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.