A new study significantly strengthens the case that attention-deficit/hyperactivity disorder (ADHD) brains are structurally unique, thanks to a new scanning technique known as the traveling-subject method. It isn't down to new technology – but better use of it.
A team of Japanese scientists led by Chiba University has corrected the inconsistencies in brain scans of ADHD individuals, where mixed results from magnetic resonance imaging (MRI) studies left researchers unable to say for certain whether neurodivergency could be identified in the lab. Some studies reported smaller gray matter volumes in children with ADHD compared to those without, while others showed no difference or even larger volumes. With some irony, it's been a gray area for diagnostics and research.
Here, the researchers employed an innovative technique called the traveling-subject (TS) method, which removed the "technical noise" that has traditionally distorted multi-site MRI studies. The result is a more reliable look at the ADHD brain – and a clearer picture of how the condition is linked to structural differences.
Essentially, different hospitals, clinics or research facilities use different scanners, with varying calibration, coils and software. When researchers pool data from multiple sites, they risk confusing biological variation with machine error. Statistical correction tools exist – like the widely used “ComBat” method – but these can sometimes overcorrect, erasing real biological signals along with noise. That’s a big problem for conditions like ADHD, where the predicted structural differences are subtle – so if the measurement noise is louder than the biological effect, results end up contradictory.
The TS method takes a more hands-on approach – basically making the scans uniform across a study group. The researchers recruited 14 non-ADHD volunteers and scanned each of them across four different MRI machines over three months. Since the same person’s brain doesn’t change in that short window, any differences between scans are from the machines themselves. This template served as a sort of neurotypical control, which allowed the researchers to further investigate a much larger dataset from the Child Developmental MRI database, which included 178 "typically developing" children and 116 kids with ADHD.
What they found was that once the scanner bias was removed, the results became much clearer. Children with ADHD showed smaller brain volumes in the frontotemporal regions compared to their typically developing peers. These brain areas are central to attention and information processing, emotional regulation, executive function and decision-making – all markers of ADHD.
"Despite these promising results, this study had some limitations," the team noted in the paper. "The study sample may not fully represent the broader population of children with ADHD. The participants were drawn from specific geographical regions and clinical settings, which could limit the generalizability of the findings to other populations. Additionally, this study only examined the brain structure characteristics in children with ADHD elucidated using harmonization."
While the new findings will need to be validated on a larger scale, the TS method could help with earlier diagnosis of ADHD and personalized treatments that track how therapies affect brain structure. It could also remove some of the stigma associated with ADHD, offering black-and-white, measurable evidence that neurodivergent brains are different – neurobiological evidence that isn't based on behavior or self-reporting.
The research also shows that, like any biology student who has struggled with experiment design will know, accurate data is all about getting the methods of testing right.
"This study demonstrated the effectiveness of the TS method in correcting measurement bias in multi-site MRI studies involving children with ADHD," the researchers added. "These findings highlight significant structural differences in the brains of patients with ADHD, particularly in the middle temporal gyrus, and underscore the importance of using robust harmonization techniques to improve the reproducibility and accuracy of neuroimaging research."
The study was published in the journal Molecular Psychiatry.
Source: Chiba University
