A number of Special Interest Groups (SIGs) were created by the International Neuroinformatics Coordinating Facility (INCF) to advance areas of common interest within the neuroscience community. These are now referred to as Working Groups (WG).
This WG deals with the various tools and formats for creating and sharing representations of biological neuronal networks, and will work towards ensuring these are as interoperable and usable as possible for computational neuroscientists.
The homepage for this WG is here. This GitHub repository is intended for documents, code samples, issue tracking and links to related initiatives.
The motivation for this WG is the ongoing development of complex data-driven models of neuronal networks, as well as the emergence of general purpose software packages and standardised formats to make it easier to build, specify and share such networks. To encourage researchers to use these common tools and formats (and ultimately create and disseminate higher quality models) we have gathered together developers creating these packages to share code and ideas, to encourage interoperability and have a forum for users and developers to find out about the state of the art and to contribute to a better ecosystem of tools and standards in this area.
The short term goals focus on highlighting and promoting existing open source initiatives working with network representations. These include, but are not limited to:
- BMTK, The Brain Modeling Toolkit: https://github.com/AllenInstitute/bmtk
- NEST: http://www.nest-simulator.org
- NetPyNE: http://www.netpyne.org
- NeuroML: http://www.neuroml.org; https://github.com/NeuroML/NeuroMLlite
- NineML: http://www.nineml.net
- PyNN: http://neuralensemble.org/PyNN/
- Sonata: https://github.com/AllenInstitute/sonata
- TVB, The Virtual Brain: http://www.thevirtualbrain.org
Practical steps will include making sure these are compatible and interoperable where appropriate.
Some of the formats
which are being examined in this WG and their scope in terms of biophysical detail
(x-axis) and usage in the model building workflow (y-axis).
Longer term goals including working towards minimising overlap in functionality/scope, adding other open tools/formats to the interoperability framework and ensuring the use of these (particularly low level declarative formats) are as transparent and as user friendly as possible for the modeller.
- Anton Arkhipov, Allen Institute, USA
- Tom Close, Monash University, Australia
- Sharon Crook, Arizona State University, USA
- Kael Dai, Allen Institute, USA
- Andrew Davison, UNIC, CNRS, France
- Lia Domide, Codemart, Romania & Aix-Marseille Université, France
- Salvador Durá-Bernal, SUNY Downstate Medical Center, USA
- Viktor Jirsa, Aix-Marseille Université, France
- John Griffiths, Rotman Research Institute, Baycrest, Canada
- Padraig Gleeson, University College London, UK
- Sacha van Albada, Jülich Research Centre, Germany
- Marmaduke Woodman, Aix-Marseille Université, France
An overview of the tasks which are ongoing and planned related to the work of this WG can be found here: https://github.com/NeuralEnsemble/Networks_SIG/projects/1
A workshop on Tools and formats for large scale network modelling will be organised by the WG at the INCF Neuroinformatics Assembly 2022. See here for more information.
Many members/initiatives from the WG were involved with the NeuroML development workshop at the Oct 2021 COMBINE meeting, including representatives from NeuroML, NetPyNE and PyNN, where future plans for network specification in NeuroML (centred around NeuroMLlite) were discussed.
A workshop on "Standardised neuronal network specifications" is being organised in a breakout session of COMBINE 2020 on 9th Oct. More details here.
A workshop on "Tools and resources for developing and sharing models in computational neuroscience" was organised by members of the WG as part of the fully online CNS 2020 meeting on 21/22nd July. More details here.
Plans are in development for WG activities at the (delayed) INCF Neuroinformatics 2020 meeting. Stay tuned...
A number of developers of the packages which are part of this WG presented at the Open Source Brain meeting in Alghero, Sardinia in Sept 2019. The meeting page contains links to slide presentations with recent work from many groups/initiatives including the Human Brain Project, Allen Institute, NEST, Geppetto, NWB, TVB, Open Source Brain, NeuroML & NeuroML-DB.
A workshop entitled “Developing, standardising and sharing large scale cortical network models” was held at CNS 2018 in Seattle: http://www.opensourcebrain.org/docs/Help/Meetings#CNS_2018. A report of the meeting is available here.
The following publications are related to the activities of this WG.
Note: these have not been specifically coordinated/funded/directed through this WG, but feature authors from multiple labs who are members of this WG and are in line with the goals of the wider group.
Padraig Gleeson, Matteo Cantarelli, Boris Marin, Adrian Quintana, Matt Earnshaw, Sadra Sadeh, Eugenio Piasini, Justas Birgiolas, Robert C. Cannon, N. Alex Cayco-Gajic, Sharon Crook, Andrew P.Davison, Salvador Dura-Bernal, András Ecker, Michael L. Hines, Giovanni Idili, Frederic Lanore, Stephen D. Larson, William W. Lytton, Amitava Majumdar, Robert A. McDougal, Subhashini Sivagnanam, Sergio Solinas, Rokas Stanislovas, Sacha J. van Albada, Werner van Geit, R. Angus Silver (2019). Open Source Brain: a collaborative resource for visualizing, analyzing, simulating and developing standardized models of neurons and circuits. Neuron 103 (3):395–411
Kael Dai, Juan Hernando, Yazan N. Billeh, Sergey L. Gratiy, Judit Planas, Andrew P. Davison, Salvador Dura-Bernal, Padraig Gleeson, Adrien Devresse, Michael Gevaert, James G. King, Werner A. H. Van Geit, Arseny V. Povolotsky, Eilif Muller, Jean-Denis Courcol, Anton Arkhipov (2019). The SONATA data format for efficient description of large-scale network models. bioRxiv 625491
Salvador Dura-Bernal, Benjamin A Suter, Padraig Gleeson, Matteo Cantarelli, Adrian Quintana, Facundo Rodriguez, David J Kedziora, George L Chadderdon, Cliff C Kerr, Samuel A Neymotin, Robert A McDougal, Michael Hines, Gordon MG Shepherd, William W Lytton (2019). NetPyNE, a tool for data-driven multiscale modeling of brain circuits. eLife 8, e44494