Brian2GeNN - the Brian 2 frontend to the GeNN simulator

Official Brian2GeNN site on GitHub

Brian2GeNN is Python based software that allows to run Brian 2 models on the GPU accelerated GeNN backend. Depending on the model and available GPU hardware, this can allow considerable speed-up. The manual for Brian2GeNN is hosted on ReadTheDocs. There are many install options including conda, pip and manual install of zip or tarball. Refer to the manual for details of install and use.

Dynamic Clamp StdpC

Official StdpC site on GitHub

The Dynamic Clamp protocol, developed indepently by Sharp et. al. (J. Neurophysiol. 69:992-995, 1993) and Robinson and Kawai (J Neurosci Methods 49(3):157-65, 1993) allows "insertion" of simulated membrane conductances in, and/or simulated synapses between biological neurons. Reynaldo Pinto et al. developed a very nice clamp implementation for windows platforms called DYNCLAMP2/4. StdpC is the next generation dynamic clamp based on his original design.

Neural Network Animation NeurAnim

Official NeurAnim website on

Neuranim is a QT/OpenGL based software to visualize neural network simulation data. It supports the neuroML standard for input geometry and various data formats for the simulation data.

GPU enhanced Neural Networks (GeNN)

Obtain the software on GitHub and find all details on the GeNN webpage

GeNN is a framework for neuronal network simulations on NVIDIA graphical processing units (GPUs). It uses a code generation approach to generate efficient simulation engines for neuronal network models that are specified through a simple interface. The generated code compiles with NVIDIA CUDA to run on any CUDA-enabled NVIDIA GPU. This project is in active development, please contact me if you are interested in contributing.