For the past twenty years, scientific visualization has assisted simulation-based research to explore problems of organized complexity. Environmental research, social sciences, astronomy, and modern physics have exploited the increasing power of computer graphics to interactively visualize three-dimensional models. Of late, neuroscience has witnessed the use of large-scale simulation with biologically detailed neuron models, and aspires to benefit from scientific visualization too. This thesis is the result of a close collaboration with the Blue Brain Project, a neuroscience endeavor working on biologically detailed large-scale simulation of the brain, and tries to answer the following question: How can scientific visualization improve neuroscience insights in the context of simulation-based research? Scientific visualization of a model typically preserves its spatial layout. In continuity with this axiom, we identified in more depth the requirements for a scientific visualization solution in neuroscience. Thus, the preservation of the domain specificity, the hybrid visualization, the validation, and the adaptation to the limitations of the human-visual perception enhance the readability of the generated results. We applied these requirements to elaborate an hybrid representation of neuronal structures, and proposed a unified framework of visualization methods which preserves the domain specificities of neuroscience. This framework was finally assessed in case studies, where neuroscientific investigations about structure, composition, and dynamics of neuronal microcircuit challenge the developed visualization solutions to derive insight. We believe that these representations and visualization methods form a solid ground for the elaboration of virtual instruments dedicated to a new approach of neuroscience, where in silico landscapes of the brain are complementary to the classical in vitro and in vivo investigations.