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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.
Full description
This study aims to establish a BCI regulation scheme and system for individuals with mdd, and to conduct validation for this application. Four more detailed contents are being designed, including 1. providing biological markers in brain regions, circuits, and networks that are probably related to MDD, 2. assessment models of the state of brain and multivariate signal mapping models, 3. virtual regulation paradigms, evaluations on the effect of the regulation , and 4. multimodal information collection and regulation software and hardware technologies.
Shanghai Mental Health Center, as the sponsor institution, tends to recruit MDD patients from daily outpatient service. The paticipants' personal information will be noted and then the patients will undergo different assessment on their level of depression, anxiety, anhedonia, manic state, cognitive status, effect and side effects of the current treatment, and their biological rhythm, sleep, quality of life, etc. Peripheral blood will be drawn for different potential biomarkers, as well as multimodal information such as EEG, eye movement, magnetic resonance imaging, magnetoencephalogram, fNIRS, and etc. Then compare the following laboratory indicators between depressed patients and healthy individuals such as differences in the concentration and gene expression of peripheral blood inflammatory factors, oxidative stress indicators, brain-derived neurotrophic factors, brain imaging, electrophysiology, blood oxygen and etc. The work above is to obtain specific neurobiological markers of MDD.
Intervention measures are as follows:
Other technologies used in this study includes:
MDD patients will be divided into different treatment gourds based on theirs condition and whether the chosen treatment would be the most suitable for them. All individuals will undergo the above assessments to establish a comprehensive, multimodal information data base, and finally after comparing the outcome before and after the treatment, the study tries to find out new and effective measures and validate their feasibility.
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400 participants in 5 patient groups
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Qinyu Lv, chief physician; Zhenghui Yi, chief physician
Data sourced from clinicaltrials.gov
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