Serotonergic axons (fibers) are a universal feature of all vertebrate brains. They form meshworks, typically quantified with regional density measurements, and appear to support neuroplasticity. The self-organization of this system remains poorly understood, partly because of the strong stochasticity of individual fiber trajectories. In an extension to our previous analyses of the mouse brain, serotonergic fibers were investigated in the brain of the Pacific angelshark (Squatina californica), a representative of a unique (ray-like) lineage of the squalomorph sharks. First, the fundamental cytoarchitecture of the angelshark brain was examined, including the expression of ionized calcium binding adaptor molecule 1 (Iba1, AIF-1) and the mesencephalic trigeminal nucleus. Second, serotonergic fibers were visualized with immunohistochemistry, which showed that fibers in the forebrain have the tendency to move toward the dorsal pallium and also accumulate at higher densities at pial borders. Third, a population of serotonergic fibers was modeled inside a digital model of the angelshark brain by using a supercomputing simulation. The simulated fibers were defined as sample paths of fractional Brownian motion (FBM), a continuous-time stochastic process. The results reproduced key features of serotonergic fiber densities in the telencephalon, a brain division with a considerable physical uniformity and no major \"obstacles\" (dense axon tracts). The study provides further evidence that serotonergic fibers can be successfully modeled as paths of a rigorously-defined stochastic process, and that a rich repertoire of self-organizing behaviors can be produced by axons that are inherently stochastic but also respond to external forces.