Publications

Simulation models in many scientific fields can have non-unique solutions or unique solutions which can be difficult to find. Moreover, in evolving systems, unique ?nal state solutions can be reached by multiple different trajectories. Neuroscience is no exception. Often, neural network models are subject to parameter fitting to obtain desirable output comparable to experimental data. Parameter fitting without sufficient constraints and a systematic exploration of the possible solution space can lead to conclusions valid only around local minima or around non-minima. To address this issue, we have developed an interactive tool for visualizing and steering parameters in neural network simulation models. In this work, we focus particularly on connectivity generation, since ?nding suitable connectivity configurations for neural network models constitutes a complex parameter search scenario. The development of the tool has been guided by several use cases—the tool allows researchers to steer the parameters of the connectivity generation during the simulation, thus quickly growing networks composed of multiple populations with a targeted mean activity. The flexibility of the software allows scientists to explore other connectivity and neuron variables apart from the ones presented as use cases. With this tool, we enable an interactive exploration of parameter spaces and a better understanding of neural network models and grapple with the crucial problem of non-unique network solutions and trajectories. In addition, we observe a reduction in turn around times for the assessment of these models, due to interactive visualization while the simulation is computed.

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 speci?c aspects of the data. Interactive multi-view analysis therefore assists existing data Analysis workflows. Furthermore,ongoingeffortsincludingtheEuropeanHumanBrainProjectaim 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.

Life and health sciences are key application areas for immersive analytics. This spans a broad range including medicine (e.g., investigations in tumour boards), pharmacology (e.g., research of adverse drug reactions), biology (e.g., immersive virtual cells) and ecology (e.g., analytics of animal behaviour). We present a brief overview of general applications of immersive analytics in the life and health sciences, and present a number of applications in detail, such as immersive analytics in structural biology, in medical image analytics, in neurosciences, in epidemiology, in biological network analysis and for virtual cells.

This chapter overviews the application of immersive analytics to simulations of built environments through three distinct case studies. The first case study examines an immersive analytics approach based upon the concept of “Virtual Production Intelligence” for virtual prototyping tools throughout the planning phase of complete production sites. The second study addresses the 3D simulation of an extensive urban area and the attendant immersive analytic considerations in an interactive model of a sustainable city. The third study reviews how immersive analytic overlays have been applied for virtual heritage in the reconstruction and crowd simulation of the medieval Cambodian temple complex of Angkor Wat.

We introduce a novel methodology to study peer effects. Using virtual reality technology, we create a naturalistic work setting in an immersive virtual environment where we embed a computer-generated virtual human as the co-worker of a human subject, both performing a sorting task at a conveyor belt. In our setup, subjects observe the virtual peer, while the virtual human is not observing them. In two treatments, human subjects observe either a low productive or a high productive virtual peer. We find that human subjects rate their presence feeling of \being there" in the immersive virtual environment as natural. Subjects also recognize that virtual peers in our two treatments showed different productivities. We do not find a general treatment effect on productivity. However, we find that competitive subjects display higher performance when they are in the presence of a highly productive peer - compared to when they observe a low productive peer. We use tracking data to learn about the subjects' body movements. Analyzing hand and head data, we show that competitive subjects are more careful in the sorting task than non-competitive subjects. We also discuss some methodological issues related to virtual reality experiments.

In the simulation of manufacturing processes, complex models are used to examine process properties. To save computation time, so-called metamodels serve as surrogates for the original models. Metamodels are inherently difficult to interpret, because they resemble multi-dimensional functions f : Rn -> Rm that map configuration parameters to production criteria. We propose a multi-view visualization application called memoSlice that composes several visualization techniques, specially adapted to the analysis of metamodels. With our application, we enable users to improve their understanding of a metamodel, but also to easily optimize processes. We put special attention on providing a high level of interactivity by realizing specialized parallelization techniques to provide timely feedback on user interactions. In this paper we outline these parallelization techniques and demonstrate their effectivity by means of micro and high level measurements.

Personal space (PS), the flexible protective zone maintained around oneself, is a key element of everyday social interactions. It, e.g., affects people's interpersonal distance and is thus largely involved when navigating through social environments. However, the PS is regulated dynamically, its size depends on numerous social and personal characteristics and its violation evokes different levels of discomfort and physiological arousal. Thus, gaining more insight into this phenomenon is important.

