Functional connectivity in ADHD children doing Go/No-Go tasks: An fMRI systematic review and meta-analysis

Sihyong J Kim1, Onur Tanglay1,2, Elizabeth H N Chong3

  • 1Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia.

Translational Neuroscience
|February 27, 2024
PubMed

Insights

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. This study found less default mode network activation in children with ADHD during Go/No-Go tasks compared to controls.

Area of Science:

  • Neuroscience
  • Developmental Psychology
  • Medical Imaging

Background:

  • Attention deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder characterized by impaired behavioral inhibition and sustained attention.
  • Functional magnetic resonance imaging (fMRI) and the Go/No-Go task have identified brain regions like the supplementary motor area and prefrontal cortex in ADHD.
  • Coordinate-based meta-analysis using Activation Likelihood Estimation (ALE) offers an objective method to synthesize fMRI data for understanding brain networks in ADHD.

Purpose of the Study:

  • To conduct a coordinate-based meta-analysis of Go/No-Go task-based fMRI studies in children and adolescents with ADHD.
  • To investigate brain network architecture and connectivity differences in ADHD using quantitative techniques.
  • To objectively summarize neurobiological correlates of ADHD during inhibitory control tasks.

Main Methods:

  • Selected Go/No-Go task-based fMRI studies involving children and adolescents.
  • Collected coordinates of activation foci and generated Activation Likelihood Estimates (ALE) with specific statistical thresholds (voxel-level p < 0.001, cluster-level p < 0.05).
  • Matched ALEs to canonical brain networks from the Human Connectome Project, analyzing 14 studies with 457 participants.

Main Results:

  • No significant convergence of Go/No-Go related brain activation was found in ADHD groups.
  • Three significant ALE clusters were detected for controls or when ADHD had less activation than controls, primarily in the default mode network (DMN).
  • Network analysis indicated reduced DMN, dorsal attention network, and limbic network activation in ADHD children compared to controls.

Conclusions:

  • ADHD in children is associated with altered activation within specific brain networks, particularly the DMN, during inhibitory control tasks.
  • The findings suggest network-level differences in ADHD, with less extensive activation in key attention and self-referential networks.
  • Potential heterogeneity in study samples and experimental paradigms may influence ALE results; further research on hemispheric asymmetry in ADHD is recommended.