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Introduction
High-Performance Computing, Scientific computing, Biomedical signal processing,
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Publications
Publications (124)
Poxviruses are among the largest double-stranded DNA viruses, with members such as variola virus, monkeypox virus and the vaccination strain vaccinia virus (VACV). Knowledge about the structural proteins that form the viral core has remained sparse. While major core proteins have been annotated via indirect experimental evidence, their structures h...
Poxviruses are among the largest double-stranded DNA viruses with members such as Variola virus, Monkeypox virus and the famous vaccination strain Vaccinia virus (VACV). Knowledge about the structural proteins that form the viral core, found in all infectious poxvirus forms, has remained sparse. While major core proteins have been annotated via ind...
Pattern separation is a fundamental brain computation that converts small differences in input patterns into large differences in output patterns. Several synaptic mechanisms of pattern separation have been proposed, including code expansion, inhibition and plasticity; however, which of these mechanisms play a role in the entorhinal cortex (EC)–den...
Ever since the first publication of the standard communication protocol for computer-assisted electrocardiography (SCP-ECG), prENV 1064, in 1993, by the European Committee for Standardization (CEN), SCP-ECG has become a leading example in health informatics, enabling open, secure, and well-documented digital data exchange at a low cost, for quick a...
Background
To understand information coding in single neurons, it is necessary to analyze subthreshold synaptic events, action potentials (APs), and their interrelation in different behavioral states. However, detecting excitatory postsynaptic potentials (EPSPs) or currents (EPSCs) in behaving animals remains challenging, because of unfavorable sig...
Graphical Abstract Highlights d >50% of hippocampal GCs are active, but activity level varies over a wide range. 5% of GCs are place cells, but 50% receive spatially tuned synaptic input d Mixed input of GCs constrains models of grid-place code conversion d GC firing is controlled by intrinsic excitability In Brief Zhang et al. simultaneously measu...
To understand the mechanisms of information coding in single neurons, it is necessary to analyze subthreshold synaptic events, action potentials (APs), and the interrelation between these two forms of activity in different behavioral states. However, detecting excitatory postsynaptic potentials (EPSPs) or currents (EPSCs) in awake, behaving animals...
Abstracts of the Austrian High-Performance-Computing meeting 2020
Pattern separation is a fundamental brain computation that converts small differences in synaptic input patterns into large differences in action potential (AP) output patterns. Pattern separation plays a key role in the dentate gyrus, enabling the efficient storage and recall of memories in downstream hippocampal CA3 networks. Several mechanisms f...
Background:
Standards have become available to share semantically encoded vital parameters from medical devices, as required for example by personal healthcare records. Standardised sharing of biosignal data largely remains open.
Objectives:
The goal of this work is to explore available biosignal file format and data exchange standards and profi...
The hippocampal CA3 region plays a key role in learning and memory. Recurrent CA3-CA3 synapses are thought to be the subcellular substrate of pattern completion. However, the synaptic mechanisms of this network computation remain enigmatic. To investigate these mechanisms, we combined functional connectivity analysis with network modeling. Simultan...
Intracellular electrophysiological recordings provide crucial insights into elementary neuronal signals such as action potentials and synaptic currents. Analyzing and interpreting these signals is essential for a quantitative understanding of neuronal information processing, and requires both fast data visualization and ready access to complex anal...
To search for a target in a complex environment is an everyday behavior that ends with finding the target. When we search for two identical targets, however, we must continue the search after finding the first target and memorize its location. We used fixation-related potentials to investigate the neural correlates of different stages of the search...
This section provides additional analyses using different baselines and controlled saccade amplitude.
Fixation-related potentials (FRPs) for distractor fixations before and after the first target fixation. A subset of data with comparable saccade amplitudes and a baseline period before display onset was used.
Stimfit is a free cross-platform software package for viewing and analyzing electrophysiological data. It supports most standard file types for cellular neurophysiology and other biomedical formats. Its analysis algorithms have been used and validated in several experimental laboratories. Its embedded Python scripting interface makes Stimfit highly...
