An Effective Neurofeedback Intervention to Improve Social Interactions in Children with Autism Spectrum Disorder

Area of Science:

• Neuroscience
• Developmental Psychology
• Clinical Psychology

Background:

• Autism spectrum disorder (ASD) presents challenges in behavior, cognition, and emotion regulation.
• Social interaction deficits are a core feature of ASD, impacting daily life.
• Neurofeedback training (NFT) is an emerging therapeutic approach for neurodevelopmental disorders.

Purpose of the Study:

• To investigate the efficacy of two NFT paradigms for improving behavior, cognition, and emotion regulation in children with ASD.
• To compare bidirectional EEG mu suppression and enhancement with standard mu enhancement.
• To assess the impact of NFT on electrophysiological, emotional, and behavioral outcomes.

Main Methods:

• Thirteen children with ASD participated in 16 NFT sessions.
• NFT utilized a game-based approach with feedback on imitation and emotional responsiveness.
• EEG mu rhythm (8-12 Hz over somatosensory cortex) was trained using bidirectional or enhancement-only methods.

Main Results:

• Children successfully learned to control their mu rhythm with both NFT methods.
• Significant improvements were observed in electrophysiology (increased mu suppression).
• Enhanced emotional responsiveness (emotion recognition, spontaneous imitation) and behavioral regulation were noted.

Conclusions:

• NFT paradigms show promise in improving core deficits in children with ASD.
• The studied NFT approaches enhance electrophysiological markers associated with social cognition.
• NFT positively impacts emotional responsiveness and everyday behavior, facilitating social interactions.