Computational Neuroscience

Computational neuroscience aims to study the nervous system by mathematical and computer simulations. Computational models can be built on multilevel scales. With the bottom-up approach, the model is built from the same building blocks as observed in human or animal tissue. As such, the functioning of a neuron depends on the behavior of its ion channels. Subsequently, these neurons are connected via synapses to obtain the network response. Ion channels and synapses are mathematically represented by a set of differential equations, modeled after the Hodgkin-and-Huxley formalism. The models enable simple and systematic parameter manipulation of often experimentally inaccessible aspects. They can therefore be used to test hypotheses concerning underlying mechanisms of neurological diseases on multilevel scale. New hypotheses can be formulated as well. The obtained results can be used to design more delineated in-vivo I in-vitro experiments, reducing the amount of experiments needed. Finally, they are an ideal tool to gain more insights in the effect of treatment strategies and provide improved treatment protocols.