Spontaneous postsynaptic currents (PSCs) provide key information about the mechanisms of synaptic transmission and the activity modes of neuronal networks. However, detecting spontaneous PSCs in vitro and in vivo has been challenging, because of the small amplitude, the variable kinetics, and the undefined time of generation of these events. Here,...
The BCI competition IV stands in the tradition of prior BCI competitions that aim to provide high quality neuroscientific data for open access to the scientific community. As experienced already in prior competitions not only scientists from the narrow field of BCI compete, but scholars with a broad variety of backgrounds and nationalities. They in...
Parkinson’s disease (PD) is often accompanied by dysfunctions of the autonomous nervous system (ANS). Heart rate variability (HRV) may impact on sleep regulation with regard to sympatho-vagal balance and sleep stages. This study analyzed possible differences in ANS activity between PD patients medicated with levodopa and a healthy control group in...
Objective: The aim is to compare various fully automated methods for reducing ocular artifacts from EEG recordings.
Methods: Seven automated methods including regression, six component-based methods for reducing ocular artifacts have been applied to 36 data sets from two different labs. The influence of various noise sources is analyzed and the rat...
The BCI competition IV stands in the tradition of prior BCI competitions that aim to provide high quality neuroscientific data for open access to the scientific community. As experienced already in prior competitions not only scientists from the narrow field of BCI compete, but scholars with a broad variety of backgrounds and nationalities. They in...
Versteht man das Bild als kreative Quelle der Erkenntnis, so entstehen Spannungsfelder, zu denen individuelle ebenso wie kollektive Sinnkonzepte zählen. Der interdisziplinäre Zugang dieses Buches zu Bildstrukturen aus der Perspektive der Logik, Kognition, Semiotik, Bildwissenschaft, Kunstgeschichte, Psychologie, Neurowissenschaft und Informatik zei...
![Histograms of 16 all-night sleep EEG (modified from [18]). Thresholds...](publication/50851562/figure/fig4/AS:213924633944074@1428015015437/Histograms-of-16-all-night-sleep-EEG-modified-from-18-Thresholds-for-overflow_Q320.jpg)
BioSig is an open source software library for biomedical signal processing. The aim of the BioSig project is to foster research in biomedical signal processing by providing free and open source software tools for many different application areas. Some of the areas where BioSig can be employed are neuroinformatics, brain-computer interfaces, neuroph...
This chapter tackles a difficult challenge: presenting signal processing material to non-experts. This chapter is meant to
be comprehensible to people who have some math background, including a course in linear algebra and basic statistics, but
do not specialize in mathematics, engineering, or related fields. Some formulas assume the reader is fami...
Processing and storage of sensory information is based on the interaction between different neural populations rather than the isolated activity of single neurons. In order to characterize the dynamic interaction and transient cooperation of sub-circuits within a neural network, multivariate autoregressive (MVAR) models have proven to be an importa...
Determining the centers of electrical activity in the human body and the connectivity between different centers of activity in the brain is an active area of research. To understand brain function and the nature of cardiovascular diseases requires sophisticated methods applicable to non-invasively measured bioelectric and biomagnetic data. As it is...
Biomedical signals are stored in a variety of different data formats. This obstucts true interoperability, increases costs
for software development and maintenance of software. Therefore, it is would be desirable to have a single data format for
biomedical signals.
In order to address this issue, (I) essential properties of biosignal date formats...
Several feature types have been used with EEG-based Brain-Computer Interfaces. Among the most popular are logarithmic band power estimates with more or less subject-specific optimization of the frequency bands. In this paper we introduce a feature called Time Domain Parameter that is defined by the generalization of the Hjorth parameters. Time Doma...
A new framework is proposed for comparing evaluation metrics in classification applications with imbalanced datasets (i.e., the probability of one class vastly exceeds others). For model selection as well as testing the performance of a classifier, this framework finds the most suitable evaluation metric amongst a number of metrics. We apply this f...
Software development is a key issue in brain-computer interface (BCI) research. Software can show the similarities and differences of different data processing methods. It can also make clear which hyperparameters must be determined for particular algorithms. And it can demonstrate whether certain concepts are compatible or not. With BioSig's compr...
