  This is a living document that will be updated when appropriate. MIIND [1, 2]
is a population-level neural simulator. It is based on population density
techniques, just like DIPDE [3]. Contrary to DIPDE, MIIND is agnostic to the
underlying neuron model used in its populations so any 1, 2 or 3 dimensional
model can be set up with minimal effort. The resulting populations can then be
grouped into large networks, e.g. the Potjans-Diesmann model [4]. The MIIND
website http://miind.sf.net contains training materials, and helps to set up
MIIND, either by using virtual machines, a DOCKER image, or directly from
source code.
