ArticleJournal of computational neuroscience2012
Accuracy evaluation of numerical methods used in state-of-the-art simulators for spiking neural networks.
Article in Journal of computational neuroscience, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- NESTML: a generic modeling language and code generation tool for the simulation of spiking neural networks with advanced plasticity rules.Frontiers in neuroinformatics · 2025Article
- Performance Comparison of the Digital Neuromorphic Hardware SpiNNaker and the Neural Network Simulation Software NEST for a Full-Scale Cortical Microcircuit Model.Frontiers in neuroscience · 2018Article
- Reducing the computational footprint for real-time BCPNN learning.Frontiers in neuroscience · 2015Article
- A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations.Frontiers in neuroinformatics · 2015Article
- Limits to high-speed simulations of spiking neural networks using general-purpose computers.Frontiers in neuroinformatics · 2014Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the various simulators for spiking neural networks developed in recent years, a variety of numerical solution methods for the underlying differential equations are available. In this article, we introduce an approach to systematically assess the accuracy of these methods. In contrast to previous investigations, our approach focuses on a completely deterministic comparison and uses an analytically solved model as a reference. This enables the identification of typical sources of numerical inaccuracies in state-of-the-art simulation methods. In particular, with our approach we can separate the error of the numerical integration from the timing error of spike detection and propagation, the latter being prominent in simulations with fixed timestep. To verify the correctness of the testing procedure, we relate the numerical deviations to theoretical predictions for the employed numerical methods. Finally, we give an example of the influence of simulation artefacts on network behaviour and spike-timing-dependent plasticity (STDP), underlining the importance of spike-time accuracy for the simulation of STDP.
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Registered trials
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