Distinct neural signatures detected for ADHD subtypes after controlling for micro-movements in resting state functional connectivity MRI data

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.

Altered intrinsic organisation of brain networks implicated in attentional processes in adult attention-deficit/hyperactivity disorder: a resting-state study of attention, default mode and salience network connectivity

“…It is important to note that previous studies have suggested that brain network connectivity alterations may be differentially related to different subtypes of ADHD [68,69]. However, due to the fact that the current ADHD sample included only 6 inattentive type participants, we were unable to reliably investigate this aspect.…”

Double-dissociation between the mechanism leading to impulsivity and inattention in Attention Deficit Hyperactivity Disorder: A resting-state functional connectivity study

“…Also, whole brain voxel-based analyses revealed decreased entropy (Sokunbi et al 2013) and decreased amplitude of low-frequency fluctuation (Zang et al 2007;An, Cao, Sui, et al 2013) in the frontal and the occipital lobes. These inconsistencies are likely to be due to a combination of methodological factors, including the method of analysis employed, micro-movements (Fair et al 2012), variability in the subtype diagnosis and the age range of subjects. The small size of clinical samples has also been a significant limitation of the majority of imaging studies of ADHD to date.…”

Inter-hemispherical asymmetry in default-mode functional connectivity and BAIAP2 gene are associated with anger expression in ADHD adults

“…From a neuroimaging viewpoint, compelling evidence points to rather large-scale abnormalities in network organization in ADHD (Sergeant et al, 2006;Konrad and Eickhoff, 2010;Cao et al, 2013), affecting both functional (Cocchi et al, 2012;Colby et al, 2012;Fair et al, 2012;Tomasi and Volkow, 2012;Cao et al, 2013;Di Martino et al, 2013) and structural (Cao et al, 2013;Hong et al, 2014) connectivity. Moreover, an abnormal hemispheric asymmetry of brain structure and function was also consistently reported in ADHD (Dennis and Thompson, 2013;Shang et al, 2013;Cao et al, 2014;Hale et al, 2014Hale et al, , 2015Keune et al, 2015;Silk et al, 2015), suggesting a possible neurodevelopmental scenario for this disorder.…”