Gert Pfurtscheller

Bio: Gert Pfurtscheller is an academic researcher from Graz University of Technology. The author has contributed to research in topics: Brain–computer interface & Electroencephalography. The author has an hindex of 117, co-authored 507 publications receiving 62873 citations. Previous affiliations of Gert Pfurtscheller include University of Graz.

Combining BCI and Virtual Reality: Scouting Virtual Worlds

Abstract: 23.1 Abstract A brain-computer interface (BCI) is a closed-loop system with feedback as one important component. Dependent on the BCI application either to establish communication in patients with severe motor paralysis, to control neuroprosthesis, or to perform neurofeed-back, information is visually fed back to the user about success or failure of the intended act. One way to realize feedback is the use of virtual reality (VR). In this chapter, an overview is given of BCI-based control of VR. In addition, four examples are reported in

“Switch-Off” of Respiratory Sinus Arrhythmia Can Occur in a Minority of Subjects During Functional Magnetic Resonance Imaging (fMRI)

Abstract: A group of 23 healthy scanner naive participants of a functional magnetic resonance imaging (fMRI) study with increased state anxiety exhibited 0.1 Hz oscillations in blood-oxygenation-level-dependent (BOLD) signals, heart rate (HR) beat-to-beat intervals (RRI) and respiration. The goal of the present paper is to explore slow oscillations in respiration and RRI and their phase-coupling by applying the dynamic "wave-by-wave" analysis. Five participants with either high or moderate levels of fMRI-related anxiety (age 23.8 ± 3.3y) were found with at least one bulk of consecutive breathing waves with a respiration rate between 6 to 9 breaths/min in a 5-min resting state. The following results were obtained: (i) Breathing oscillations with dominant frequencies at 0.1 Hz and 0.15 Hz displayed a 1:1 coupling with RRI. (ii) Inspiration time was significantly longer than expiration time. (iii) RRI minima (start of HR decrease) coincided with the early inspiration, and RRI maxima (start of HR increase) coincided with the late inspiration. (iv) RRI rhythm led over the respiratory rhythm. This phase-coupling pattern is quite contrary to typical respiratory sinus arrhythmia where HR increases during inspiration and decreases during expiration.

EEG-Based Brain-Computer Interface System

Abstract: A brain computer interface (BCI) transforms electrophysiological signals originating from the human brain into commands that control devices or applications. In this way, a BCI provides a new nonmuscular communication channel, which can be extremely useful for people with severe neuromuscular disorders such as amyotrophic lateral sclerosis and brainstem stroke. The immediate goal of our current research is to provide these users with an opportunity to communicate with their environment. Future applications also include the field of multimedia and virtual reality. Present day BCIs use a variety of electrophysiological signals such as slow cortical potentials, evoked potentials (P300), oscillatory activity recorded from scalp or subdural electrodes, and cortical neuronal activity recorded from implanted electrodes. EEG is by far the most frequently used input source, because it is readily available and noninvasive. The poor signal-to-noise ratio of scalp–recorded signals requires the application of advanced signal processing methods. This article outlines and explains the current approaches and methods used in BCI research with emphasis on the signal processing part of the system, consisting of preprocessing, feature extraction, and classification. However, the success of a BCI depends not only on the methodologies applied, but also on the capability of the user to develop and maintain the skill to produce the brain patterns employed by the BCI. Therefore, the interaction between the BCI system and the user, in terms of adaptation and learning, is a challenging aspect of any BCI development and application. Keywords: brain-computer interface; EEG; signal processing; pattern recognition; feature extraction

Verification of a Central Pacemaker in Brain Stem by Phase-Coupling Analysis Between HR Interval- and BOLD-Oscillations in the 0.10–0.15 Hz Frequency Band

Abstract: The origin of slow intrinsic oscillations in resting states of functional magnetic resonance imaging (fMRI) signals is still a matter of debate. The present study aims to test the hypothesis that slow blood oxygenation level-dependent (BOLD) oscillations with frequency components greater than 0.10 Hz result from a central neural pacemaker located in the brain stem. We predict that a central oscillator modulates cardiac beat-to-beat interval (RRI) fluctuations rapidly, with only a short neural lag around 0.3 s. Spontaneous BOLD fluctuations in the brain stem, however, are considerably delayed due to the hemodynamic response time of about ∼2-3 s. In order to test these predictions, we analyzed the time delay between slow RRI oscillations from thorax and BOLD oscillations in the brain stem by calculating the phase locking value (PLV). Our findings show a significant time delay of 2.2 ± 0.2 s between RRI and BOLD signals in 12 out of 23 (50%) participants in axial slices of the pons/brain stem. Adding the neural lag of 0.3 s to the observed lag of 2.2 s we obtain 2.5 s, which is the time between neural activity increase and BOLD increase, termed neuro-BOLD coupling. Note, this time window for neuro-BOLD coupling in awake humans is surprisingly of similar size as in awake head-fixed adult mice (Mateo et al., 2017).

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

Principles of Neural Science

Abstract: I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or