The self-paced control paradigm enables users to operate brain-computer interfaces (BCI) in a more natural way: no longer is the machine in control of the timing and speed of communication, but rather the user is. This is important to enhance the usability, flexibility, and response time of a BCI. In this work, we show how subjects, after performin...
Many Brain-computer Interfaces (BCI) use band-power estimates with more or less subject-specific optimization of the frequency bands. However, a number of alternative EEG features do not need to select the frequency bands; estimators for these features have been modified for an adaptive use. The popular band power estimates were compared with Adapt...
Biomedical signal processing is an import ant but underestimated area of medical informatics. In order to overcome this limitation, the open source software library BioSig has been established. The tools can be used to compare the recordings of different equipme nt providers, it provides validated methods for art ifact processing and supports over...
This paper discusses simulated on-line unsupervised adaptation of the LDA classier in order to counteract the harmful eect of non-class related non-stationarities in EEG during BCI sessions. Three types of adaptation procedures were applied to the two large BCI data sets from TU Graz and Berlin BCI project. Our results demonstrate that the unsuperv...
Summary Summary The spectral information of the sleep EEG is an important indicator for the sleep stage1. Adaptive autoregressive parameters can describe the time-varying spectrum. The AR spectrum is a maximum entropy spectral estimator, which is optimal with respect to the number of parameters. No selection of frequency bands is required if the AR...
We propose a new measure to estimate the direction of information flux in multivariate time series from complex systems. This measure, based on the slope of the phase spectrum (Phase Slope Index) has invariance properties that are important for applications in real physical or biological systems: (a) it is strictly insensitive to mixtures of arbitr...
This paper presents an effort launched in 2006 by the OpenECG network, led by the Graz University of Technology and supported by IEEE 1073, ISO 11073 and CEN TC251 to create a two-way converter in C++ between the SCP-ECG and the HL7 aECG standards. In the conversion, GDF, the BioSig internal data format, was used as an intermediate structure. This...
The increase of induced gamma-band responses (iGBRs; oscillations >30 Hz) elicited by familiar (meaningful) objects is well established in electroencephalogram (EEG) research. This frequency-specific change at distinct locations is thought to indicate the dynamic formation of local neuronal assemblies during the activation of cortical object repres...
The latest research in the development of technologies that will allow humans to communicate, using brain signals only, with computers, wheelchairs, prostheses, and other devices.
Interest in developing an effective communication interface connecting the human brain and a computer has grown rapidly over the past decade. The brain-computer interface...
The latest research in the development of technologies that will allow humans to communicate, using brain signals only, with computers, wheelchairs, prostheses, and other devices.
Interest in developing an effective communication interface connecting the human brain and a computer has grown rapidly over the past decade. The brain-computer interface...
The latest research in the development of technologies that will allow humans to communicate, using brain signals only, with computers, wheelchairs, prostheses, and other devices.
Interest in developing an effective communication interface connecting the human brain and a computer has grown rapidly over the past decade. The brain-computer interface...
The latest research in the development of technologies that will allow humans to communicate, using brain signals only, with computers, wheelchairs, prostheses, and other devices.
Interest in developing an effective communication interface connecting the human brain and a computer has grown rapidly over the past decade. The brain-computer interface...
A study of different on-line adaptive classifiers, using various feature types is presented. Motor imagery brain computer interface (BCI) experiments were carried out with 18 naive able-bodied subjects. Experiments were done with three two-class, cue-based, electroencephalogram (EEG)-based systems. Two continuously adaptive classifiers were tested:...
We present the self-paced 3-class Graz brain-computer interface (BCI) which is based on the detection of sensorimotor
electroencephalogram (EEG) rhythms induced by motor imagery. Self-paced operation means that the BCI is able to determine
whether the ongoing brain activity is intended as control signal (intentional control) or not (non-control s...
We present a study of linear, quadratic and regularized discriminant analysis (RDA) applied to motor imagery data of three subjects. The aim of the work was to find out which classifier can separate better these two-class motor imagery data: linear, quadratic or some function in between the linear and quadratic solutions. Discriminant analysis meth...