We contribute to the PS investigations by presenting the results of a controlled experiment in a CAVE, focusing on German males in the age of 18 to 30 years. The PS preferences of 27 participants have been sampled while they were approached by either a single embodied, computer-controlled virtual agent (VA) or by a group of three VAs. In order to investigate the influence of a VA's emotions, we altered their facial expression between angry and happy. Our results indicate that the emotion as well as the number of VAs approaching influence the PS: larger distances are chosen to angry VAs compared to happy ones; single VAs are allowed closer compared to the group. Thus, our study is a foundation for social and behavioral studies investigating PS preferences.

In virtual environments, the space that can be explored by real walking is limited by the size of the tracked area. To enable unimpeded walking through large virtual spaces in small real-world surroundings, redirection techniques are used. These unnoticeably manipulate the user’s virtual walking trajectory. It is important to know how strongly such techniques can be applied without the user noticing the manipulation—or getting cybersick. Previously, this was estimated by measuring a detection threshold (DT) in highly-controlled psychophysical studies, which experimentally isolate the effect but do not aim for perceived immersion in the context of VR applications. While these studies suggest that only relatively low degrees of manipulation are tolerable, we claim that, besides establishing detection thresholds, it is important to know when the user’s immersion breaks. We hypothesize that the degree of unnoticed manipulation is significantly different from the detection threshold when the user is immersed in a task. We conducted three studies: a) to devise an experimental paradigm to measure the threshold of limited immersion (TLI), b) to measure the TLI for slowly decreasing and increasing rotation gains, and c) to establish a baseline of cybersickness for our experimental setup. For rotation gains greater than 1.0, we found that immersion breaks quite late after the gain is detectable. However, for gains lesser than 1.0, some users reported a break of immersion even before established detection thresholds were reached. Apparently, the developed metric measures an additional quality of user experience. This article contributes to the development of effective spatial compression methods by utilizing the break of immersion as a benchmark for redirection techniques.

Neuroscientists want to inspect the data their simulations are producing while these are still running. This will on the one hand save them time waiting for results and therefore insight. On the other, it will allow for more efficient use of CPU time if the simulations are being run on supercomputers. If they had access to the data being generated, neuroscientists could monitor it and take counter-actions, e.g., parameter adjustments, should the simulation deviate too much from in-vivo observations or get stuck.

As a first step toward this goal, we devise an in situ pipeline tailored to the neuroscientific use case. It is capable of recording and transferring simulation data to an analysis/visualization process, while the simulation is still running. The developed libraries are made publicly available as open source projects. We provide a proof-of-concept integration, coupling the neuronal simulator NEST to basic 2D and 3D visualization.

During free exploration of an unknown virtual scene, users often miss important parts, leading to incorrect or incomplete environment knowledge and a potential negative impact on performance in later tasks. This is addressed by wayfinding aids such as compasses, maps, or trails, and automated exploration schemes such as guided tours. However, these approaches either do not actually ensure exploration success or take away control from the user.

Therefore, we present an interactive assistance interface to support exploration that guides users to interesting and unvisited parts of the scene upon request, supplementing their own, free exploration. It is based on an automated analysis of object visibility and viewpoint quality and is therefore applicable to a wide range of scenes without human supervision or manual input. In a user study, we found that the approach improves users' knowledge of the environment, leads to a more complete exploration of the scene, and is also subjectively helpful and easy to use.

When interacting and communicating with virtual agents in immersive environments, the agents’ behavior should be believable and authentic. Thereby, one important aspect is a convincing auralizations of their speech. In this work-in progress paper a study design to evaluate the effect of adding directivity to speech sound source on the perceived social presence of a virtual agent is presented. Therefore, we describe the study design and discuss first results of a prestudy as well as consequential improvements of the design.

Various factors influence the degree of cybersickness a user can suffer in an immersive virtual environment, some of which can be controlled without adapting the virtual environment itself. When using HMDs, one example is the size of the field of view. However, the degree to which factors like this can be manipulated without affecting the user negatively in other ways is limited. Another prominent characteristic of cybersickness is that it affects individuals very differently. Therefore, to account for both the possible disruptive nature of alleviating factors and the high interpersonal variance, a promising approach may be to intervene only in cases where users experience discomfort symptoms, and only as much as necessary. Thus, we conducted a first experiment, where the field of view was decreased when people feel uncomfortable, to evaluate the possible positive impact on sickness and negative influence on presence. While we found no significant evidence for any of these possible effects, interesting further results and observations were made.

