Neurofeedback for autism spectrum disorder: Current evidence, challenges, and future directions
Year: 2026
Type: editorial
Abstract: Neurofeedback therapy (NFT) has emerged as a promising noninvasive intervention for autism spectrum disorder (ASD), targeting core symptoms such as social communication deficits and emotional dysregulation. This editorial synthesizes findings from recent studies, including Wang et al ’s retrospective analysis (2025), which reported improvements in Social Responsiveness Scale and Aberrant Behavior Checklist scores following NFT combined with conventional therapy. Mechanistically, NFT may modulate prefrontal gamma-band activity, enhances neuroplasticity in social brain networks (e.g., default mode network, a brain network involved in social cognition), and optimizes cognitive processing via event-related potential changes (e.g., shortened P300 latency). Emerging trends include hybrid approaches (e.g., NFT with repetitive transcranial magnetic stimulation and artificial intelligence-driven protocols). However, challenges persist in protocol standardization, long-term efficacy validation, and biomarker identification. Future research must prioritize large-scale randomized trials, neuromarker discovery, and individualized protocols to establish NFT as a viable component of precision psychiatry for ASD.
Source: World Journal of Psychiatry
Authors: Yan Zhang, Jun-Jie Wang, Hao-Yu Xing, Juan Yan
Institutions: Hangzhou Seventh Peoples Hospital, Zhejiang University
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: diamond
Award: G5034973753
OpenAlex ID: W7126053847