A fully automated method for reducing EOG artifacts is presented and validated.
The correction method is based on regression analysis and was applied to 18 recordings with 22 channels and approx. 6 min each. Two independent experts scored the original and corrected EEG in a blinded evaluation.
The expert scorers identified in 5.9% of the raw data s...
In this paper, we present self-paced Brain-Computer Inter-face (BCI) based interaction with a computer game. The BCI is able to detect three different motor imagery related brain patterns (imagination of left hand, right hand, foot or tongue movements) in the ongoing brain activity by using three bipolar electroencephalogram (EEG) channels only. To...
19.1 Abstract To analyze the performance of BCI systems, some evaluation criteria must be applied. The most popular is accuracy or error rate. Because of some strict prerequisites, accuracy is not always a suitable criterion, and other evaluation criteria have been proposed. This chapter provides an overview of evaluation criteria used in BCI resea...
One major challenge in Brain-Computer Interface (BCI) research is to cope with the inherent nonstationarity of the recorded brain signals caused by changes in the subjects brain processes during an experiment. Online adaptation of the classifier embedded into the BCI is a possible way of tackling this issue. In this chapter we investigate the effec...
Recently, a new estimator—Arfit—for multivariate (vector) autoregressive (MVAR) parameters has been proposed. Several other MVAR estimators (e.g. Levinson recursion, Burg-type Nuttall–Strand, etc.) were already well known in the field of signal processing.The various MVAR estimators have been implemented for Octave and Matlab. A method based on cro...
Biomedical signals are stored in many different data formats. Most formats have been developed for a specific purpose of a specialized community for ECG research, EEG analysis, sleep research, etc. So far none of the existing formats can be considered a general purpose data format for biomedical signals. In order to solve this problem and to unify...
This paper describes the outcome of discussions held during the Third International BCI Meeting at a workshop charged with reviewing and evaluating the current state of and issues relevant to brain-computer interface (BCI) feature extraction and translation. The issues discussed include a taxonomy of methods and applications, time-frequency spatial...
A brain-computer interface (BCI) is a system that allows its users to control external devices with brain activity. Although the proof-of-concept was given decades ago, the reliable translation of user intent into device control commands is still a major challenge. Success requires the effective interaction of two adaptive controllers: the user's b...
Over the last 15 years, the Graz Brain-Computer Interface (BCI) has been developed and all components such as feature extraction and classification, mode of operation, mental strategy, and type of feedback have been investigated. Recent projects deal with the development of asynchronous BCIs, the presentation of feedback and applications for commun...
A viable fully on-line adaptive brain computer interface (BCI) is introduced. On-line experiments with nine naive and able-bodied subjects were carried out using a continuously adaptive BCI system. The data were analyzed and the viability of the system was studied. The BCI was based on motor imagery, the feature extraction was performed with an ada...
We studied the reactivity of EEG rhythms (mu rhythms) in association with the imagination of right hand, left hand, foot, and tongue movement with 60 EEG electrodes in nine able-bodied subjects. During hand motor imagery, the hand mu rhythm blocked or desynchronized in all subjects, whereas an enhancement of the hand area mu rhythm was observed dur...
BioSig is an open source software library for biomedical signal processing. Most users in the field are using Matlab; however, significant effort was undertaken to provide compatibility to Octave, too. This effort has been widely successful, only some non-critical components relying on a graphical user interface are missing. Now, installing BioSig...
Methods of spatio-temporal analysis provide important tools for characterizing several dynamic aspects of brain oscillations that are reflected in the human scalp-detected electroencephalogram (EEG). The search to identify the dynamic connectivity of brain signals within different frequency bands, in order to uncover the transient cooperation betwe...
To determine and compare the performance of different classifiers applied to four-class EEG data is the goal of this communication. The EEG data were recorded with 60 electrodes from five subjects performing four different motor-imagery tasks. The EEG signal was modeled by an adaptive autoregressive (AAR) process whose parameters were extracted by...
