Non-invasive BCI and Application Verification for Depressed People

Major Depressive Disorder (MDD) is a serious mental illness and public health problem that poses threat to both physical and mental health. According to statistics from WHO, it is estimated that more than 350 million people worldwide suffer from depression, with a prevalence rate of 2.1% in China, which is approximately 30 million people.

At present, due to the lack of neurobiological markers for screening and diagnosing depression, the identification and diagnosis of MDD are based on the judgment of professional doctors, and the treatment mostly relies on clinical symptoms.

In terms of treatment, medication remains the main stream for MDD. Although current methods have certain therapeutic effects, patients still suffer from various side effects and poor cognitive function.In current clinical practice, relying purely on symptomatic diagnosis and treatment is difficult to meet the needs of clinical practice, so there is an urgent need to search for neurobiological markers in depression and develop targeted non-invasive intervention technologies.

This study aims to combine advanced brain imaging technology, digital twin-brain models, multi-source information decoding technology, integrated detection and intervention technology. The target is to create two new types of non-invasive BCI systems that can regulate emotions. One is a intervention BCI system for MDD that is suitable for hospital settings with the purpose of precise physical stimulation, and the other one is an ecological BCI system that regulate emotions and intervene with depression which is suitable for both hospital settings and future family environments.

This study will collect a comprehensive collection of physiological and biochemical indicators from patients with depression and from healthy control groups, as well as multimodal information such as head surface electroencephalography, MRI, and eye movements under different brain states, to personalize the available BCI information of depression related brain regions, circuits, and networks. The study also tries to explore emotional-interactive games that can intervene with depression and build a game data base that is dedicated to MDD. Other goals include designing and establishing two new types of emotional regulation systems, which are precise external physical stimulation intervention and ecological intervention, constructing a BCI regulation system, and conducting application verification to evaluate the regulation effect.