Brain-computer-interface-based intervention re-normalizes brain functional network topology in children with...

Area of Science:

• Neuroscience
• Child Psychology
• Biomedical Engineering

Background:

• Attention Deficit/Hyperactivity Disorder (ADHD) in children, particularly inattentive symptoms, presents a significant challenge.
• Brain-computer interface (BCI) systems offer a novel approach for attention training.
• Understanding the neurobiological underpinnings of BCI intervention effects is crucial.

Purpose of the Study:

• To investigate the topological changes in large-scale brain functional networks following an 8-week BCI-based attention training program in boys with ADHD.
• To correlate these network alterations with behavioral improvements in attention and internalizing symptoms.

Main Methods:

• Utilized resting-state functional magnetic resonance imaging (fMRI) to assess brain functional connectivity.
• Employed graph theory analysis to examine network properties like degree centrality, clustering coefficient, and closeness.
• Compared brain network organization between an intervention group (ADHD-I) and a non-intervention group (ADHD-NI).

Main Results:

• The ADHD-I group showed reduced inattention symptoms post-intervention.
• Significant differences in brain network reorganization were observed between ADHD-I and ADHD-NI groups.
• ADHD-I group exhibited decreased local functional processing in task-positive networks, especially the salience/ventral attention network (SVN), which correlated with symptom reduction.

Conclusions:

• BCI-based attention training can effectively reorganize brain functional networks in children with ADHD.
• The intervention promotes a shift towards more random network configurations, normalizing salience network processing.
• These findings highlight the potential of BCI for ADHD treatment and suggest future longitudinal studies for brain maturation.