  In two recent papers, Rudolph and Destexhe (Neural Comp. {\bf 15},
  2577-2618, 2003; Neural Comp. in press, 2005) studied a leaky integrator
model (i.e. an RC-circuit) driven by correlated (``colored'') Gaussian
conductance noise and Gaussian current noise. In the first paper they derived
an expression for the stationary probability density of the membrane voltage;
in the second paper this expression was modified to cover a larger parameter
regime. Here we show by standard analysis of solvable limit cases (white-noise
limit of additive and multiplicative noise sources; only slow multiplicative
noise; only additive noise) and by numerical simulations that their first
result does not hold for the general colored-noise case and uncover the errors
made in the derivation of a Fokker-Planck equation for the probability density.
Furthermore, we demonstrate analytically (including an exact integral
expression for the time-dependent mean value of the voltage) and by comparison
to simulation results, that the extended expression for the probability density
works much better but still does not solve exactly the full colored-noise
problem. We also show that at stronger synaptic input the stationary mean value
of the linear voltage model may diverge and give an exact condition relating
the system parameters for which this takes place.