We present the result of on-line feedback Brain Computer Interface experiments using adaptive and non-adaptive feature extraction methods with an on-line adaptive classifier based on Quadratic Discriminant Analysis. Experiments were performed with 12 naïve subjects, feedback was provided from the first moment and no training sessions were needed. E...
We hypothesized that the extreme endurance exercise of an Ironman competition would lead to long-standing hemodynamic and autonomic changes. We investigated also the possibility of predicting competition performance from baseline hemodynamic and autonomic parameters. We have investigated 27 male athletes before competition, 1 h after, and then for...
To characterize the regional changes in neuronal couplings and information transfer related to semantic aspects of object recognition in humans we used partial-directed EEG-coherence analysis (PDC). We examined the differences of processing recognizable and unrecognizable pictures as reflected by changes in cortical networks within the time-window...
To date, the only standard for the classification of sleep-EEG recordings that has found worldwide acceptance are the rules published in 1968 by Rechtschaffen and Kales. Even though several attempts have been made to automate the classification process, so far no method has been published that has proven its validity in a study including a sufficie...
Interest in developing a new method of man-to-machine communication-a brain-computer interface (BCI)-has grown steadily over the past few decades. BCIs create a new communication channel between the brain and an output device by bypassing conventional motor output pathways of nerves and muscles. These systems use signals recorded from the scalp, th...
In this study, we applied partial-directed EEG-coherence analysis to assess regional changes in neuronal couplings and information transfer related to semantic processing. We tested the hypothesis whether (and which) processing differences between spoken words and pseudowords are reflected by changes in cortical networks within the time window of a...
Interrater variability of sleep stage scorings is a well-known phenomenon. The SIESTA project offered the opportunity to analyse interrater reliability (IRR) between experienced scorers from eight European sleep laboratories within a large sample of patients with different (sleep) disorders: depression, general anxiety disorder with and without non...
In this paper, different data-driven design concepts for an individual control of Brain-Computer Interfaces using different features (estimated parameters of linear autoregressive models and power spectrums) and classi-fiers (quadratic discriminant functions, fuzzy classifiers) are compared. The used data set was part of the BCI Competition 2003. A...
Adaptive autoregressive parameters and a linear classifier were used to detect movement related desynchronization and synchronization patterns in single-channel electrocorticogram (ECoG) obtained from implanted electrode grids. The best classification accuracies found had more than 90% hits and less than 10% false positives. The findings show that...
The Graz-brain-computer interface (BCI) is a cue-based system using the imagery of motor action as the appropriate mental task. Relevant clinical applications of BCI-based systems for control of a virtual keyboard device and operations of a hand orthosis are reported. Additionally, it is demonstrated how information transfer rates of 17 b/min can b...
A direct brain interface (DBI) based on the detection of event-related potentials (ERPs) in human electrocorticogram (ECoG) is under development. Accurate detection has been demonstrated with this approach (near 100% on a few channels) using a single-channel cross-correlation template matching (CCTM) method. Several opportunities for improved detec...
The idea of an EEG-based brain computer interface is to support the communication of locked-in-patients. Thus, it is important to quantify the information transfer. Wolpaw et al. (2000) proposed a measure which is derived from the classification error rate. We propose an alternative measure. Both measures are compared and the advantages and disadva...
An EEG-based Brain-Computer Interface (BCI) could be used as an additional communication channel between human thoughts and the environment. The efficacy of such a BCI depends mainly on the transmitted information rate. Shannon's communication theory was used to quantify the information rate of BCI data. For this purpose, experimental EEG data from...
The fields of presence research and electroencephalography (EEG) are related in, at least, two ways. Firstly, EEG can be used to analyse the neurophysiological phenomena related to presence research. For example, EEG might be useful to investigate the question of 'breaks in presence'. Secondly, EEG can be used to control external devices with a so-...
For an EEG-based Brain-Computer-Interface (BCI) is a new linear classification system proposed. The proposed method considers different variance-covariances for each class and, therefore, it has an advantage against Linear Discriminant Analysis.
The Graz Brain-Computer Interface (BCI) analyses and classifies the dynamics of oscillatory EEG components during motor imagery. At this time a patient controls the closing and opening of a hand orthosis with a BCI and students are able to write error free with a spelling rate of 1 character/minute.
