Abstract
In recent years, there has been growing enthusiasm that functional magnetic resonance imaging (MRI) could achieve clinical utility for a broad range of neuropsychiatric disorders. However, several barriers remain. For example, the acquisition of large-scale datasets capable of clarifying the marked heterogeneity that exists in psychiatric illnesses will need to be realized. In addition, there continues to be a need for the development of image processing and analysis methods capable of separating signal from artifact. As a prototypical hyperkinetic disorder, and movement-related artifact being a significant confound in functional imaging studies, ADHD offers a unique challenge. As part of the ADHD-200 Global Competition and this special edition of Frontiers, the ADHD-200 Consortium demonstrates the utility of an aggregate dataset pooled across five institutions in addressing these challenges. The work aimed to (1) examine the impact of emerging techniques for controlling for “micro-movements,” and (2) provide novel insights into the neural correlates of ADHD subtypes. Using support vector machine (SVM)-based multivariate pattern analysis (MVPA) we show that functional connectivity patterns in individuals are capable of differentiating the two most prominent ADHD subtypes. The application of graph-theory revealed that the Combined (ADHD-C) and Inattentive (ADHD-I) subtypes demonstrated some overlapping (particularly sensorimotor systems), but unique patterns of atypical connectivity. For ADHD-C, atypical connectivity was prominent in midline default network components, as well as insular cortex; in contrast, the ADHD-I group exhibited atypical patterns within the dlPFC regions and cerebellum. Systematic motion-related artifact was noted, and highlighted the need for stringent motion correction. Findings reported were robust to the specific motion correction strategy employed. These data suggest that resting-state functional connectivity MRI (rs-fcMRI) data can be used to characterize individual patients with ADHD and to identify neural distinctions underlying the clinical heterogeneity of ADHD.
Highlights
Brain imaging has increasingly become a useful tool in modern medicine
Given prior demonstrations of increased micro-movements in pediatric samples and the potential for motion artifact to contribute to estimates of functional connectivity (Power et al, 2012a; Satterthwaite et al, 2012; Van Dijk et al, 2012), we first provide a comprehensive examination of micro-movements in the Attention Deficit Hyperactivity disorder (ADHD)-200 sample, as well as the impact of various correction strategies
Traditional movement measurements relate to the six directional adjustments required to align any given frame within a blood oxygen leveldependent (BOLD) fMRI run to a reference frame within that run
Summary
Brain imaging has increasingly become a useful tool in modern medicine. Most notably, magnetic resonance imaging (MRI) has emerged as an accurate and reliable approach to identifying abnormalities characteristic of congenital, neoplastic, ischemic, inflammatory, metabolic, and infectious processes in the brain. Rs-fcMRI can be used during sleep as well as during sedation (Fukunaga et al, 2006, 2008; Vincent et al, 2007; Greicius, 2008; Horovitz et al, 2008); it yields consistent results across subjects, scans, and days (van de Ven et al, 2004; Damoiseaux et al, 2006; Shehzad et al, 2009; Van Dijk et al, 2010), and rs-fcMRI results are remarkably reliable across imaging centers (Biswal et al, 2010) These features make rs-fcMRI an attractive measure for translational and clinical applications. As highlighted in the ADHD-200 competition (ADHD-200-Consortium, 2012), and this special edition highlighting the work of the competitors, the race for these sorts of applications is currently underway (ADHD-200-Consortium, 2012)
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