Frontiers in Systems Neuroscience (Feb 2013)

Distinct Neural Signatures Detected for ADHD Subtypes After Controlling for Micro-Movements in Resting State Functional Connectivity MRI Data

  • Damien eFair,
  • Joel T Nigg,
  • Swathi eIyer,
  • Deepti eBathula,
  • Kathryn L Mills,
  • Nico UF Dosenbach,
  • Bradley L Schlaggar,
  • Maarten eMennes,
  • David eGutman,
  • Saroja eBangaru,
  • Jan K Buitelaar,
  • Daniel P Dickstein,
  • Adriana eDi Martino,
  • David N Kennedy,
  • Clare eKelly,
  • Beatriz eLuna,
  • Julie B Schweitzer,
  • Katerina eVelanova,
  • Yu-Feng eWang,
  • Yu-Feng eWang,
  • Stewart H Mostofsky,
  • Stewart H Mostofsky,
  • Francisco Xavier Castellanos,
  • Francisco Xavier Castellanos,
  • Michael P Milham,
  • Michael P Milham

DOI
https://doi.org/10.3389/fnsys.2012.00080
Journal volume & issue
Vol. 6

Abstract

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In recent years, there has been growing enthusiasm that functional 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 A) examine the impact of emerging techniques for controlling for micro-movements, and B) provide novel insights into the neural correlates of ADHD subtypes. Using SVM based 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 rs-fcMRI data can be used to characterize individual patients with ADHD and to identify neural distinctions underlying the clinical heterogeneity of ADHD.

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