Gaining a better understanding of the human brain continues to be one of the greatest and most elusive of challenges. Its extreme complexity can only be addressed through the coordinated and collaborative work of researchers from a range of disciplines. 3D visualization has proven to be a useful tool for simplifying the analysis of complex systems, where gaining meaningful understanding from unstructured raw data is almost impossible, such as in the case of the brain. This paper presents a novel approach for visualizing neurons directly from the morphological descriptions extracted by neuroscience laboratories, pursuing two goals: improving the readability of complex neuronal scenarios and avoiding the need to store 3D models of the intricate geometry of neurons, since such models are demanding of computer resources. The proposed rendering method involves illustration techniques that facilitate the visual analysis of dense neural scenes. The work presented here brings the field of neuroscience and the benefits of 3D visualization environments closer together, increasing the interpretability of massive neural scenarios through visual inspection. A preliminary user study has proven the utility of the proposed rendering techniques for the visual exploration of dense neuronal scenes. The feasibility of parallelizing the implemented algorithms has also been assessed, representing a further step towards interactive illustrative visualization of neuronal forests.

3D Visualization techniques, neuronal data visualization, illustrative rendering