  We study the dynamics of the structure of a formal neural network wherein the
strengths of the synapses are governed by spike-timing-dependent plasticity
(STDP). For properly chosen input signals, there exists a steady state with a
residual network. We compare the motif profile of such a network with that of a
real neural network of \emph{C. elegans} and identify robust qualitative
similarities. In particular, our extensive numerical simulations show that this
STDP-driven resulting network is robust under variations of the model
parameters.
