UNC researchers conducted a study to image neural activity related to cognitive flexibility and uncover differences in brain activity between children with ADHD and those who did not. The findings, published in the journal Molecular Psychiatry, could help clinicians with diagnosing ADHD in children as well as monitoring the severity of the disorder and treatment success.

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(Photo: Caleb Woods/Unsplash)
A GIrl covering her face

Cognitive Flexibility Function

The researchers wanted to learn what happens in the brain when executive function, particularly cognitive flexibility, is impaired. Lin and colleagues examined the neural flexibility of 180 children with ADHD and 180 normally developing children using functional magnetic resonance imaging (fMRI).

Cognitive flexibility varies from one person to another. Some people are cognitively flexible, while some are not. In some ways, it's just the luck of the genetic draw. However, a person can enhance cognitive flexibility once inflexibility is recognized.

One example of being cognitively flexible is when a person starts dinner by letting the onions simmer, texts a friend, and returns without burning the onions. Another instance is when switching communication styles between a child and an adult. Even in solving a problem, cognitive flexibility also helps. For example, when you realize you don't have enough onions to make dinner, you will need to come up with a different strategy. It is a part of the human executive function, including remembering things and exercising self-control. In some cases, poor executive function indicates ADHD in children and adults.

Children with ADHD struggle to control their actions and attention, impacting their academic achievement and social functioning. Notably, these symptoms frequently continue throughout adulthood. The current ADHD diagnosis is based primarily on behavioral measures after symptoms appear. Furthermore, clinical diagnostic procedures may be subjective, influencing diagnostic accuracy. Thus, techniques capable of detecting ADHD early and objectively may provide an opportunity for early intervention, perhaps reducing long-term consequences.

The advancement of machine learning methods has given rise to the possibility of addressing these difficulties. It is possible to distinguish participants with ADHD from normally developing children (TDC) and, more importantly, predict treatment outcomes by combining neuroimaging data and machine learning approaches.

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Cognitive Flexibility in ADHD Research Findings

According to Weili Lin, Ph.D., the study's senior author, the researchers focused on MR-derived neural flexibility, which is assumed to underpin cognitive flexibility, or the ability to switch between mental processes selectively. The ADHD group had significantly lower neural flexibility at the entire brain and sub-network levels, particularly in the default mode, attention-related, executive function, and main networks.

The researchers also discovered that children with ADHD who were given medication had much greater brain flexibility than children with ADHD who were not given medication.

The team could also predict ADHD severity using clinical markers of symptom severity. They believe that their findings show that neural flexibility has the potential clinical utility of identifying children with ADHD and monitoring treatment responses and the severity of the problem in individual children. Through the study, the researchers discovered that they could use fMRI to detect changes in neuronal flexibility across entire brain areas between children with ADHD and traditionally developing children.

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