Enhancing studies of the connectome in autism using the autism brain imaging data exchange II

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

Basal ganglia volume and shape in children with attention deficit hyperactivity disorder

10.1176/appi.ajp.2008.08030426American Journal of Psychiatry166174-82AJPS

Behavioural and neural basis of anomalous motor learning in children with autism

Autism spectrum disorder is a developmental disorder characterized by deficits in social and communication skills and repetitive and stereotyped interests and behaviours. Although not part of the diagnostic criteria, individuals with autism experience a host of motor impairments, potentially due to abnormalities in how they learn motor control throughout development. Here, we used behavioural techniques to quantify motor learning in autism spectrum disorder, and structural brain imaging to investigate the neural basis of that learning in the cerebellum. Twenty children with autism spectrum disorder and 20 typically developing control subjects, aged 8-12, made reaching movements while holding the handle of a robotic manipulandum. In random trials the reach was perturbed, resulting in errors that were sensed through vision and proprioception. The brain learned from these errors and altered the motor commands on the subsequent reach. We measured learning from error as a function of the sensory modality of that error, and found that children with autism spectrum disorder outperformed typically developing children when learning from errors that were sensed through proprioception, but underperformed typically developing children when learning from errors that were sensed through vision. Previous work had shown that this learning depends on the integrity of a region in the anterior cerebellum. Here we found that the anterior cerebellum, extending into lobule VI, and parts of lobule VIII were smaller than normal in children with autism spectrum disorder, with a volume that was predicted by the pattern of learning from visual and proprioceptive errors. We suggest that the abnormal patterns of motor learning in children with autism spectrum disorder, showing an increased sensitivity to proprioceptive error and a decreased sensitivity to visual error, may be associated with abnormalities in the cerebellum

Attention deficit hyperactivity disorder with reading disabilities: preliminary genetic findings on the involvement of the ADRA2A gene

Background: Attention deficit/hyperactivity disorder (ADHD) and reading disability (RD) tend to co-occur and quantitative genetic studies have shown this to arise primarily through shared genetic influences. However, molecular genetic studies have shown different genes to be associated with each of these conditions. Neurobiological studies have implicated noradrenergic function in the aetiology of ADHD that is comorbid with RD. This paper examines the neurobiological evidence and presents preliminary testing of the hypothesis that the ADRA2A receptor gene is contributing to ADHD and comorbid RD. Methods: One hundred and fifty-two children (140 boys, 12 girls) of British Caucasian origin, aged between 6 and 13 years and with a diagnosis of ADHD, were recruited. The children’s reading ability was tested. Children were identified as having ADHD or ADHD plus RD (n =82). DNA was available for 10 parent child trios and 42 parent child duos. Genotyping was undertaken for an ADRA2A polymorphism.Results: For those with ADHD plus RD there was evidence of association with the alpha 2A adrenergic receptor (ADRA2A) polymorphism with the G allele being preferentially transmitted.Conclusions: The preliminary evidence together with other neurobiological research findings suggests that the ADRA2A gene may contribute to comorbid ADHD and RD and needs to be properly examined

Discriminative Analysis of Brain Function at Resting-State for Attention-Deficit/Hyperactivity Disorder

In this work, a discriminative model of attention deficit hyperactivity disorder (ADHD) is presented on the basis of multivariate pattern classification and functional magnetic resonance imaging (fMRI). This model consists of two parts, a classifier and an intuitive representation of discriminative pattern of brain function between patients and normal controls. Regional homogeneity (ReHo), a measure of brain function at resting-state, is used here as a feature of classification. Fisher discriminative analysis (FDA) is performed on the features of training samples and a linear classifier is generated. Our initial experimental results show a successful classification rate of 85%, using leave-one-out cross validation. The classifier is also compared with linear support vector machine (SVM) and Batch Perceptron. Our classifier outperforms the alternatives significantly. Fisher brain, the optimal projective-direction vector in FDA, is used to represent the discriminative pattern. Some abnormal brain regions identified by Fisher brain, like prefrontal cortex and anterior cingulate cortex, are well consistent with that reported in neuroimaging studies on ADHD. Moreover, some less reported but highly discriminative regions are also identified. We conclude that the discriminative model has potential ability to improve current diagnosis and treatment evaluation of ADHD. ? Springer-Verlag Berlin Heidelberg 2005.EI