Artificial Intelligence-Driven Transcranial Magnetic Stimulation(TMS) for Autism Spectrum Disorder

Abstract

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by impairments in social communication, repetitive behaviors, sensory processing abnormalities, and variable cognitive deficits. Despite significant advances in behavioral therapies and pharmacological interventions, effective treatments capable of directly modulating dysfunctional neural networks remain limited. Transcranial Magnetic Stimulation (TMS) has emerged as a promising non-invasive neuromodulation technique that can alter cortical excitability, enhance neuroplasticity, and potentially improve cognitive and behavioral outcomes. Simultaneously, recent developments in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Explainable Artificial Intelligence (XAI), Reinforcement Learning (RL), and Digital Twin technologies have created new opportunities to personalize TMS protocols using multimodal patient data, including structural and functional neuroimaging, electroencephalography (EEG), behavioral assessments, genetic information, and longitudinal clinical outcomes.