Introduction to the Meta-analysis method of functional magnetic resonance imaging research and the exploration of its application in the field of acupuncture.

Abstract

In recent years, the number of functional magnetic resonance imaging (fMRI) research in acupuncture grows increasingly. However, due to the differences in acupoint selection, acupuncture technique and sample size, the problems get more prominent in terms of the diverse results and the lack of common rules of acupuncture among researches. By taking the fMRI research for post-stroke motor dysfunction (PSMD) treated with acupuncture as the example, this paper introduces the fMRI Meta-analysis technology for integrating the relevant research results and extracting the common rules, namely image-based Meta-analysis (IBMA) and coordinate-based Meta-analysis (CBMA). Considering the higher feasibility of CBMA, three available CBMA methods are explained specially, including activation likelihood estimation (ALE), kernel density analysis (KDA), and seed-based d mapping (SDM). Focusing on the precautions and operation procedure of CBMA, the review is conducted systematically on the type of fMRI research, task design, analytical method, and the thinking integrity of fMRI Meta-analysis, and the review findings are collated in charts. It aims to assist readers to understand the abstract and complex theories and practical information of this technology efficiently, conveniently and systematically, and hopes to provide the references for the future learning and the application.