Study of 11,000 Children Challenges 2008 ADHD Brain-Delay Finding
Updated
Updated · Livescience.com · May 22
Study of 11,000 Children Challenges 2008 ADHD Brain-Delay Finding
2 articles · Updated · Livescience.com · May 22
A PNAS study using data from more than 11,000 U.S. children found no evidence that ADHD is linked to delayed cortical maturation once sex-specific brain-development patterns were modeled.
The reanalysis suggests the influential 2008 result—built on MRI scans from 223 children with ADHD and a similar control group—was skewed by smaller samples and dropout that overrepresented boys' slower cortical thinning.
Researchers first reproduced the old association in the ABCD dataset, then saw it vanish after accounting for boys' and girls' different thinning rates; separate analyses of boys and girls also found no link.
Follow-up checks in clinically diagnosed ADHD subsets produced similar results, reinforcing the conclusion that cortical thickness is not a reliable biological signature for the disorder.
The finding adds to neuroscience's replication crisis while leaving intact the view that ADHD is a biological, strongly genetic condition—just one still lacking a robust brain-scan marker.
ADHD science was built on boys. How will new research finally reshape diagnosis and treatment for women?
If brain scans can't spot ADHD, what reliable biological markers are scientists hunting for now?
A key brain theory for ADHD is now debunked. What biological explanations are replacing it?
No Reliable Brain Biomarkers for ADHD: Insights from the 2026 PNAS and ABCD Studies
Overview
A major 2026 study published in PNAS used data from the large Adolescent Brain Cognitive Development (ABCD) study, which has tracked over 11,500 U.S. children since 2017, to re-examine the idea that children with ADHD have delayed brain maturation. The findings challenge a long-held belief, showing that earlier conclusions—especially from a 2008 study—may have been due to statistical artifacts. This new evidence is prompting experts to reassess how brain development in ADHD is understood, highlighting the importance of large, robust datasets for drawing reliable conclusions about neurodevelopmental conditions.