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

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. In order to cover the surface area captured by today's experimental techniques and to achieve sufficient self-consistency, such models contain millions of nerve cells. 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 incorporating distance-dependent connectivity 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. Interactive multi-view analysis therefore assists existing data analysis workflows. 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

General Chair Message

It is our great pleasure to welcome you to the 25th IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR), the premiere international conference focused on research in these domains! This year the name of the conference changed since the highly successful 12-year IEEE Symposium on 3D User Interfaces is brought back into the main VR conference. It is a tremendous honor to host the conference in Reutlingen on its first return to Germany since 2005. Reutlingen is situated nicely with respect to our research institutes, the city has the charm of a southern German town, and the recently built (2013) Stadthalle and concert venue has a professional team that is experienced in conferences highlighting innovation in technology. This venue has enabled us to create a large program both in scientific content and in terms of demonstration and exhibit space

General chair message

It is our great pleasure to welcome you to the 25th IEEE Conference on Virtual Reality and 3D User Interfaces (IEEE VR), the premiere international conference focused on research in these domains! This year the name of the conference changed since the highly successful 12-year IEEE Symposium on 3D User Interfaces is brought back into the main VR conference. It is a tremendous honor to host the conference in Reutlingen on its first return to Germany since 2005. Reutlingen is situated nicely with respect to our research institutes, the city has the charm of a southern German town, and the recently built (2013) Stadthalle and concert venue has a professional team that is experienced in conferences highlighting innovation in technology. This venue has enabled us to create a large program both in scientific content and in terms of demonstration and exhibit space

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

Neuronal network models and corresponding computer simulations areinvaluable tools to aid the interpretation of the relationship betweenneuron properties, connectivity and measured activity in corticaltissue. Spatiotemporal patterns of activity propagating across thecortical surface as observed experimentally can for example be describedby neuronal network models with layered geometry and distance-dependentconnectivity. In order to cover the surface area captured by today'sexperimental techniques and to achieve sufficient self-consistency,such models contain millions of nerve cells. The interpretation ofthe resulting stream of multi-modal and multi-dimensional simulationdata calls for integrating interactive visualization steps into existingsimulation-analysis workflows. Here, we present a set of interactivevisualization concepts called views for the visual analysis of activitydata in topological network models, and a corresponding referenceimplementation VIOLA (VIsualization Of Layer Activity). The softwareis a lightweight, open-source, web-based and platform-independentapplication combining and adapting modern interactive visualizationparadigms, such as coordinated multiple views, for massively parallelneurophysiological data. For a use-case demonstration we considerspiking activity data of a two-population, layered point-neuron networkmodel incorporating distance-dependent connectivity subject to a spatiallyconfined excitation originating from an external population. Withthe multiple coordinated views, an explorative and qualitative assessmentof the spatiotemporal features of neuronal activity can be performedupfront of a detailed quantitative data analysis of specific aspectsof the data. Interactive multi-view analysis therefore assists existingdata analysis workflows. Furthermore, ongoing efforts including theEuropean Human Brain Project aim at providing online user portalsfor integrated model development, simulation, analysis and provenancetracking, 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

Integrating Visualizations into Modeling NEST Simulations

Modeling large-scale spiking neural networks showing realistic biological behavior in their dynamics is a complex and tedious task. Since these networks consist of millions of interconnected neurons, their simulation produces an immense amount of data. In recent years it has become possible to simulate even larger networks. However, solutions to assist researchers in understanding the simulation's complex emergent behavior by means of visualization are still lacking. While developing tools to partially fill this gap, we encountered the challenge to integrate these tools easily into the neuroscientists' daily workflow. To understand what makes this so challenging, we looked into the workflows of our collaborators and analyzed how they use the visualizations to solve their daily problems. We identified two major issues: first, the analysis process can rapidly change focus which requires to switch the visualization tool that assists in the current problem domain. Second, because of the heterogeneous data that results from simulations, researchers want to relate data to investigate these effectively. Since a monolithic application model, processing and visualizing all data modalities and reflecting all combinations of possible workflows in a holistic way, is most likely impossible to develop and to maintain, a software architecture that offers specialized visualization tools that run simultaneously and can be linked together to reflect the current workflow, is a more feasible approach. To this end, we have developed a software architecture that allows neuroscientists to integrate visualization tools more closely into the modeling tasks. In addition, it forms the basis for semantic linking of different visualizations to reflect the current workflow. In this paper, we present this architecture and substantiate the usefulness of our approach by common use cases we encountered in our collaborative work

Multiscale approach to explore the relationships between connectivity and function in whole brain simulations

To better understand the relationship between connectivity and function in the brain at different scales, in this work we show the results of using point-neuron network simulations to complement connectivity information from whole brain simulations based on a dynamic neuron mass model. In our multiscale approach, we simulate a whole brain parcellated into 68 regions where each region is modeled as a dynamic neuron mass, and in parallel, we also model each region as small 200 point-neuron populations in NEST. Structural plasticity in NEST is then used to calculate inner connectivity of each region with the aid of an interactive tool designed for visualizing and steering the algorithm. Using this approach, the fitting and parameter space exploration times are reduced and a new way to explore the impact of connectivity in function at different scales is presented

Using Directed Variance to Identify Meaningful Views in Call-path Performance Profiles

Understanding the performance behaviour of massively parallel high-performance computing (HPC) applications based on call-path performance profiles is a time-consuming task. In this paper, we introduce the concept of directed variance in order to help analysts find performance bottlenecks in massive performance data and in the end optimize the application. According to HPC experts' requirements, our technique automatically detects severe parts in the data that expose large variation in an application's performance behaviour across system resources. Previously known variations are effectively filtered out. Analysts are thus guided through a reduced search space towards regions of interest for detailed examination in a 3D visualization. We demonstrate the effectiveness of our approach using performance data of common benchmark codes as well as from actively developed production codes