VIOLA - A multi-purpose and web-based visualization tool for neuronal-network simulation output

Neuronal network models and corresponding computer simulations are invaluable tools to aid the interpretation of the relationship between neuron properties, connectivity and measured activity in cortical tissue. Spatiotemporal patterns of activity propagating across the cortical surface as observed experimentally can for example be described by neuronal network models with layered geometry and distance-dependent connectivity. The interpretation of the resulting stream of multi-modal and multi-dimensional simulation data calls for integrating interactive visualization steps into existing simulation-analysis workflows. Here, we present a set of interactive visualization concepts called views for the visual analysis of activity data in topological network models, and a corresponding reference implementation VIOLA (VIsualization Of Layer Activity). The software is a lightweight, open-source, web-based and platform-independent application combining and adapting modern interactive visualization paradigms, such as coordinated multiple views, for massively parallel neurophysiological data. For a use-case demonstration we consider spiking activity data of a two-population, layered point-neuron network model subject to a spatially confined excitation originating from an external population. With the multiple coordinated views, an explorative and qualitative assessment of the spatiotemporal features of neuronal activity can be performed upfront of a detailed quantitative data analysis of specific aspects of the data. Furthermore, ongoing efforts including the European Human Brain Project aim at providing online user portals for integrated model development, simulation, analysis and provenance tracking, wherein interactive visual analysis tools are one component. Browser-compatible, web-technology based solutions are therefore required. Within this scope, with VIOLA we provide a first prototype.Comment: 38 pages, 10 figures, 3 table

Development of practical vocational training class making use of virtual reality-based simulation system and augmented reality technologies

Virtual reality (VR) refers to the technologies creating a virtual environment to provide users a sensory simulation of the environment being presented. In Hong Kong Institute of Vocational Education (IVE), we are in the process of developing a VR-based simulation system having four screens surrounding users to simulate an immersive environment. This application is commonly known as the cave automatic virtual environment (CAVE). The objective of our VR-based simulation system project is to apply the virtual reality and the augmented reality (AR) technologies for practical training in vocational education and training (VET). Our system is used for various training programs in the engineering areas. These include simulation of any workspaces for operations and maintenance training in electrical and mechanical services. Workspace training is important and beneficial to VET students in addition to practical training in school settings. Meanwhile, some workspaces are full of danger and severe casualty can be resulted if inappropriate operations are performed. Our VRbased simulation system manages to provide a solution to complement the shortfalls of workplace training and ensure that students can acquire a range of skills including safety operations under various environments. In this paper, we introduce our design of a class making use of the CAVE system and augmented reality technology. The class aims at providing training for VET students to perform inspection and maintenance procedures in a virtual engine plant room. The class was found to be educational and managed to promote the skill development among students

VisNEST - Interactive analysis of neural activity data

The aim of computational neuroscience is to gain insight into the dynamics and functionality of the nervous system by means of modeling and simulation. Current research leverages the power of High Performance Computing facilities to enable multi-scale simulations capturing both low-level neural activity and large-scalce interactions between brain regions. In this paper, we describe an interactive analysis tool that enables neuroscientists to explore data from such simulations. One of the driving challenges behind this work is the integration of macroscopic data at the level of brain regions with microscopic simulation results, such as the activity of individual neurons. While researchers validate their findings mainly by visualizing these data in a non-interactive fashion, state-of-the-art visualizations, tailored to the scientific question yet sufficiently general to accommodate different types of models, enable such analyses to be performed more efficiently. This work describes several visualization designs, conceived in close collaboration with domain experts, for the analysis of network models. We primarily focus on the exploration of neural activity data, inspecting connectivity of brain regions and populations, and visualizing activity flux across regions. We demonstrate the effectiveness of our approach in a case study conducted with domain experts