Learning in the form of synaptic plasticity is an essential part of any neural simulation software claiming to be biologically plausible. While plasticity has been a part of Nengo from the beginning, few simulations have been created to make full use of the plasticity mechanisms built into Nengo, and as a result, they have been under-maintained. Since SVN revision 985, the way plasticity is implemented in Nengo has changed signifcantly. This report is intended to explain how plasticity rules are implemented since that revision, and provide examples of how to use and extend the plasticity rules currently implemented.