The concept of personal space is a key element of social interactions. As such, it is a recurring subject of investigations in the context of research on proxemics. Using virtual-reality-based experiments, we contribute to this area by evaluating the direct effects of emotional expressions of an approaching virtual agent on an individual’s behavioral and physiological responses. As a pilot study focusing on the emotion expressed solely by facial expressions gave promising results, we now present a study design to gain more insight.

Fluid artwork refers to works of art based on the aesthetics of fluid motion, such as smoke photography, ink injection into water, and paper marbling. Inspired by such types of art, we created Fluid Sketching as a novel medium for creating 3D fluid artwork in immersive virtual environments. It allows artists to draw 3D fluid-like sketches and manipulate them via six degrees of freedom input devices. Different sets of brush strokes are available, varying different characteristics of the fluid. Because of fluid's nature, the diffusion of the drawn fluid sketch is animated, and artists have control over altering the fluid properties and stopping the diffusion process whenever they are satisfied with the current result. Furthermore, they can shape the drawn sketch by directly interacting with it, either with their hand or by blowing into the fluid. We rely on particle advection via curl-noise as a fast procedural method for animating the fluid flow.

In this work, we describe a hybrid, hand-based interaction metaphor that makes remote and close objects in an HMD-based immersive virtual environment (IVE) seamlessly accessible. To accomplish this, different existing techniques, such as go-go and HOMER, were combined in a way that aims for generality, intuitiveness, uniformity, and speed. A technique like this is one prerequisite for a successful integration of IVEs to professional everyday applications, such as data analysis workflows.

Feature tracking is a method of time-varying data analysis. Due to the complexity of the underlying problem, different feature tracking algorithms have different levels of correctness in certain use cases. However, there is no efficient way to evaluate their performance on simulation data since there is no ground-truth easily obtainable. Synthetic data is a way to ensure a minimum level of correctness, though there are limits to their expressiveness when comparing the results to simulation data. To close this gap, we calculate a synthetic data set and use its results to extract a hypothesis about the algorithm performance that we can apply to simulation data.

Cybersickness poses a crucial threat to applications in the domain of Virtual Reality. Yet, its predictors are insufficiently explored when redirection techniques are applied. Those techniques let users explore large virtual spaces by natural walking in a smaller tracked space. This is achieved by unnoticeably manipulating the user’s virtual walking trajectory. Unfortunately, this also makes the application more prone to cause Cybersickness. We conducted a user study with a semi-structured interview to get quantitative and qualitative insights into this domain. Results show that Cybersickness arises, but also eases ten minutes after the exposure. Quantitative results indicate that a tolerance towards Cybersickness might be related to self-efficacy constructs and therefore learnable or trainable, while qualitative results indicate that users’ endurance of Cybersickness is dependent on symptom factors such as intensity and duration, as well as factors of usage context and motivation. The role of Cybersickness in Virtual Reality environments is discussed in terms of the applicability of redirected walking techniques.

Being able to inspect neuronal network simulations while they are running provides new research strategies to neuroscientists as it enables them to perform actions like parameter adjustments in case the simulation performs unexpectedly. This can also save compute resources when such simulations are run on large supercomputers as errors can be detected and corrected earlier saving valuable compute time. This talk presents a prototypical pipeline that enables in-situ analysis and visualization of running simulations.

In this interactive demo, we present our Fluid Sketching application as an innovative virtual reality-based interpretation of traditional marbling art. By using a particle-based simulation combined with natural, spatial, and multi-modal interaction techniques, we create and extend the original artistic work to build a comprehensive interactive experience. With the interactive demo of Fluid Sketching during Mensch und Computer 2018, we aim at increasing the awareness of paper marbling as traditional type of art and demonstrating the potential of virtual reality as new and innovative digital and artistic medium.

Personal Space (PS) is regulated dynamically by choosing an appropriate interpersonal distance when navigating through social environments. This key element in social interactions is influenced by numerous social and personal characteristics, e.g., the nature of the relationship between the interaction partners and the other’s sex and age. Moreover, affective contexts and expressions of interaction partners influence PS preferences, evident, e.g., in larger distances to others in threatening situations or when confronted with angry-looking individuals. Given the prominent role of emotional expressions in our everyday social interactions, we investigate how emotions affect PS adaptions.

Real walking is the most natural and intuitive way to navigate the world around us. In Virtual Reality, the limited tracking area of commercially available systems typically does not match the size of the virtual environment we wish to explore. Spatial compression methods enable the user to walk further in the virtual environment than the real tracking bounds permit. This demo gives a glimpse into our ongoing research on spatial compression in VR. Visitors can walk through a realistic model of the Aachen Cathedral within a room-sized tracking area.