A Machine Learning Approach for Predicting Transcranial Direct Current Stimulation Treatment Outcomes in Adolescents With Autism Spectrum Disorders

What this Trial Is About

Researchers are studying adolescents and young adults with autism spectrum disorder (ASD), a condition marked by difficulties in communication, social skills, and repetitive behaviors. The study aims to understand how a brain stimulation technique called transcranial direct current stimulation (tDCS) might reduce symptoms like anxiety and impulsivity. The research also seeks to use brain activity data and clinical information to predict who will respond well to this treatment. Participants will receive active tDCS for 10 sessions over two weeks, one session per day on working days. During each 20-minute session, they will perform exercises designed to improve processing speed and executive function while receiving brain stimulation. After treatment, participants will be classified as responders or non-responders based on improvements in social responsiveness scores. Throughout the study, participants will undergo various assessments including behavioral scales, cognitive tests, and neurophysiological measurements at the start and after the treatment period. Researchers will track changes in social communication, repetitive behaviors, and brain function. This will help determine the effects of tDCS and identify characteristics that predict treatment response, with the total study duration extending up to the final follow-up in 2026.

A Machine Learning Approach for Predicting tDCS Treatment Outcomes of Adolescents With Autism Spectrum Disorders