  The input-output behaviour of the Wiener neuronal model subject to
alternating input is studied under the assumption that the effect of such an
input is to make the drift itself of an alternating type. Firing densities and
related statistics are obtained via simulations of the sample-paths of the
process in the following three cases: the drift changes occur during random
periods characterized by (i) exponential distribution, (ii) Erlang distribution
with a preassigned shape parameter, and (iii) deterministic distribution. The
obtained results are compared with those holding for the Wiener neuronal model
subject to sinusoidal input