Dieser Artikel gibt einen Überblick über das von der Europäischen Kommission im Rahmen der BIOMED-2-Ausschreibungen geförderten Projektes SIESTA. Das wesentliche Ziel war die intensive Forschung zur Architektur des Schlafes und die Entwicklung und Evaluierung neuer Verfahren zur Schlafanalyse, aufbauend auf polygraphischen Ableitungen mit dem Schwe...
The SIESTA project had two major goals: developing new tools for analyzing computer-based sleep recordings and creating a reference database for sleep-related features. Basically, both goals have been reached, although validation and fine tuning of the sleep analyzer is still on-going. Investigations on the Web interface will be finished soon and a...
Aspects to consider when building a database are presented. The
work is based on experiences from the SIESTA project which identified
sleep disorders
This article presents some requirements imposed on data format specifications derived from different biosignal recording environments. This is followed by a review of four particularly interesting data formats and some notes about other specifications. Finally, the merits of different formats are discussed and some views about future developments a...
The electroencephalogram (EEG) is modified by motor imagery and can be used by patients with severe motor impairments (e.g., late stage of amyotrophic lateral sclerosis) to communicate with their environment. Such a direct connection between the brain and the computer is known as an EEG-based brain-computer interface (BCI). This paper describes a n...
Analysis of heart rate variability requires the calculation of the mean heart rate. Adaptive methods are important for online and real-time parameter estimation. In this paper, we demonstrate the use of Kalman filtering to estimate adaptively the mean heart rate and remove the trend.
This paper describes a research approach to develop a brain-computer interface (BCI) based on recognition of subject-specific EEG patterns. EEG signals recorded from sensorimotor areas during mental imagination of specific movements are classified on-line and used e.g. for cursor control. In a number of on-line experiments, various methods for EEG...
A criterion, similar to the information criterion of a stationary
autoregressive (AR) model, is introduced for an adaptive
(non-stationary) autoregressive model. It is applied to nonstationary
EEG data. It is shown that the criterion can be used to determine the
update coefficient, the model order and the estimation algorithm
Sixteen polysomnographic recordings from 8 European sleep laboratories were analyzed. The histogram analysis was used to introduce quality control of all-night EEG recordings.
It was found that the header information does not always provide the real saturation values of the recording equipment. The entropy measure was used for the quantitative anal...
Quantitative analysis of sleep EEG data can provide valuable additional information in sleep research. However, analysis of data contaminated by artifacts can lead to spurious results. Thus, the first step in realizing an automatic sleep analysis system is the implementation of a reliable and valid artifact processing strategy. This strategy should...
EEG feedback studies demonstrate that human subjects can learn to regulate electrocortical activity over the sensorimotor cortex. Such self-induced EEG changes could serve as control signals for a Brain Computer Interface. The experimental task of the current study was to imagine either right-hand or left-hand movement depending on a visual cue sti...
An EEG-based brain-computer interface (BCI) is a direct connection between the human brain and the computer. Such a communication system is needed by patients with severe motor impairments (e.g. late stage of Amyotrophic Lateral Sclerosis) and has to operate in real-time. This paper describes the selection of the appropriate components to construct...
Estimates of the cardiac field artifact were obtained for each EEG/EOG channel of all-night sleep EEG/ECG recordings by heartbeat-related averaging of the EEG. These estimates – so-called templates – can be used for minimization of the arti-fact, e. g. by heartbeat-synchronized subtraction of the template. The 3-dimensional nature of the car-diac f...
An EEG-based brain-computer interface (BCI) is a direct connection between the human brain and the computer. Such a communication system is needed by patients with severe motor impairments (e.g. late stage of Amyotrohpic Lateral Sclerosis) and has to operate in real-time. This paper describes the selection of the appropriate components to construct...
The automatic detection of sleep spindles can be accomplished with filter methods. The optimisation of filter characteristics is necessary to improve the performance of the detection. Raw EEG data were filtered with varying basebands in the frequency range of sleep spindles. The outputs were taken to calculate Receiver Operating Characteristics-Cur...
