“…In the most commonly used formulations of Granger causality (Ding et al, 2006), the degree to which a causal variable help to predict an effective variable beyond the information contained in the effective variable's own past is measured either by the decrease of the residuals (Ding et al, 2006; Jiao et al, 2014; Kullmann et al, 2014), i.e., the time domain formulation, or by the frequency decomposition (Geweke, 1982; Bajaj et al, 2014, 2015), i.e., the frequency domain formulation, both through estimating an autoregression model with a fixed order. However, in some recent studies, another “signed path coefficient” version of Granger causality was proposed (Chen et al, 2009) and had been firstly used to reveal the causality from brain regions of patients with major depression disorder (Hamilton et al, 2011), and gradually it was popular among a number of researchers in the field of fMRI.…”