Building and running large scale computational neuroscience models

The ambitious aim of computational neuroscience is to gain a better understanding of the operation of real neurons and brain circuits. But real neurons are extremely complicated electronic and biochemical devices, whose dynamics we still have a poor understanding of, and they are connected in extremely large, complex and specific networks, whose connectivity and dynamics we have even less understanding of. We are working on three of the software problems associated with modeling brain networks; obtaining access to sufficient experimental data to build models; developing GUIs and standards for declarative XML based model specifications, containing all parameters of multi-level models of neurons, ion channels and networks; and automated techniques for scaling large models across clusters without the modeller having to become a parallel programming expert.