Tracking time-varying causality network. Sij(t) represents time-varying causality effect from neuron i to j. A. Simulation: Proposed time-varying causality measure had larger values when x caused y than when x did not cause y. B. Real data analysis: Time-varying causality network was estimated using two neural spike train data recorded in the insular cortex of a rat over before and after LiCl injections.