Tobias Rick

Probabilistic fibre tract analysis of cytoarchitectonically defined human inferior parietal lobule areas reveals similarities to macaques

The human inferior parietal lobule (IPL) is a multimodal brain region, subdivided in several cytoarchitectonic areas which are involved in neural networks related to spatial attention, language, and higher motor processing. Tracer studies in macaques revealed differential connectivity patterns of IPL areas as the respective structural basis. Evidence for comparable differential fibre tracts of human IPL is lacking. Here, anatomical connectivity of five cytoarchitectonic human IPL areas to 64 cortical targets was investigated using probabilistic tractography. Connection likelihood was assessed by evaluating the number of traces between seed and target against the distribution of traces from that seed to voxels in the same distance as the target. The main fibre tract pattern shifted gradually from rostral to caudal IPL: Rostral areas were predominantly connected to somatosensory and superior parietal areas while caudal areas more strongly connected with auditory, anterior temporal and higher visual cortices. All IPL areas were strongly connected with inferior frontal, insular and posterior temporal areas. These results showed striking similarities with connectivity patterns in macaques, providing further evidence for possible homologies between these two species. This shift in fibre tract pattern supports a differential functional involvement of rostral (higher motor functions) and caudal IPL (spatial attention), with probable overlapping language involvement. The differential functional involvement of IPL areas was further supported by hemispheric asymmetries of connection patterns which showed left-right differences especially with regard to connections to sensorimotor, inferior frontal and temporal areas.

Fast Edge-Diffraction-Based Radio Wave Propagation Model for Graphics Hardware

Fast radio wave propagation predictions are of tremendous interest, e.g., for planning and optimisation of cellular radio networks. We propose the use of ordinary graphics cards and specialized algorithms to achieve extremely fast predictions. We present a ray-optical approach for wave diffraction at building edges into street canyons, exploiting the programming model of graphics cards. More than twenty predictions per second are achieved in a 7 km2 urban area with a mean squared error of less than 7 dB when compared with measurements.

Accelerating Radio Wave Propagation Predictions by Implementation on Graphics Hardware

Fast radio wave propagation predictions are of tremendous interest, e.g., for planning and optimization of cellular radio networks. We propose the use of ordinary graphics cards and specialized algorithms to achieve extremely fast predictions. Our implementation of the empirical COST-Walfisch-Ikegami model allows the computation of several hundred predictions in one second in a 7 km urban area. Further, we present a ray-optical approach exploiting the programming model of graphics cards. This algorithm combines fast computation times with high accuracy.

Comparing steering-based travel techniques for search tasks in a CAVE

We present a novel bimanual body-directed travel technique, PenguFly (PF), and compare it with two standard travel-by-pointing techniques by conducting a between-subject experiment in a CAVE. In PF, the positions of the users head and hands are projected onto the ground, and travel direction and speed are computed based on direction and magnitude of the vector from the midpoint of the projected hand positions to the projected head position. The two baseline conditions both use a single hand to control the direction, with speed controlled discretely by button pushes with the same hand in one case, and continuously by the distance between the hands in the other case. Users were asked to travel through a simple virtual world and collect virtual coins within a set time. We found no significant differences between travel conditions for reported presence or usability, but a significant increase in nausea with PF. Total travel distance was significantly higher for the baseline condition with discrete speed selection, whereas travel accuracy in terms of coin-to-distance ratio was higher with PF.

Efficient Rasterization for Outdoor Radio Wave Propagation

Conventional beam tracing can be used for solving global illumination problems. It is an efficient algorithm and performs very well when implemented on the GPU. This allows us to apply the algorithm in a novel way to the problem of radio wave propagation. The simulation of radio waves is conceptually analogous to the problem of light transport. We use a custom, parallel rasterization pipeline for creation and evaluation of the beams. We implement a subset of a standard 3D rasterization pipeline entirely on the GPU, supporting 2D and 3D frame buffers for output. Our algorithm can provide a detailed description of complex radio channel characteristics like propagation losses and the spread of arriving signals over time (delay spread). Those are essential for the planning of communication systems required by mobile network operators. For validation, we compare our simulation results with measurements from a real-world network. Furthermore, we account for characteristics of different propagation environments and estimate the influence of unknown components like traffic or vegetation by adapting model parameters to measurements.

Evaluating a Visualization of Uncertainty in Probabilistic Tractography

In this paper we evaluate a visualization approach for representing uncertainty information in probabilistic fiber pathways in the human brain. We employ a semi-transparent volume rendering method where probabilities of fiber tracts are conveyed by colors and opacities (cf. Figure 1). Anatomic orientation is provided by placing anatomic landmarks in form of cortial or functional defined brain areas. In order to quantify the effectiveness of our approach we have conducted a formal user study concerning preferred anatomic context information and coloring of fiber tracts.

Visualization of Probabilistic Fiber Tracts in Virtual Reality

Understanding the connectivity structure of the human brain is a fundamental prerequisite for the treatment of psychiatric or neurological diseases. Probabilistic tractography has become an established method to account for the inherent uncertainties of the actual course of fiber bundles in magnetic resonance imaging data. This paper presents a visualization system that addresses the assessment of fiber probabilities in relation to anatomical landmarks. We employ real-time transparent rendering strategy to display fiber tracts within their structural context in a virtual environment. Thereby, we not only emphasize spatial patterns but furthermore allow an interactive control over the amount of visible anatomical information.

Simulation of radio wave propagation by beam tracing

Beam tracing can be used for solving global illumination problems. It is an efficient algorithm, and performs very well when implemented on the GPU. This allows us to apply the algorithm in a novel way to the problem of radio wave propagation. The simulation of radio waves is conceptually analogous to the problem of light transport. However, their wavelengths are of proportions similar to that of the environment. At such frequencies, waves that bend around corners due to diffraction are becoming an important propagation effect. In this paper we present a method which integrates diffraction, on top of the usual effects related to global illumination like reflection, into our beam tracing algorithm. We use a custom, parallel rasterization pipeline for creation and evaluation of the beams. Our algorithm can provide a detailed description of complex radio channel characteristics like propagation losses and the spread of arriving signals over time (delay spread). Those are essential for the planning of communication systems required by mobile network operators. For validation, we compare our simulation results with measurements from a real world network.

Accelerating Radio Wave Propagation Algorithms by Implementation on Graphics Hardware

Radio wave propagation prediction is a fundamental prerequisite for planning, analysis and optimization of radio networks. For instance coverage analysis, interference estimation or channel and power allocation all rely on propagation predictions. In wireless communication networks optimal antenna sites are determined by either conducting a series of expensive propagation measurements or by estimating field strengths numerically. In order to cope with the vast amount of different configurations to select the best candidate from and to avoid expensive measurement campaigns, numerical predictions have to be both accurate and fast. In this chapter we focus on accelerating techniques for radio wave propagation algorithms in dense urban environments with the target frequency range of common mobile communication systems, i.e., several hundred MHz up to few GHz. One important aspect in radio wave propagation is the prediction of the mean received signal strength which can be simulated by taking complex interactions between radio waves and the propagation environment (see Figure 1) into account. Thus, the simulation of radio waves for propagation predictions becomes a computationally intensive task. A promising approach is the use of ordinary graphics cards, nowadays available in every personal computer. With over 1000 Gigaflops, modern graphics hardware offers the computational power of a small-sized supercomputer. This is achieved by a strict parallel many-core architecture which can be accessed by a high level of programmability. The main challenge of utilizing graphics hardware for scientific computations is to trick the graphics processors into general purpose computing by casting problems as graphics: Input data is transformed into images and algorithms are turned into image synthesis. However, in the last couple of years a growing support of so-called ”General Purpose Computation on Graphics Hardware” has led to recent changes in this architecture, allowing more common ways of parallel programming. Much effort and interest has been put on the acceleration of ray optical approaches, since most ray tracing algorithms tend to be computational intensive and exhibit run times up to hours. Therefore, we focus on the efficient implementation of wave guiding effects on graphics hardware. Among the most time consuming tasks in ray tracing is the problem of visibility between objects, i.e., the identification of all possible interaction sources for diffracted or reflected propagation rays. The algorithms we will present here are specifically designed to reduce the computational cost of the visibility computations by exploiting special features of the graphics card.

GPU implementation of 3D object selection by conic volume techniques in virtual environments

In this paper we present a GPU implementation to accurately select 3D objects based on their silhouettes by a pointing device with six degrees of freedom (6DOF) in a virtual environment (VE). We adapt a 2D picking metaphor to 3D selection in VEs by changing the projection and view matrices according to the position and orientation of a 6DOF pointing device and rendering a conic selection volume to an off-screen pixel buffer. This method works for triangulated as well as volume rendered objects, no explicit geometric representation is required.