NESTML: a modeling language for spiking neurons
This work addresses the problem for neuroscientists by offering a modular and extensible tool to simplify model creation, though it is incremental as it builds on existing modeling languages by focusing on simulator-specific features.
The authors tackled the difficulty of creating complex spiking neuron models for neuroscientists by developing NESTML, a domain-specific modeling language that provides neuroscience concepts as first-class constructs and generates efficient code for the NEST simulation tool, with the language and example models made publicly available on GitHub.
Biological nervous systems exhibit astonishing complexity .Neuroscientists aim to capture this com- plexity by modeling and simulation of biological processes. Often very comple xm odels are nec- essary to depict the processes, which makes it dif fi cult to create these models. Powerful tools are thus necessary ,which enable neuroscientists to express models in acomprehensi ve and concise way and generate ef fi cient code for digital simulations. Se veral modeling languages for computational neuroscience ha ve been proposed [Gl10, Ra11]. Howe ver, as these languages seek simulator inde- pendence the ytypically only support asubset of the features desired by the modeler .Int his article, we present the modular and extensible domain speci fi cl anguage NESTML, which provides neuro- science domain concepts as fi rst-class language constructs and supports domain experts in creating neuron models for the neural simulation tool NEST .N ESTML and aset of example models are publically available on GitHub.