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I know, this question is opinion-based, but where else should I ask it (or how could I ask it here without being flagged "opinon-based!")?

Which neuronal simulators - in the line of NEURON and GENESIS - are the "best", "mostly used", "mostly influential" today, not only in supercomputing, but also for small scale (personal) use?

The one I found best - even though designed for large scale applications - for my small scale (personal) requirements was nest, an explicit successor of NEURON. I have the impression, that nest is "better" for me than NEURON, in terms of usability, visualization, data exploration, ... but I don't know if there aren't even better neuro-simulation tools.

Would anyone mind giving his/her opinion?

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  • $\begingroup$ I'd suggest asking questions like this that are a bit outside the normal SE rules in the Biology.SE chat. I'm most familiar with NEURON, though mostly in an educational rather than research context; I haven't used nest but if it is a successor to NEURON that's what I would recommend. One nice thing about NEURON is that there are so many examples/preexisting models to choose from, including some beautifully detailed volume reconstructions of real neurons; GENESIS may have the same, and I hope nest was able to preserve some of them. $\endgroup$ – Bryan Krause Sep 12 '17 at 17:07
  • $\begingroup$ I think it's a great question, and I hope it is not closed for being opinion-based. This is exactly the question I had years ago when starting on a project! Btw, you might also try the scientific computation SE as well. $\endgroup$ – user3658307 Sep 13 '17 at 1:09
  • $\begingroup$ I also think that this is a worthwhile, on-topic question, even if it is opinion-based. $\endgroup$ – vkehayas Sep 15 '17 at 10:31
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Another option, maximal in terms of flexibility albeit also possibly effort, is to write your own. Of course, this presupposes some extra knowledge. However, I think coding your own gives a level of control that may be very difficult to attain with a library. Hence, it depends on the application. (ModelDB has some examples of these.)

Of course, I don't recommend this for highly complicated cases (don't try to write your own code to solve SPDEs in volumetric meshes or something).

Using matlab or python (numpy & scipy) makes writing at least some of these models fairly straightforward, and both (especially the latter) have extraordinary scientific visualization capabilities. I have run neurosimulations like this on both my personal laptop and via hundreds of cores in clusters, so it is certainly viable in both cases.

Every model is approximation, and sometimes it is worth it to have better understanding and control of a simpler model than to have an enormously complicated one with huge numbers of different channels that may be hard to realistically choose (what is their spatial distribution and concentration? what are their parameters for the species of interest?). It depends on the phenomenon you want to simulate.


In any case, to speak of libraries, both NEST and NEURON seem like great choices. Personally, I've heard only of NEURON in any detail before.

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I have only used NEURON and the DIY approach for small scale simulations.

You can have a look at this comparative table:

https://grey.colorado.edu/emergent/index.php/Comparison_of_Neural_Network_Simulators

which was last updated in 2014. Except NEURON, GENESIS, and NEST, I have also heard positive comments about Brian.

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