Network structure among brain systems in adult ADHD is uniquely modified by stimulant administration

Robert P. Cary, Siddharth Ray, David S. Grayson, Julia Painter, Samuel Carpenter, Leeza Maron, Olaf Sporns, Alexander A. Stevens, Joel T. Nigg, Damien A. Fair

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Current research in connectomics highlights that self-organized functional networks or "communities" of cortical areas can be detected in the adult brain. This perspective may provide clues to mechanisms of treatment response in psychiatric conditions. Here we examine functional brain community topology based on resting-state fMRI in adult Attention-Deficit/ Hyperactivity Disorder (ADHD; n = 22) and controls (n = 31). We sought to evaluate ADHD patterns in adulthood and their modification by short term stimulants administration. Participants with ADHD were scanned one or two weeks apart, once with medication and once without; comparison participants were scanned at one time-point. Functional connectivity was estimated from these scans and community detection applied to determine cortical network topology. Measures of change in connectivity profile were calculated via a graph measure, termed the Node Dissociation Index (NDI). Compared to controls, several cortical networks had atypical connectivity in adults with ADHD when withholding stimulants, as measured by NDI. In most networks stimulants significantly reduced, but did not eliminate, differences in the distribution of connections between key brain systems relative to the control sample. These findings provide an enriched model of connectivity in ADHD and demonstrate how stimulants may exert functional effects by altering connectivity profiles in the brain.

Original languageEnglish (US)
Pages (from-to)3970-3979
Number of pages10
JournalCerebral Cortex
Volume27
Issue number8
DOIs
StatePublished - Aug 1 2017

Keywords

  • ADHD
  • Functional connectivity
  • MRI
  • Resting state
  • Stimulants

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience

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