This workshop was held at the 29th Annual Computational Neuroscience Meeting. CNS 2020 was held entirely online in 2020.
- Kael Dai, Allen Institute for Brain Science, [email protected]
- Salvador Dura-Bernal, State University of New York Downstate, [email protected]
- Padraig Gleeson, University College London, [email protected]
- Upi Bhalla, National Centre for Biological Sciences, India (MOOSE) [Slides]
- Petra Ritter, Charité, Berlin, Germany (TVB, VirtualBrainCloud)
- Ben Cummings, ETH Zurich, Switzerland (ARBOR)
- Charl Linssen, Jülich Supercomputing Centre, Germany (NEST)
- Dan Goodman, Imperial College, UK (Brian) [Slides]
- Robert McDougal and Lia Eggleston, Yale University, USA (NEURON / ModelDB)
- Salvador Dura-Bernal, SUNY Downstate, Brooklyn, USA (NetPyNE)
- Anton Arkhipov, Allen Institute for Brain Science, USA (BMTK) [Slides]
- Andrew Davison, Paris-Saclay Institute of Neuroscience, France (PyNN) [Slides]
- Luca Bologna, CNR / Human Brain Project (HBP BSP) [Slides]
- Ted Carnevale and Serena Thaw-Poon, Yale University, USA (ModelDB) [Slides]
- Padraig Gleeson, University College London, UK (NeuroML / OSB)
- Pramod Kumbhar, EPFL / Blue Brain Project, Switzerland (coreNEURON) [Slides]
- Subhashini Sivagnanam, San Diego Supercomputer Center, USA (Neuroscience Gateway)
- Aurel Lazar, Columbia University, USA (FFBO & FBL) [Slides]
This workshop focussed on recent advances in software tools for modeling neurons and neuronal networks at different levels of resolution. Neuroscience has been experiencing a rapid growth of data streams characterizing composition, connectivity, and activity of brain networks in ever increasing details. Data-driven modeling will be essential to integrate these multimodal and complex data into predictive simulations to advance our understanding of brain function and mechanisms. We brought together representatives of many teams that develop computational tools aimed at incorporating and simulating this complexity.
Major topics for discussion included the established and emerging computational approaches for building and simulating network models, advances in enabling increased access to sophisticated modeling for a broad community of users, and sharing and reproducibility of models. These discussions should serve to promote the efficiency, reproducibility, and free exchange of computational models in the community to support advances in many areas of neuroscience.
A detailed schedule with links to video stream each talk was made available online via Sched.com. To view this schedule please register to the CNS'2020 meeting.
The workshop scheduled is summarized below, with times in the US EASTERN TIME / NY timezone:
