Title :
Granger causality analysis in the neural mass model
Author :
Liang, Li ; Deng, Bin ; Wang, Jiang ; Wang, Ruofan ; Wei, Xile ; Yu, Haitao ; Qin, Yingmei ; Yang, Chen
Author_Institution :
School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072
Abstract :
The study of brain functional connectivity has become an important aspect of neuroscience. With the development of different methods to detect functional connectivity, the neural mass model based on physiology provides a basis for validating methods. As a popular method of discovering functional connectivity, Granger causality is applied to many fields of neurophysiology, but the mapping between Granger causality and coupling strength of neural mass model is unclear. To explore this relationship, we make a simulation to change the coupling strength of a double-column mass model, and calculate the corresponding Granger causality value. It is found that Granger causality and coupling strength has a relationship but nonlinear.
Keywords :
Analytical models; Brain modeling; Couplings; Electroencephalography; Mathematical model; Sociology; Statistics; Granger causality; coupling strength; neural mass model;
Conference_Titel :
Control Conference (CCC), 2015 34th Chinese
Conference_Location :
Hangzhou, China
DOI :
10.1109/ChiCC.2015.7260356