Contact us

If you are interested in EDEN, we’ll be delighted to hear from you:

General discussion

Get in touch with our community on our chatroom and mailing list - or just email the developers.

Support tickets

If you’d like to ask for a new feature, or report a problem, please file a support ticket on GitLab.

To subscribe to the mailing list, send an email to eden-simulator-general+subscribe@googlegroups.com.

And more generally, feel free to send e-mail to the developers anytime:

Tip

For questions and suggestions regarding NeuroML, contact also the wider NeuroML community.

Join us

Do you want to add something to EDEN, like a feature, a modified engine or an improved user guide? Join us!

(See also: We have open student thesis topics on sim tech research!)

Guide contributions

Do you have a nice usage example, or method of experimenting, with EDEN? Or perhaps you’d like to see some part of this guide explained in more detail? Contact us for suggestions.

Hint

Refer to Examples gallery to see if something is missing.

Code contributions

Would you like to add a new simulation feature, customize the existing codebase to your needs, or contribute some useful API extensions or language bindings?

See the Hacker’s guide (TBA), contact us for support, and make a pull request.

Research topics

Neural simulation is a topic of active scientific research. More than a product, EDEN is also designed as a platform to test new ideas on the technology of numerical simulation. This ideas can range from new simulation algorithms, to adaptive performance tuning, to specialized computational hardware.

We do have several cutting-edge research questions on simulation technology; if a prospective student (or intern) has some relevant knowledge, and support from an academic institution or an intense personal interest, we can provide specific research topics to work on, and additional guidance.

Here are a few challenges, to explain our kind of work to prospective students:

  • Get the sim code for a neural mass model from GitHub, and convert it so that the matrix is laid out in the ELLPACK format, for more than 1000 neurons and connection probabilities of 1%, 10%, 90%. Compare simulation speed vs. the original code, and and try to explain the results.

  • Get a neural network model in the ModelDB with more than, say, a thousand neurons. Extract the set of synaptic connections between neurons. Apply clustering algorithms to the neurons of the network, so that for N clusters the number of x * (max neurons per cluster) + y * (sum connections between clusters) is minimized. Explore for varying x, y, N.

If you have pulled off one of these, or have another research project to propose, contact us; see also our Msc thesis vacancies (theme “BrainFrame”).