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:
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.
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.
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:
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.
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).
Eye movement detection. Eye movement will be traced using Tobii Pro Spectrum.
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.
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.