Marc-Oliver Gewaltig, "Simulation Technologie for large neural systems.", Recent developments, chances and limitations of modern brain research., Technologie Ausschuss des Deutschen Bundestags, 2006.

In computational neuroscience, simulations are an important tool to investigate and answer questions which are not tractable by experimental methods. They allow us to explicitly test models of information processing, by constructing models according to the hypothesized principles. Most computer models of neural systems focus on the properties of single neurons or small networks of neurons (see 2.2.2). However, in order to understand the fundamental principles of information processing in the brain, we need models which also capture the global control architecture of the brain, including the fine-tuned interplay between its different parts and processing levels. Large-scale computer simulations, using parallel and distributed computing technology, are required to investigate such models. Although current computer technology is far from providing the necessary resources to model all sub-systems of the brain in great detail, large-scale simulation technology allows us to approach this goal from different directions. More research on appropriate simulation technology, including computer science and hardware research has to be conducted.