Hi everyone,
I wonder if anyone knows of a Computational Neuroscience lab that can create postdoc positions and favours Julia development?
@mefob in response to your initial post now there is also this package: https://github.com/darsnack/SpikingNN.jl, which has a branch: refactor/gpu-support. I have found GPU support (via CuArray) does not work on arbitrary models and networks, but it does work in a limited way on some models.
At the moment I am working on a repository that uses genetic algorithms to fit network raster plots and single-cell recordings for spike train data. The repository is here: https://github.com/russelljjarvis/SpikeNetOpt.jl. The code organization is currently a bit of a mess, as I am still learning how to make packages in Julia. Most often I optimize SNNs and single cell models implemented by AStupidBear/SpikingNeuralNetworks.jl, because at the time, this package was the most feature-rich (more ready to go plotting utils) and more easily hackable for a beginner.
These other two (previously mentioned) packages do seem to offer alternative and equally merited approaches and methods. Ideally, someone would be able to integrate the best of all three SNN packages:
- AStupidBear/SpikingNeuralNetworks.jl (hackable, lots of functioning network examples, plotting works well possibly not written in CUDA compliant manner).
- leaflabs/WaspNet.jl (putative GPU support?, not much plotting functions).
- darsnack/SpikingNN.jl (has different and convenient methods for providing arbitrary external current inputs to spiking neural models, has some putative GPU support, as mentioned above).
My approach at the moment is to use Genetic Algorithms to make SNNs a better representation of experimental data, as this approach conforms to my background, but I would also like to re-apply the code for Learning 2 Learn (L2L) experiments.