Advances in the Application of Brain–Computer Interface-Based Neurofeedback Training in the Rehabilitation of Patients with Major Depressive Disorder

Junting Liu,1 Lingyu Liu,2 Han Chen,1 Shu Xuan,1 Xinke Leng1 1School of Physical Education, Hunan University, Changsha, Hunan, People’s Republic of China; 2School of Acupuncture, Rehabilitation and Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, People’s Republic of ChinaCorrespondence: Xinke Leng, School of Physical Education, Hunan University, Changsha, Hunan, People’s Republic of China, Email [email protected]: Major depressive disorder is a highly prevalent affective disorder worldwide, and existing pharmacological and psychological treatments continue to demonstrate notable limitations in terms of therapeutic stability, adverse effects, and relapse prevention. Brain–computer interface-based neurofeedback training (BCI‑NFT) guides patients to actively regulate abnormal neural functional states through real‑time feedback of brain activity signals, thereby providing a precise interventional pathway that acts directly at the level of neural function. This narrative review examines the theoretical foundations, neural mechanisms, and clinical application modalities of BCI‑NFT in depression rehabilitation, encompassing advances in both non‑invasive and invasive neurofeedback technologies, diverse combined intervention paradigms, and the application prospects of a concurrent intervention approach integrating wearable BCI technology with aerobic exercise at the interdisciplinary intersection of sports neuroscience and psychiatric rehabilitation medicine. Preliminary evidence suggests that BCI‑NFT may facilitate neural functional recovery in patients with major depressive disorder through three primary mechanisms: remodeling of emotion‑regulation‑related brain regions, correction of aberrant EEG activity patterns, and improvement of large‑scale brain network connectivity; however, given the sample sizes and methodological heterogeneity of existing studies, these conclusions still require further validation through large-scale randomized controlled trials. Nevertheless, the widespread clinical implementation of BCI‑NFT remains constrained by a lack of standardized training protocols, insufficient clarity regarding suitable patient populations, and a paucity of large‑sample clinical data. Future research should, within a precision psychiatry framework and through the integration of multimodal neuroimaging and large‑scale randomized controlled trials, further advance the standardized clinical translation of BCI‑NFT.Keywords: brain–computer interface, neurofeedback training, major depressive disorder, sports neuroscience, neuromodulation, neuroplasticity, psychiatric rehabilitation