Resting-state EEG Connectivity in Young Children with ADHD

Area of Science:

• Neuroscience
• Developmental Psychology
• Child Psychiatry

Background:

• Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder impacting children.
• Early childhood is critical for intervention, but ADHD diagnosis can be unstable in this age group.
• Neural connectivity disruptions are known in older children with ADHD, but less is known about early childhood.

Purpose of the Study:

• To investigate network connectivity as a potential neural correlate for ADHD diagnosis in early childhood.
• To explore if brain network efficiency differs between young children with and without ADHD.
• To examine the relationship between neural connectivity and ADHD symptom severity in preschoolers and early school-aged children.

Main Methods:

• Electroencephalography (EEG) data collected from 52 children with ADHD and 77 typically developing controls (ages 3-7).
• EEG data down sampled and analyzed using Independent Component Analysis (ICA) and graph theoretical methods.
• Connectivity measured by synchrony between electrode time series; global efficiency calculated to assess information transfer.

Main Results:

• Increased global efficiency, suggesting a hyper-connected neural network, was associated with higher inattentive symptom severity in children.
• This association remained significant after controlling for age, IQ, socioeconomic status, and internalizing symptoms.
• Findings indicate a link between hyper-connectivity and ADHD symptom severity in early childhood.

Conclusions:

• Increased global efficiency may serve as a neural correlate for ADHD symptom severity in early childhood.
• These results extend previous findings of altered neural connectivity in older children with ADHD to a younger age group.
• Neural network connectivity shows promise as an early indicator for ADHD.