal and parietal cortices. We establish shifts in between-network connectivity from outside to within the identified regions as a key driver of these abnormalities. The magnitude of these alterations is linked to core ASD symptoms related to communication and social interaction and is not affected by age, sex or medication status. The identified brain functional alterations provide a reproducible pathophysiological phenotype underlying the diagnosis of ASD reconciling previous divergent findings. The large effect sizes in standardized cohorts and the link to clinical symptoms emphasize the importance of the identified imaging alterations as potential treatment and stratification biomarkers for ASD.

International audience; Background:Patients with autism have been often reported to have a smaller corpus callosum (CC) than control subjects.; Methods:We conducted a meta-analysis of the literature, analyzed the CC in 694 subjects of the Autism Brain Imaging Data Exchange project, and performed computer simulations to study the effect of different analysis strategies.; Results:Our meta-analysis suggested a group difference in CC size; however, the studies were heavily underpowered (20% power to detect Cohen's d = .3). In contrast, we did not observe significant differences in the Autism Brain Imaging Data Exchange cohort, despite having achieved 99% power. However, we observed that CC scaled nonlinearly with brain volume (BV): large brains had a proportionally smaller CC. Our simulations showed that because of this nonlinearity, CC normalization could not control for eventual BV differences, but using BV as a covariate in a linear model would. We also observed a weaker correlation of IQ and BV in cases compared with control subjects. Our simulations showed that matching populations by IQ could then induce artifactual BV differences.; Conclusions:The lack of statistical power in the previous literature prevents us from establishing the reality of the claims of a smaller CC in autism, and our own analyses did not find any. However, the nonlinear relationship between CC and BV and the different correlation between BV and IQ in cases and control subjects may induce artifactual differences. Overall, our results highlight the necessity for open data sharing to provide a more solid ground for the discovery of neuroimaging biomarkers within the context of the wide human neuroanatomical diversity.

Community-based studies have consistently shown a sex ratio heavily skewed towards males in autism spectrum disorders (ASD). The factors underlying this predominance of males are largely unknown, but the way girls score on standardized categorical diagnostic tools might account for the underrecognition of ASD in girls. Despite the existence of different norms for boys and girls with ASD on several major screening tests, the algorithm of the Autism Diagnosis Interview-Revised (ADI-R) has not been reformulated. The aim of our study was to investigate which ADI-R items discriminate between males and females, and to evaluate their weighting in the final diagnosis of autism. We then conducted discriminant analysis (DA) on a sample of 594 probands including 129 females with ASD, recruited by the Paris Autism Research International Sibpair (PARIS) Study. A replication analysis was run on an independent sample of 1716 probands including 338 females with ASD, recruited through the Autism Genetics Resource Exchange (AGRE) program. Entering the raw scores for all ADI-R items as independent variables, the DA correctly classified 78.9% of males and 72.9% of females (P 0.001) in the PARIS cohort, and 72.2% of males and 68.3% of females (P 0.0001) in the AGRE cohort. Among the items extracted by the stepwise DA, four belonged to the ADI-R algorithm used for the final diagnosis of ASD. In conclusion, several items of the ADI-R that are taken into account in the diagnosis of autism significantly differentiates between males and females. The potential gender bias thus induced may participate in the underestimation of the prevalence of ASD in females. Autism Res 2016,. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. Autism Res 2017, 10: 680-689. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

The second iteration of the Autism Brain Imaging Data Exchange (ABIDE II) aims to enhance the scope of brain connectomics research in Autism Spectrum Disorder (ASD). Consistent with the initial ABIDE effort (ABIDE I), that released 1112 datasets in 2012, this new multisite open-data resource is an aggregate of resting state functional magnetic resonance imaging (MRI) and corresponding structural MRI and phenotypic datasets. ABIDE II includes datasets from an additional 487 individuals with ASD and 557 controls previously collected across 16 international institutions. The combination of ABIDE I and ABIDE II provides investigators with 2156 unique cross-sectional datasets allowing selection of samples for discovery and/or replication. This sample size can also facilitate the identification of neurobiological subgroups, as well as preliminary examinations of sex differences in ASD. Additionally, ABIDE II includes a range of psychiatric variables to inform our understanding of the neural correlates of co-occurring psychopathology; 284 diffusion imaging datasets are also included. It is anticipated that these enhancements will contribute to unraveling key sources of ASD heterogeneity. ispartof: Scientific Data vol:4 ispartof: location:England status: published

