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PyNN specifications


Unique identifier OMICS_15876
Name PyNN
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Python
License CeCILL version 2.1
Computer skills Advanced
Version 0.8.2
Stability Beta
Maintained Yes




No version available



  • person_outline Andrew Davison

Publication for PyNN

PyNN citations


Credibility, Replicability, and Reproducibility in Simulation for Biomedicine and Clinical Applications in Neuroscience

Front Neuroinform
PMCID: 5911506
PMID: 29713272
DOI: 10.3389/fninf.2018.00018

[…] nly used frameworks include Travis CI (Continuous Integration), Circle CI, Jenkins, and AppVeyor.Whenever possible, use reliable model development platforms such as NEST, BRIAN, NEURON, MOOSE, NENGO, PyNN, etc. This will increase the likelihood of accurate simulation and will enhance sharing. Similarly, model components should be taken from reliable databases of morphologies, channels and other co […]


Software for Brain Network Simulations: A Comparative Study

Front Neuroinform
PMCID: 5517781
PMID: 28775687
DOI: 10.3389/fninf.2017.00046

[…] As we mentioned in Section , several software front-ends such as PyNN and neuroConstruct can hide the real implementation from a user. Usability and user level support are even more important for large size models, in addition to cases when a user applies a specifi […]


Constructing Neuronal Network Models in Massively Parallel Environments

Front Neuroinform
PMCID: 5432669
PMID: 28559808
DOI: 10.3389/fninf.2017.00030
call_split See protocol

[…] icity (STDP). Researchers create network models and specify simulations using high-level commands of a built-in interpreter (SLI), a Python interface (Eppler et al., ; Zaytsev and Morrison, ), or the PyNN network simulator interface (Davison et al., ).Internally, the simulation kernel, including all neuron and synapse models, is implemented in C++. Neurons and synapses are represented as instances […]


Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform

PMCID: 5263131
PMID: 28179882
DOI: 10.3389/fnbot.2017.00002

[…] imulator with the capability of running on high-performance computing platforms, that is also one of the simulation backends of the Brain Simulation Platform. NEST is supported through the use of the PyNN abstraction layer (Davison et al., ) that provides the same interface for different simulators and also for neuromorphic processing units, i.e., dedicated hardware for the simulation of SNN such […]


Benchmarking Spike Based Visual Recognition: A Dataset and Evaluation

Front Neurosci
PMCID: 5090001
PMID: 27853419
DOI: 10.3389/fnins.2016.00496

[…] s recorded from a DVS retina (Serrano-Gotarredona and Linares-Barranco, ). The resolution of the DVS recorded data is 128 × 128. The second spike-based format used is a list of spike source arrays in PyNN (Davison et al., ), a description language for building spiking neuronal network models. Python code is provided for converting from either file format to the other. The duration of the artificia […]


SpineCreator: a Graphical User Interface for the Creation of Layered Neural Models

PMCID: 5306153
PMID: 27628934
DOI: 10.1007/s12021-016-9311-z

[…] erface of buttons and menus. Therefore while there is some overlap between the tools there is also a clear distinction.Several tools use the high level Python programming language for model creation (PyNN (Davison et al. ), Brian (Goodman and Brette ), pyNEST (Eppler et al. )). These tools use a scripting approach where a set of functions are used to build the model. The scripting approach allows […]

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PyNN institution(s)
Unité de Neurosciences Intégratives et Computationelles, CNRS Gif sur Yvette, France
PyNN funding source(s)
This work was supported by the European Union (FACETS project, FP6-2004-IST-FETPI-015879), and by the German Federal Ministry of Education and Research (BMBF grant 01GQ0420, Freiburg).

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