Objective To perform a comprehensive meta-analysis of task-based functional MRI studies of Attention-Deficit/Hyperactivity Disorder (ADHD). Method PubMed, Ovid, EMBASE, Web of Science, ERIC, CINHAL, and NeuroSynth were searched for studies published through 06/30/2011. Significant differences in activation of brain regions between individuals with ADHD and comparisons were detected using activation likelihood estimation meta-analysis (p<0.05, corrected). Dysfunctional regions in ADHD were related to seven reference neuronal systems. We performed a set of meta-analyses focused on age groups (children; adults), clinical characteristics (history of stimulant treatment; presence of psychiatric comorbidities), and specific neuropsychological tasks (inhibition; working memory; vigilance/attention). Results Fifty-five studies were included (39 in children, 16 in adults). In children, hypoactivation in ADHD vs. comparisons was found mostly in systems involved in executive functions (frontoparietal network) and attention (ventral attentional network). Significant hyperactivation in ADHD vs. comparisons was observed predominantly within the default, ventral attention, and somatomotor networks. In adults, ADHD-related hypoactivation was predominant in the frontoparietal system, while ADHD-related hyperactivation was present in the visual, dorsal attention, and default networks. Significant ADHD-related dysfunction largely reflected task features and was detected even in the absence of comorbid mental disorders or history of stimulant treatment. Conclusions A growing literature provides evidence of ADHD-related dysfunction within multiple neuronal systems involved in higher-level cognitive functions but also in sensorimotor processes, including the visual system, and in the default network. This meta-analytic evidence extends early models of ADHD pathophysiology focused on prefrontal-striatal circuits.

Attention-deficit/hyperactivity disorder (ADHD) has long been thought to reflect dysfunction of prefrontal-striatal circuitry, with involvement of other circuits largely ignored. Recent advances in systems neuroscience-based approaches to brain dysfunction enable the development of models of ADHD pathophysiology that encompass a number of different large-scale “resting state” networks. Here we review progress in delineating large-scale neural systems and illustrate their relevance to ADHD. We relate frontoparietal, dorsal attentional, motor, visual, and default networks to the ADHD functional and structural literature. Insights emerging from mapping intrinsic brain connectivity networks provide a potentially mechanistic framework for understanding aspects of ADHD, such as neuropsychological and behavioral inconsistency, and the possible role of primary visual cortex in attentional dysfunction in the disorder.

Given concerns about the reproducibility of scientific findings, neuroimaging must define best practices for data analysis, results reporting, and algorithm and data sharing to promote transparency, reliability and collaboration. We describe insights from developing a set of recommendations on behalf of the Organization for Human Brain Mapping and identify barriers that impede these practices, including how the discipline must change to fully exploit the potential of the world’s neuroimaging data.

Context Volumetric studies have reported relatively decreased cortical thickness and gray matter volumes in adults with Attention-Deficit/Hyperactivity Disorder (ADHD) whose childhood status was retrospectively recalled. We present the first prospective study combining cortical thickness and voxel-based morphometry (VBM) in adults diagnosed with ADHD in childhood. Objective In adults who had Combined Type ADHD in childhood, to 1) test whether they exhibit cortical thinning and decreased gray matter in regions hypothesized related to ADHD, and 2) test whether anatomic differences are associated with current ADHD diagnosis, including persistence versus remission. Design Cross-sectional analysis embedded in a 33-year prospective follow-up at mean age 41. Setting Research outpatient center. Participants ADHD probands were from a cohort of 207 6–12 year old Caucasian boys; male comparison subjects (n=178) had been free of ADHD in childhood. We obtained MRI scans in 59 probands and 80 comparisons (28% and 45% of original samples, respectively). Main Outcome Measure Whole-brain VBM and vertex-wise cortical thickness analyses. Results Cortex was significantly thinner in ADHD probands than comparisons in the dorsal attentional network and limbic areas (FDR<0.05, corrected). Additionally, gray matter was significantly decreased in probands in right caudate, right thalamus and bilateral cerebellar hemispheres. Probands with persistent ADHD (n=17) did not differ significantly from remitters (n=26) at FDR<0.05. At uncorrected p<0.05, remitters had thicker cortex relative to those with persistent ADHD in medial occipital cortex, insula, parahippocampus, and prefrontal regions. Conclusions We observed anatomic gray matter reductions in adults with childhood ADHD, regardless of current diagnosis. The most affected regions underpin top-down control of attention and regulation of emotion and motivation. Exploratory analyses suggest that diagnostic remission may result from compensatory maturation of prefrontal, cerebellar, and thalamic circuitry.

Neuroimaging enables rich noninvasive measurements of human brain activity, but translating such data into neuroscientific insights and clinical applications requires complex analyses and collaboration among a diverse array of researchers. The open science movement is reshaping scientific culture and addressing the challenges of transparency and reproducibility of research. To advance open science in neuroimaging the Organization for Human Brain Mapping created the Committee on Best Practice in Data Analysis and Sharing (COBIDAS), charged with creating a report that collects best practice recommendations from experts and the entire brain imaging community. The purpose of this work is to elaborate the principles of open and reproducible research for neuroimaging using Magnetic Resonance Imaging (MRI), and then distill these principles to specific research practices. Many elements of a study are so varied that practice cannot be prescribed, but for these areas we detail the information that must be reported to fully understand and potentially replicate a study. For other elements of a study, like statistical modelling where specific poor practices can be identified, and the emerging areas of data sharing and reproducibility, we detail both good practice and reporting standards. For each of seven areas of a study we provide tabular listing of over 100 items to help plan, execute, report and share research in the most transparent fashion. Whether for individual scientists, or for editors and reviewers, we hope these guidelines serve as a benchmark, to raise the standards of practice and reporting in neuroimaging using MRI.