抑郁症的脑功能异常:来自静息态功能磁共振成像的证据

Depression Brain Dysfunction: Evidence from a Local Functional Connectivity Methods

静息态功能磁共振成像是指在静息状态下测量的BOLD信号,即受试者安静地躺在扫描仪中,不给受试者任何特定的任务,受试者也不用做任何反应,此时受试者的大脑活动处于自发状态。通过使用该技术可以为抑郁症发作的临床现象提供神经影像学依据,以期为将来抑郁症的治疗提供生物标记。因此,本文综述了大量抑郁症患者在静息态脑功能方面的差异研究,发现了单、双相抑郁症,首、复发抑郁症,早发性、晚发性抑郁症,难治、非难治性抑郁症等不同类型的抑郁症在包括局部一致性(Re Ho)和低频振幅(ALFF)在内的功能分化以及包括功能连接密度(FCD)、功能同伦(VMHC)、复杂网络(Complex Network)和ROI功能连接在内的功能整合两大指标的改变。

Resting -state functional magnetic resonance imaging is the spontaneous neural activity in the absence of external information input and output conditions of the brain, the local functional connectivity based on resting state of depression for the study of the characteristics of spontaneous neural activity and brain function changes of great significance. This paper reviews a number of studies, and found the change including local consistency （ReHo） and low frequency amplitude （ALFF） functional differentiation, and includes functional connection density （FCD）, whole brain symmetry voxel homeomorphism connectivity （VMHC）, Complex networks （Complex Network） and integration of functions of ROI function connection. Based on simple local connection method can provide an important basis for the early detection and treatment of clinical depression of brain function. Future connections and functions connected by a comprehensive understanding of the anatomical basis of the organizational structure will be resting brain research and its functional connection status signal characteristics and prediction, diagnosis and treatment of diseases combined to achieve its clinical value. In addition, early clinical diagnosis based on the patient＇s medical history and clinical symptoms were highly subjective, it not only cannot achieve early diagnosis and early treatment, but also makes an objective evaluation of drug efficacy to be a problem. To seek early diagnosis and evaluation of drug efficacy objective quantitative brain disease bio-markers, we use multi-modality medical imaging technology, combined with machine learning methods and pattern recognition technology, in many ways to understand the structure and function of the brain changes in the brain caused by brain disease and these findings apply to early diagnosis of brain diseases. The birth of a human brain imaging technology for the first time in the history of science can be directly and noninvasive way to see neural activity in the brain. Meanwhile, brain imaging has become indispensable in today＇s various neurological disease diagnosis tool. Clinically, brain imaging for the diagnosis and treatment of brain disorders has important significance. Therefore, through the use of a variety of functions for local function and brain image recognition technology index, more comprehensive and more accurate phenomenon of abnormal activity in patients with specific brain regions can be reflected. As a result, this can provide standard for early identification of depression. Above all, we want to more in-depth analysis and research method of resting state functional connectivity, and pay attention to it and the comprehensive utilization of a variety of emerging technologies, realize the value of its clinical application.