Non-invasive BCI and Application Verification for Depressed People

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:

1. Traditional medication with SSRIs. MDD patients will be give different SSRIs medication and undergo a two-week treatment, after which the above assessments will be done again to evaluation the efficacy and side effects of the current treatment. For MDD patients with anhedonia, other medication can be considered such as Voxetine and Bupropion. 2. rTMS combined with traditional SSRIs medication. The current brain regions chosen for rTMS include dorsolateral pre-frontal cortex. In this part, the study tends to find out new potential brain regions suitable for physical treatment in MDD patients. The considered brain regions include orbitofrontal cortex, cerebellum and others. It uses a classic 8-shaped coils, butterfly coils, deep coils, etc., neural navigation to locate stimulation targets. 3. Treatment based on neurobiological feedback. In this kind of treatment, MDD patients are treated with neurobiological feedback and will be monitored by EGG to catch unique and specific brain waves that may considered only found in MDD patients. This treatment involves using different psychological paradigms including classic cognitive research paradigms to evaluate the outcome of neuron-training and cognitive function after treatment.

Other technologies used in this study includes:

1. Functional Magnetic Resonance Imaging. Brain images will be captures during different functional tasks such as emotional matching, Monetary Incentive Delay Task ( MID ). These images will be further analyzed to figure out the neuro-mechanism of MDD. We will be using 3T Siemens PRISMA, collecting data of rs-fMRI、DTI、T1、T2 and fMRI. 2. Electroencephalography. In this part, the investigators will be using the DSI-24 wireless dry electrode EEG system. Each subject will undergo EEG collection experiments, at least collecting EEG data in a resting state (with eyes closed and open). 3. Eye movement detection. Eye movement will be traced using Tobii Pro Spectrum. 4. Functional Near-Infrared Spectroscopy. Patients will perform different tasks under the monitoring of a portable fNIRS device called Nirsport2 wireless wearable NIRS imaging system. It consists of a 8-channel LED illuminator and 8-channel active sensor for fiberless optical detection. During the tasks, the device will provide the value and changes in the level of oxyhemoglobin and deoxygenated hemoglobin observed in the subjects. 5. Magnetoencephalogram. MEG is a completely non-invasive function detection technique, widely used in the development and research of brain function and the clinical diagnosis of brain diseases. MEG uses a sensitive magnetic sensor SQUID (Superconducting Quantum Interferometer), which is placed around the head to measure the abnormally weak magnetic field generated by neuronal activity. The detected magnetic signal data will then be analyzed and processed by a computer and superimposed on magnetic resonance imaging (MRI). Through software 3D imaging, the results can be more intuitive, making the MEG have extremely high temporal and spatial resolution.

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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