The understanding of the human brain is a formidable task. While our knowledge is quickly expanding on the detailed function on the cellular level we have still a long way to go in understanding of brain function at the systems level. Brain function rests on non-supervised parallel processing with distinct non-linear properties. Hence, reductionist type of solutions and intuitive pseudo linear models do not lead to a deeper understanding. Computational neuroscience entails micro level based macro models of brain function. The higher the neurorealism the higher the predictive value of the model. However, high detail models entail a substantial problem in the demand for computational power. We have recently acquired an entry-level machine (IBM Blue Gene P 1024 processors) in order to robustly establish the field computational neurosceince at Stockholm Brain Institute.
