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

Reproducibility in the absence of selective reporting : An illustration from large-scale brain asymmetry research

Altres ajuts: Max Planck Society (Germany).The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p-hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left-right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta-analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an "ideal publishing environment," that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically-used sample sizes

Current issues in the diagnosis of attention deficit hyperactivity disorder, oppositional defiant disorder, and conduct disorder

This review evaluates the diagnostic criteria for three of the most common disorders for which children and adolescents are referred for mental health treatment: attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and conduct disorder (CD). Although research supports the validity and clinical utility of these disorders, several issues are highlighted that could enhance the current diagnostic criteria. For ADHD, defining the core features of the disorder and its fit with other disorders, enhancing the validity of the criteria through the lifespan, considering alternative ways to form subtypes of the disorder, and modifying the age-of-onset criterion are discussed relative to the current diagnostic criteria. For ODD, eliminating the exclusionary criteria of CD, recognizing important symptom domains within the disorder, and using the cross-situational pervasiveness of the disorder as an index of severity are highlighted as important issues for improving classification. Finally, for CD, enhancing the current subtypes related to age of onset and integrating callous-unemotional traits into the diagnostic criteria are identified as key issues for improving classification

Recent developments in neuropsychological models of childhood psychiatric disorders

The number of studies on the neuropsychology of childhood disorders has increased exponentially over the past decade. We report the results of an initial meta-analysis of key neuropsychological constructs included in studies of nine of the most prevalent childhood disorders. Results indicated that the neuropsychological etiologies of each of these disorders are complex and multifactorial. No single deficit is necessary or sufficient to explain all cases of any disorder, but preliminary evidence suggests that disorders may be distinguished by profiles across multiple neuropsychological processes. Slow processing speed and increased response variability are ubiquitous across disorders, but somewhat distinct profiles emerge on different aspects of executive functions. Attention deficit/hyperactivity disorder and Tourette’s disorder are most strongly associated with inhibitory difficulties, whereas difficulties with cognitive flexibility are most pronounced in groups with autism spectrum disorders and childhood-onset schizophrenia. Working memory difficulties are significant in most groups, but these weaknesses are largest in groups with learning disorders and childhood-onset schizophrenia. Future research is needed to clarify further the relations among these heterogeneous diagnostic phenotypes and complex neuropsychological processes to facilitate studies that link these weaknesses to specific etiological risk factors.<br/

Annual research review: Reaction time variability in ADHD and autism spectrum disorders: measurement and mechanisms of a proposed trans-diagnostic phenotype

Background: Intraindividual variability in reaction time (RT) has received extensive discussion as an indicator of cognitive performance, a putative intermediate phenotype of many clinical disorders, and a possible trans-diagnostic phenotype that may elucidate shared risk factors for mechanisms of psychiatric illnesses. Scope and Methodology: Using the examples of attention deficit hyperactivity disorder (ADHD) and autism spectrum disorders (ASD), we discuss RT variability. We first present a new meta-analysis of RT variability in ASD with and without comorbid ADHD. We then discuss potential mechanisms that may account for RT variability and statistical models that disentangle the cognitive processes affecting RTs. We then report a second meta-analysis comparing ADHD and non-ADHD children on diffusion model parameters. We consider how findings inform the search for neural correlates of RT variability. Findings: Results suggest that RT variability is increased in ASD only when children with comorbid ADHD are included in the sample. Furthermore, RT variability in ADHD is explained by moderate to large increases (d = 0.63-0.99) in the ex-Gaussian parameter τ and the diffusion parameter drift rate, as well as by smaller differences (d = 0.32) in the diffusion parameter of nondecision time. The former may suggest problems in state regulation or arousal and difficulty detecting signal from noise, whereas the latter may reflect contributions from deficits in motor organization or output. The neuroimaging literature converges with this multicomponent interpretation and also highlights the role of top-down control circuits. Conclusion: We underscore the importance of considering the interactions between top-down control, state regulation (e.g. arousal), and motor preparation when interpreting RT variability and conclude that decomposition of the RT signal provides superior interpretive power and suggests mechanisms convergent with those implicated using other cognitive paradigms. We conclude with specific recommendations for the field for next steps in the study of RT variability in neurodevelopmental disorders