In many instances, the dynamical richness and complexity observed in natural phenomena can be related to stochastic drives influencing their temporal evolution. For example, random noise allied to spatial asymmetries may induce stabilization of otherwise diverging trajectories in dynamical systems. However, to identify how exactly this takes place in actual processes usually is not a simple task. Here we unveil a few trends leading to dynamical stabilization and diversity of behavior by introducing Gaussian white noise to a class of exactly solvable non-linear deterministic models displaying space-dependent drifts. For the resulting nonlinear Langevin equations, the associated Fokker-Planck equations can be solved through the similarity method or the Fourier transform technique. By comparing the cases with and without noise, we discuss the changes in the systems dynamical characteristics. Simple examples of drift and diffusion coefficients are explicitly analyzed and comparisons with some other models in the literature are made. Our study illustrates the rich phenomenology originated from spatially heterogeneous dynamical systems under the influence of white noise.
