EDEN: A High-Performance, General-Purpose, NeuroML-Based Neural Simulator

ABSTRACT: Modern neuroscience employs in silico experimentation on ever-increasing and more detailed neural networks. The high modeling detail goes hand in hand with the need for high model reproducibility, reusability and transparency. Besides, the size of the models and the long timescales under study mandate the use of a simulation system with high computational performance, so as to provide an acceptable time to result. In this work, we present EDEN (Extensible Dynamics Engine for Networks), a new general-purpose, NeuroML-based neural simulator that achieves both high model flexibility and high computational performance, through an innovative model-analysis and code-generation technique. The simulator runs NeuroML-v2 models directly, eliminating the need for users to learn yet another simulator-

SUBMITTER: Panagiotou S 

PROVIDER: S-EPMC9167055 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature