Proposes a simulator-independent language for building neuronal network models. PyNN makes it possible to write a simulation script once, using the Python programming language, and run it without modification on any supported simulator (currently NEURON, NEST, PCSIM, Brian and the Heidelberg VLSI neuromorphic hardware). PyNN increases the productivity of neuronal network modelling by providing high-level abstraction, by promoting code sharing and reuse, and by providing a foundation for simulator-agnostic analysis, visualization and data-management tools. PyNN increases the reliability of modelling studies by making it much easier to check results on multiple simulators.
Serves for training, testing, finetuning, and deploying models, with well-documented examples for all of these tasks. Caffe is a program allowing extension to new formats, network layers, and loss functions. It can be useful for state-of-the-art deep learning algorithms and a collection of reference models. Moreover, this tool fits industry and internet-scale media needs by CUDA graphics processing unit (GPU) computation.
Assists users for numerical computation. Scilab aims to provide computing environment for engineering and scientific applications. This tool includes functionalities specifically for: (1) numerical analysis, (2) data visualization, (3) algorithm development, and (4) application deployment.
Aims to support neural simulations conceived under python. NeuroTools intends to supply an additional assistance for tasks which are not provided by simulation engines, for instance into the fields of parameterization, instrumentation or visualization. This package is composed of nine modules encompassing several tools to assist users in plotting and image processing as well as in manipulation and calculation using spike trains.
A toolbox that facilitates importing and exporting models represented in the Systems Biology Markup Language (SBML) in and out of the MATLAB environment and provides functionality that enables an experienced user of either SBML or MATLAB to combine the computing power of MATLAB with the portability and exchangeability of an SBML model. SBMLToolbox supports all levels and versions of SBML.
Automates the workflow of simulation job submissions when using heterogeneous computational resources, simulators, and simulation tasks. NeuroManager is an object-oriented simulation management software engine for computational neuroscience. This method (i) provides flexibility to adapt a variety of neuroscience simulators, (ii) simplifies the use of heterogeneous computational resources, from desktops to super computer clusters, and (iii) improves tracking of simulation evolution.
Allows analysis of many types of experiments, validation of computational models, and extraction of maximum information from the available experimental data. gfit aims to connect models with various types of experimental data. The software (1) simplifies the model's task of directly simulating experimentally observable variables, (2) maintains communications between the analysis components, acting as a mediator during regression analysis, and (3) facilitates customization of the analysis procedure.