Diagnostic utility of brain activity flow patterns analysis in attention deficit hyperactivity disorder

Area of Science:

• Neuroscience
• Clinical Psychology
• Biomedical Engineering

Background:

• Previous research indicated Brain Network Activation (BNA) may aid in diagnosing attention deficit hyperactivity disorder (ADHD).
• This study validates an advanced BNA methodology on a larger adult cohort with and without ADHD.

Purpose of the Study:

• To assess the diagnostic capability of an advanced Brain Network Activation (BNA) methodology in adults with and without ADHD.
• To evaluate the utility of BNA in objectively identifying electrophysiological changes associated with ADHD.

Main Methods:

• Recruited unmedicated adults (18-55 years) diagnosed with or without ADHD.
• Collected electroencephalography (EEG) data during a Go/NoGo response inhibition task.
• Applied spatio-temporal BNA analysis to EEG data and used machine learning for classification.

Main Results:

• BNA demonstrated high discriminative capacity between ADHD patients and controls.
• Achieved high AUC, specificity, and sensitivity in differentiating groups during Go and NoGo conditions.
• BNA scores provided insights into cortical connectivity and brain states.

Conclusions:

• BNA methodology effectively differentiates ADHD from healthy controls based on functional brain connectivity.
• BNA serves as a valuable tool to augment clinical ADHD evaluations with objective electrophysiological data.
• Findings support a network-based approach for studying ADHD.