Innovation Series: Advanced Science (ISSN 2938-9933, CNKI Indexed)

Applications of Brain-Computer Interfaces in Neurodegenerative Diseases

Yarong Xue¹, Bingcang Yan^2,*

¹School of Clinical Medicine, Shaanxi University of Chinese Medicine, Xianyang 712046, Shaanxi, China

²Xi'an Hospital of Encephalopathy Affiliated to Shaanxi University of Chinese Medicine, Xi'an 710000, Shaanxi, China

Corresponding author: Bingcang Yan (mexycb@126.com)

Abstract: Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS) are three highly prevalent, severely disabling neurodegenerative disorders. They share core pathological hallmarks: progressive degeneration and apoptosis of central neurons, persistent disconnection of intracerebral neural networks, which gradually impair memory, motor function, language, emotion and other core neurological functions. Conventional clinical treatments have notable limitations. Pharmacotherapy can only delay pathological deterioration temporarily and fails to repair damaged neural circuits, accompanied by adverse reactions such as drowsiness, dyskinesia and gastrointestinal injury after long-term administration. Traditional rehabilitation training heavily relies on patients’ active limb movements, making it nearly ineffective for patients with advanced complete disability. Conventional open-loop constant deep brain stimulation (DBS) cannot dynamically adjust stimulation parameters according to real-time brain activity, resulting in insufficient regulatory precision. A brain-computer interface (BCI) establishes a bidirectional information pathway between the brain and external devices independent of muscles and peripheral nerves. By decoding neural signals and delivering multimodal feedback stimuli to form closed-loop neuromodulation, BCIs simultaneously achieve neural repair and functional compensation relying on neural plasticity. This paper stratifies five major BCI systems including EEG, fNIRS, MEG, ECoG and implantable microelectrode arrays by invasion degree. Combined with meta-analyses, multicenter randomized controlled trials (RCTs) and professional expert consensus published in the past five years, we systematically elaborate intervention protocols, clinical efficacy and intrinsic neural mechanisms of various BCIs for AD cognitive impairment, PD motor dysfunction and ALS locked-in syndrome. From hardware performance, clinical standardization, evidence-based research and data ethics four dimensions, we analyze the bottlenecks hindering clinical translation. Prospective directions including multimodal fusion, minimally invasive implantation, home-based adaptive intelligent BCIs and standardized diagnosis-treatment systems are proposed, providing evidence-based references for clinical intervention in neurology and rehabilitation, as well as related engineering and basic neuroscience research.

Keywords: Brain-computer interface; Neurodegenerative diseases; Alzheimer’s disease; Parkinson’s disease; Amyotrophic lateral sclerosis; Neural plasticity; Closed-loop neuromodulation

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