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Biological neuronal network simulations with Python

What it gives you

  • shell environment with NEST 2.6, NEURON 7.3, Brian 1.4 and PyNN 0.8 installed.
  • IPython, scipy, matplotlib and OpenMPI are also installed.
  • ssh access, so you can access the container with multiple terminals.
  • X-windows support, so you can display windows running in the container on your host display.
  • use directly or as a base for your own project-specific Docker images.


To enable ssh access you will need to obtain the private key for the image. Start a container with a bash shell:

(host)$ docker run -i -t neuralensemble/simulationx /bin/bash

and then in the container run:

(docker)# cat $KEYFILE

Copy-and-paste the output into a file in your working directory, e.g. docker_key, and then set the access permissions so only you can read it, i.e. chmod go-r docker_key.

(Note: since anyone can obtain this key by downloading the image, it is not safe for running on the public web, and is intended only for running locally. If you wish to run this image in the cloud, you should create a new key pair).

Basic use

In normal use, you will run the container as an SSH server:

(host)$ docker run -d -p 22 neuralensemble/simulationx

Run docker ps to obtain the port number, and then use this to connect to the container:

(host)$ ssh -Y -i ./docker_key -p 32782 docker@localhost

You should then activate the "simulation" virtual environment:

(docker)$ source ~/env/simulation/bin/activate

after which you can run simulations with Python and MPI. To test that X11 forwarding is working, run xeyes.

Mac OS X

On Mac OS X, you will need to launch XQuartz if you want to display X11 windows.

Since you will be running Docker in a VM, e.g. using boot2docker or docker-machine, you will need to obtain the IP address of the VM, e.g.

(host)$ docker-machine ip default
(host)$ ssh -Y -i ./docker_key -p 32782 docker@


For documentation of the simulation tools installed in the image, see