INCF/OCNS Software Working Group free tool tutorials, June 27 - July 113 June 2022
The INCF/OCNS Software Working Group is hosting a virtual five-day satellite event with neuroscience software tool tutorials on June 27 - July 1, before the CNS*2022 conference.
Registration is free but mandatory. The following tools/projects will be presented:
The Arbor simulator
A multi-compartment neuron simulation library; compatible with next-generation accelerators; best-practices applied to research software; focussed on community-driven development, written in C++ and CUDA.
The Brian2 simulator
An open source simulator for spiking neural networks, written in the Python programming language and available on almost all platforms. Designed to be easy to learn and use, highly flexible and easily extensible.
The EBRAINS infrastructure
A digital research infrastructure created by the EU-funded Human Brain Project that gathers an extensive range of data and tools for brain-related research.
The GeNN simulator
GeNN is a GPU enhanced Neuronal Network simulation environment based on NVIDIA CUDA technology.
The LFPy module
A Python module for calculation of extracellular potentials from multicompartment neuron models. It relies on the NEURON simulator and uses the Python interface it provides.
The MOOSE simulator
The Multiscale Object-Oriented Simulation Environment is designed to simulate neural systems ranging from subcellular components and biochemical reactions to complex models of single neurons, circuits, and large networks at many levels of detail, from stochastic chemical computations, to multicompartment single-neuron models, to spiking neuron network models.
The Neo package + the Elephant toolkit
Neo is a package for representing electrophysiology data in Python, together with support for reading a wide range of neurophysiology file formats and support for writing to a subset of these formats plus non-proprietary formats including HDF5. Elephant (Electrophysiology Analysis Toolkit) is an emerging open-source, community centered library for the analysis of electrophysiological data in the Python programming language.
The NEST simulator
A simulator for spiking neural network models that focuses on the dynamics, size and structure of neural systems rather than on the exact morphology of individual neurons.
The NetPyNE package
An open-source Python package to facilitate the development, parallel simulation, analysis, and optimization of biological neuronal networks using the NEURON simulator.
The NeuroLib framework
A simulation and optimization framework for whole-brain modeling that allows the user to implement their own neural mass models to simulate fMRI BOLD activity.
The NeuroML initiative
An international, collaborative initiative to develop a language and associated software tools for describing detailed models of neural systems. The NeuroML format is endorsed as a standard by INCF and COMBINE.
The NEURON simulator
A simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well-suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties.
The Open Source Brain v2
A resource for sharing and collaboratively developing computational models of neural systems.
The RateML tool
A code generation tool built on the NeuroML low-level specification language LEMS. Can generate CUDA code. Intended for brain network models and tailored to generate rate-based-models suited for simulators such as the Virtual Brain (TVB) featuring high performance computing and parameter sweep capabilities.
There will also be an introduction to containers, and a presentation of Keras/TensorFlow
The INCF/OCNS Software Working Group was founded in 2020 and is joint between INCF and OCNS (the Organization for Computational Neuroscience). The group gathers computational neuroscience tool developers and maintainers, as well as tool users. They focus on evaluating and testing computational neuroscience tools; finding them, testing them, learning how they work, and informing developers of issues to ensure that these tools remain in good shape by having communities looking after them.