Cerebellar volume abnormalities have been often suggested as a possible endophenotype for autism spectrum disorder (ASD). We aimed at objectifying this possible alteration by performing a systematic meta-analysis of the literature, and an analysis of the Autism Brain Imaging Data Exchange (ABIDE) cohort. Our meta-analysis sought to determine a combined effect size of ASD diagnosis on different measures of the cerebellar anatomy, as well as the effect of possible factors of variability across studies. We then analysed the cerebellar volume of 328 patients and 353 controls from the ABIDE project. The meta-analysis of the literature suggested a weak but significant association between ASD diagnosis and increased cerebellar volume (p=0.049, uncorrected), but the analysis of ABIDE did not show any relationship. The studies in the literature were generally underpowered, however, the number of statistically significant findings was larger than expected. Although we could not provide a conclusive explanation for this excess of significant findings, our analyses would suggest publication bias as a possible reason. Finally, age, sex and IQ were important sources of cerebellar volume variability, however, independent of autism diagnosis.

Resume Les nombreuses etudes en neuro-imagerie, conduites dans les vingt dernieres annees, ont eu un role cle dans la comprehension des mecanismes pathophysiologiques a la base du trouble de deficit de l’attention/hyperactivite. Meme si la plupart des etudes ont un faible pouvoir statistique, de recentes meta-analyses ont permis de faire des conclusions solides sur l’imputation de circuits cerebraux relies aux fonctions cognitives superieures ainsi que de reseaux sensorimoteurs de base. Notamment, de nombreuses etudes soutiennent l’implication tant des systemes fronto-parietal, striatal, thalamique et cerebelleux que des reseaux regulateurs des processus attentionnels, du « mode de defaut », des cortex sensorimoteur et visuel. De toute facon, l’application, en pratique clinique, de ces connaissances reste le principal defi actuel. Les « machines a vecteur de support » representent une nouvelle approche analytique qui pourrait surmonter cet enjeu, dans l’optique du developpement d’une medecine personnalisee.

Neuroimaging studies of attention-deficit/hyperactivity disorder (ADHD) are continuously adding to our knowledge on the neurobiology of this condition. Here, we update previous narrative and systematic reviews on the neuroimaging of ADHD, focusing on studies published in 2013. In order to comprehensively retrieve all the published studies, we searched a broad range of electronic databases (PubMed, Ovid PsychInfo, Ovide Medline, Web of Science, and EMBASE). We critically overview anatomical magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) studies, as well as functional MRI and resting state MRI studies. We also included studies aimed at elucidating the mechanism of action of ADHD drugs. We conclude that the combination of multimodal neuroimaging techniques has the potential not only to increase our understanding of structural disruptions in neuronal circuits associated with functional deficits in children with ADHD, but also to provide objective data that may assist the clinician in the day-to-day practice.

The corpus callosum -- the main pathway for long-distance inter-hemispheric integration in the human brain -- has been frequently reported to be smaller among autistic patients compared with non-autistic controls. We conducted a meta-analysis of the literature which suggested a statistically significant difference. However, the studies included were heavily underpowered: on average only 20% power to detect differences of 0.3 standard deviations, which makes it difficult to establish the reality of such a difference. We therefore studied the size of the corpus callosum among 694 subjects (328 patients, 366 controls) from the Abide cohort. Despite having achieved 99% power to detect statistically significant differences of 0.3 standard deviations, we did not observe any. To better understand the neuroanatomical diversity of the corpus callosum, and the possible reasons for the previous findings, we analysed the relationship between its size, the size of the brain, intracranial volume and intelligence scores. The corpus callosum appeared to scale non-linearly with brain size, with large brains having a proportionally smaller corpus callosum. Additionally, intelligence scores correlated with brain volume among controls but the correlation was significantly weaker among patients. We used simulations to determine to which extent these two effects could lead to artefactual differences in corpus callosum size within populations. We observed that, were there a difference in brain volume between cases and controls, normalising corpus callosum size by brain volume would not eliminate the brain volume effect, but adding brain volume as a covariate in a linear model would. Finally, we observed that because of the weaker correlation of intelligence scores and brain volume among patients, matching populations by intelligence scores could result in a bias towards including more patients with large brain volumes, inducing an artificial difference. Overall, our results highlight the necessity for open data sharing efforts such as Abide to provide a more solid ground for the discovery of neuroimaging biomarkers, within the context of the wide human neuroanatomical diversity.

Objectives: the purpose of our study was to describe the demographic and phenotypic profiles of a French cohort of toddlers with social communication disorders. We also aimed to estimate if the cumulative effect of risk factors know to be associated with ASD increases the probability to receive a final diagnosis of ASD. Methods: we retrospectively collected and analyzed the clinical data of children aged