Steady states in an iterative model for multiplicative spike-timing-dependent plasticity

Recent experimental evidence suggests that synaptic plasticity depends on t he precise timing of pre- and post-synaptic activity. In this paper, an ite rative model for a multiplicative form of this spike-timing-dependent plast icity (mSTDP) is introduced. This model is incorporated into a neural netwo rk with many input cells coupled via excitation to a single output cell. An alysis of this network yields a criterion for the output cell to fire on ev ery iteration, as well as general formulae for the steady-state output firi ng rate and the steady-state value to which all synaptic weights are driven by mSTDP. These characterize the basic state of network operation generate d by mSTDP.