Parametric and non-parametric modeling of short-term synaptic plasticity. Part I: computational study

摘要: Parametric and non-parametric modeling methods are combined to study the short-term plasticity (STP) of synapses in central nervous system (CNS). The nonlinear dynamics STP modeled by means: (1) previously proposed parametric models based on mechanistic hypotheses and/or specific dynamical processes, (2) (in form Volterra kernels) that transforms presynaptic signals into postsynaptic signals. In order synergistically use two approaches, we estimate kernels for four types using synthetic broadband input–output data. Results show accurately efficiently replicate transformations models. provide a general quantitative representation STP.