Tag Archives: schematic visualization

Multi-View Framework

The Multi-View Framework is a software component, which offers functionality to combine various visual representations of one or more data sets in a coordinated fashion.  Software components offering visualization capabilities can be included in such a network, as well as software components offering other functionality, such as statistical analysis. Multi-display scenarios can be addressed by the framework as coordination information can be distributed over network between view instances running on distributed machines.

The framework is composed of three libraries: nett, nett-python and nett-connect. nett implements a light-weight underlying messaging layer enabling the communication between views, whereas nett-python implements a python binding for nett, which enables the integration of python-based software components into a multi-view setup. nett-connect adds additional functionality to this basic communication layer, which enables non-experts to create multi-view setups according to their specific needs and workflows.

Interactive optimization of parameters for structural plasticity in neural network models (top left); comparative analysis of NEST simulations (top right); statistical analysis of NEST simulations (bottom left); multi-device and multi-user scenarios (bottom right)
Date of release2017
Version of softwareN/A
Version of documentationN/A
Software availablePlease contact the developers
Documentationhttps://devhub.vr.rwth-aachen.de/cnowke/nett-connect
ResponsibleU Trier: Weyers, Benjamin (weyers@uni-trier.de)
Requirements & dependencies
Target system(s)

MSPViz

MSPViz is a visualization tool for the Model of Structural Plasticity. It uses a visualisation technique  based on the representation of the neuronal information through the use of abstract levels and a set of schematic representations into each level. The multilevel structure and the design of the representations constitutes an approach that provides organized views that facilitates visual analysis tasks.

Each view has been enhanced adding line and bar charts to analyse trends in simulation data. Filtering and sorting capabilities can be applied on each view to ease the analysis. Other views, such as connectivity matrices and force-directed layouts, have been incorporated, enriching the already existing views and improving the analysis process. This tool has been optimised to lower render and data loading times, even from remote sources such as WebDav servers.

Screenshot of MSPViz
Screenshot of MSPViz
Screenshot of MSPViz
Screenshot of MSPViz
View of MSPViz to investigate structural plasticity models on different levels of abstraction: connectivity of a single neuron
View of MSPViz to investigate structural plasticity models on different levels of abstraction: full network connectivity
Date of releaseMarch 2018
Version of software0.2.6
Version of documentation0.2.6 for users
Software availablehttp://gmrv.es/mspviz
DocumentationSelf-contained in the application
ResponsibleUPM: Juan Pedro Brito (juanpedro.brito@upm.es)
Requirements & dependenciesSelf-contained code
Target system(s)Platform independent

NeuroScheme

NeuroScheme is a tool that allows users to navigate through circuit data at different levels of abstraction using schematic representations for a fast and precise interpretation of data. It also allows filtering, sorting and selections at the different levels of abstraction. Finally it can be coupled with realistic visualization or other applications using the ZeroEQ event library developed in WP 7.3.

This application allows analyses based on a side-by-side comparison using its multi-panel views, and it also provides focus-and-context. Its different layouts enable arranging data in different ways: grid, 3D, camera-based, scatterplot-based or circular. It provides editing capabilities, to create a scene from scratch or to modify an existing one.

ViSimpl, part of the NeuroScheme framework, is a prototype developed to analyse simulation data, using both abstract and schematic visualisations. This analysis can be done visually from temporal, spatial and structural perspectives, with the additional capability of exploring the correlations between input patterns and produced activity.

 

NeuroScheme
NeuroScheme screenshot
NeuroScheme
NeuroScheme screenshot
NeuroScheme
NeuroScheme screenshot
NeuroScheme
NeuroScheme screenshot
NeuroScheme
NeuroScheme screenshot
Overview of various neurons
User interface of ViSimpl visualising activity data emerging from a simulation of a neural network model
Date of releaseMarch 2018
Version of software0.2
Version of documentation0.2
Software availablehttps://github.com/gmrvvis/NeuroScheme
Documentationhttps://github.com/gmrvvis/NeuroScheme, http://gmrv.es/gmrvvis
ResponsibleURJC: Pablo Toharia (pablo.toharia@urjc.es)
Requirements & dependenciesRequired: Qt4, nsol
Optional: Brion/BBPSDK (to access BBP data), ZeroEQ (to couple with other software)
Supported OS: Windows 7, Windows 8.1, Linux (tested on Ubuntu 14.04) and Mac OSX
Target system(s)Desktop computers, notebooks, tablets