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[Mechanisms and outcome evaluation of neurofeedback in post-traumatic stress disorder intervention].

October 25, 2026pubmed logopapers

Authors

Huang K,Ding P,Luo R,Li T,Zhao L,Su L,Xu J,Fu Y

Affiliations (3)

  • Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, P. R. China.
  • Brain Cognition and Brain-computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming 650500, P. R. China.
  • Faculty of Science, Kunming University of Science and Technology, Kunming 650500, P. R. China.

Abstract

Patients with post-traumatic stress disorder (PTSD) still face challenges such as limited treatment response in some cases and substantial inter-individual variability when receiving existing interventions. Neurofeedback (NFB), as a closed-loop neuromodulation approach based on brain-computer interface (BCI), can guide patients to regulate abnormal neural activity patterns by providing real-time feedback on brain activity features, and therefore shows potential for PTSD rehabilitation. This paper reviews the regulatory mechanisms of NFB on the prefrontal-limbic emotion regulation circuit and the dysregulated states of the default mode network, salience network, and central executive network. It compares three major modalities, including electroencephalography, real-time functional magnetic resonance imaging, and functional near-infrared spectroscopy, in terms of feedback targets, spatiotemporal resolution, and clinical applicability. Based on a multidimensional evaluation framework composed of clinical scales, neurophysiological indicators, and functional recovery indicators, this paper further discusses the clinical positioning of NFB relative to first-line treatments and the potential synergistic mechanisms of its combined application with psychological interventions. Current studies still face limitations such as insufficient control design and a lack of standardized training parameters. Future research should integrate individualized target selection and machine learning-based modeling to promote the standardized application of NFB.

Topics

NeurofeedbackStress Disorders, Post-TraumaticBrain-Computer InterfacesJournal ArticleReviewEnglish Abstract

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