ArticleNeuroinformatics2014
From model specification to simulation of biologically constrained networks of spiking neurons.
Article in Neuroinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Impact of Neuron Models on Spiking Neural Network Performance: A Complexity-based Classification Approach.Neuroinformatics · 2026Article
- Abstract concept learning in a simple neural network inspired by the insect brain.PLoS computational biology · 2018Article
- Integrating Brain and Biomechanical Models-A New Paradigm for Understanding Neuro-muscular Control.Frontiers in neuroscience · 2018Article
- Parameter Optimization Using Covariance Matrix Adaptation-Evolutionary Strategy (CMA-ES), an Approach to Investigate Differences in Channel Properties Between Neuron Subtypes.Frontiers in neuroinformatics · 2018Article
- Code Generation in Computational Neuroscience: A Review of Tools and Techniques.Frontiers in neuroinformatics · 2018Review
- Temporal constrained objects for modelling neuronal dynamics.PeerJ. Computer science · 2018Article
- SpineCreator: a Graphical User Interface for the Creation of Layered Neural Models.Neuroinformatics · 2017Article
- A computational model of the integration of landmarks and motion in the insect central complex.PloS one · 2017Article
- A Model for an Angular Velocity-Tuned Motion Detector Accounting for Deviations in the Corridor-Centering Response of the Bee.PLoS computational biology · 2016Article
- Promoting Coordinated Development of Community-Based Information Standards for Modeling in Biology: The COMBINE Initiative.Frontiers in bioengineering and biotechnology · 2015Review
- libNeuroML and PyLEMS: using Python to combine procedural and declarative modeling approaches in computational neuroscience.Frontiers in neuroinformatics · 2014Article
- LEMS: a language for expressing complex biological models in concise and hierarchical form and its use in underpinning NeuroML 2.Frontiers in neuroinformatics · 2014Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A declarative extensible markup language (SpineML) for describing the dynamics, network and experiments of large-scale spiking neural network simulations is described which builds upon the NineML standard. It utilises a level of abstraction which targets point neuron representation but addresses the limitations of existing tools by allowing arbitrary dynamics to be expressed. The use of XML promotes model sharing, is human readable and allows collaborative working. The syntax uses a high-level self explanatory format which allows straight forward code generation or translation of a model description to a native simulator format. This paper demonstrates the use of code generation in order to translate, simulate and reproduce the results of a benchmark model across a range of simulators. The flexibility of the SpineML syntax is highlighted by reproducing a pre-existing, biologically constrained model of a neural microcircuit (the striatum). The SpineML code is open source and is available at http://bimpa.group.shef.ac.uk/SpineML .
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.