[Pattern of acupoint selection based on complex network analysis technique]

Abstract

To analyze the global structural models of point prescription in acupuncture therapy, and to provide new insights for acupoint selection based on syndrome differentiation. Taking prescriptions in the commonly used textbooks as the resources, a directed network of point prescription according to syndrome differentiation was constructed. The network was visualized with Pajek 1.25, the linkage distributions of points and symptoms were analyzed with Matlab 7.0. The result showed that there existed 1 635 combinations between 233 syndromes and 232 acupoints. The linkages of symptoms and selection of acupoints confirmed to the feature of random distribution with 5 points for each symptom in average. And the linkages obeyed a power-law distribution, which indicates that most symptoms can be treated by selecting a few points. Thus, it was concluded that complexity can be found in the global structural of relation between syndrome differentiation and acupoint selection. The selection of acupoints for every symptom and the matching of symptoms for every acupoint had different distribution patterns. The former obeyed a random pattern while the latter had a scale-free property. The complex network analysis is promised to be an available tool for researches on acupuncture prescriptions.