Efficient Estimation of Directed Connectivity in Nonlinear and Nonstationary Spiking Neuron Networks

Studying directed connectivity within spiking neuron networks can help understand neural mechanisms. Existing methods assume linear time-invariant neural dynamics with a fixed time lag in information transmission, while spiking networks usually involve complex dynamics that are nonlinear and nonstationary, and have varying time lags.