With the host of experimental data in neuroscience, systems modeling is an increasingly important tool for relating data to algorithmic models of neural computation. In this symposium, eight speakers present state-of-the-art systems neuroscience modeling work encompassing topics like large-scale computational models, plausible learning algorithms and population models. This symposium specifically aims to bring together people with shared interest in system-scale neural computation.