Change in human brain functional network based on Granger causality analysis

In recent years, the emergence of the fMRI provides a possibility of further exploration for the human brain. The complex workings of the brain are composed of a plurality of brain functional networks. To further explore the change affected by task in human brain functional network, the efficiency of a method of effective connectivity is examined by comparing the two resting state fMRI data before and after a task. Distinguished from the view of the brain network as a whole in previous studies, the method of Granger causality analysis (GCA) we used is focused on the internal organization within a brain network. Also, the method of functional connectivity is used to compare the efficiency of Granger causality analysis. The results show that taking the default mode network (DMN) as an example, the method of Granger causality analysis can be more sensitive to the functional re-organization in a human brain network after a task compared with functional connectivity. And the target of incoming causal influences area changed from rPCu to BG after task.