Neuroimaging provides a window into the developing brain, allowing us to examine safely and noninvasively brain anatomy, function, biochemistry, and connectivity. When applied to neurodevelopmental disorders, such as ADHD, imaging in vivo could provide objective tools to inform diagnosis, prognosis, and stimulate discovery of novel therapeutics. In this article, three recent important trends in ADHD neuroimaging are highlighted: (1) the rise of big data in ADHD imaging; (2) how neuroimaging has expanded its focus from children to include adults; and (3) efforts to translate neuroimaging into clinical tools. This review is selective and provides a narrative rather than quantitative synthesis of recent literature.
Big data and genetic imaging
As clinicians know, the diagnosis of ADHD encompasses a wide range of clinical presentations, from the distracted day-dreamy child to the exceptionally impulsive hyperkinetic teen. This clinical heterogeneity is a major challenge for imaging studies, particularly those with small sample sizes—different clinical presentations are unlikely to have identical underlying neural substrates. This source of heterogeneity is compounded by the fact that different study centers often use different scanners, imaging protocols, and analytic approaches.
One strategy for dealing with some of this heterogeneity is to combine the data from multiple studies, thus providing a quantitative summary that will highlight the more robust ADHD-associated differences (Figure 1). One meta-analysis incorporated cross-sectional data from 1713 individuals with ADHD and 1529 unaffected controls and found smaller subcortical structures in patients with ADHD compared with controls, more pronounced in childhood than adulthood.1
A similar collaborative effort used longitudinal imaging data from four cohorts to chart diagnostic differences in the growth of the cerebellum, a pivotal structure in movement, cognition, and emotion.2 Findings indicate that across these cohorts, the ADHD group showed slower growth of cerebellar white matter in early childhood, but faster growth in late childhood. Other meta-analyses have considered the white matter tracts connecting different brain regions and report focal alterations to the corpus callosum and other association tracts.3,4
Several key points emerge when considering these large, meta-analytic studies. The neural differences between youths with ADHD and youths without, while highly significant are associated with small to medium effect sizes. This means that although the distributions of a given brain feature in the ADHD and comparison groups are shifted apart, the distributions still overlap substantially.
These effect sizes are ubiquitous in psychiatric imaging and limit the application of neuroimaging to the individual. Nonetheless, such meta- analytic findings can give powerful insights into neurobiology, particularly when contrasts are drawn across diagnoses. For example, comparative meta-analyses find that while ADHD is associated with decreased volume and hypoactivation during inhibitory processing in the putamen and insula, obsessive compulsive disorder shows the reverse.5 Such dissociations, emerging through the meta-analyses on thousands of subjects, are particularly powerful pointers to key neural circuits in different disorders.
Dr Shaw is an Earl Stadtman Investigator, Neurobehavioral Research Section, Social and Behavioral Research Branch, National Human Genome Research Institute, NIH; Adjunct Faculty National Institute of Mental Health, Bethesda, MD. Dr Shaw reports no conflicts of interest concerning the subject matter of this article.
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