Recent advances in our ability to record simultaneously from large numbers of neurons has shifted the focus in neuroscience from understanding dynamics at a single cell level to the network level. At the same time, the rise of modern machine learning has independently generated interest in how computation arises from the coordinated activity of large networks of simple units. This workshop explores how computation emerges from network dynamics, asking how circuit structure, network architecture, and plasticity/learning shape the neural dynamics underlying cognitive functions.