Gert Pfurtscheller

Graz University of Technology | TU Graz · Institute for Knowledge Discovery

Brain-heart interactions (BHI) are critical for generating and processing emotions, including anxiety. Understanding specific neural correlates would be instrumental for greater comprehension and potential therapeutic interventions of anxiety disorders. While prior work has implicated the pontine structure as a central processor in cardiac regulati...

MRI-related anxiety in healthy participants is often characterized by a dominant breathing frequency at around 0.32 Hz (19 breaths per minute, bpm) at the beginning but in a few cases also at the end of scanning. Breathing waves at 19 bpm are also observed in patients with anxiety independently of the scanned body part. In patients with medically i...

Background: Respiratory sinus arrhythmia (RSA) denotes decrease of cardiac beat-to-beat intervals (RRI) during inspiration and RRI increase during expiration, but an inverse pattern (termed negative RSA) was also found in healthy humans with elevated anxiety. It was detected using wave-by-wave analysis of cardiorespiratory rhythms and was consider...

Brain-body interactions can be studied by using directed coupling measurements of fMRI oscillations in the low (0.1–0.2 Hz) and high frequency bands (HF; 0.2–0.4 Hz). Recently, a preponderance of oscillations in the information flow between the brainstem and the prefrontal cortex at around 0.15/0.16 Hz was shown. The goal of this study was to inves...

Slow oscillations of different center frequencies and their coupling play an important role in brain-body interactions. The crucial question analyzed by us is, whether the low frequency (LF) band (0.05–0.15 Hz) or the intermediate frequency (IMF) band (0.1–0.2 Hz) is more eminent in respect of the information flow between body (heart rate and respi...

Recently, we reported on a rare manifestation of respiratory sinus arrhythmia (RSA), namely the “switched-off” RSA (Rassler et al., 2018), also called negative RSA (nRSA). It was found in a minority of healthy persons during elevated fMRI-related anxiety characterized by slow spontaneous breathing and synchronous slow beat-to-beat interval (RRI) os...

Brain–heart synchronization is fundamental for emotional-well-being and brain–heart desynchronization is characteristic for anxiety disorders including specific phobias. Recording BOLD signals with functional magnetic resonance imaging (fMRI) is an important noninvasive diagnostic tool; however, 1–2% of fMRI examinations have to be aborted due to c...

Objective Although about 1-2% of MRI examinations must be aborted due to anxiety, there is little research on how MRI-related anxiety affects BOLD signals in resting states. Methods We re-analyzed cardiac beat-to beat interval (RRI) and BOLD signals of 23 healthy fMRI participants in four resting states by calculation of phase-coupling in the 0.07...

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 i...

Heart rate variability (HRV) has been associated with various diseases and reflects autonomic cardiac control sensitive to central nervous system function. Examples of the heart-brain interaction are illustrated by extreme clinical conditions such as brain death, orthotopic heart transplantation, weaning from respirator support, and brain maturatio...

Recently, we reported on the unusual “switch-off” of respiratory sinus arrhythmia (RSA) by analyzing heart rate (HR) beat-to-beat interval (RRI) signals and respiration in five subjects during a potentially anxiety-provoking first-time functional magnetic resonance imaging (fMRI) scanning with slow spontaneous breathing waves (Rassler et al., 2018)...

[This corrects the article DOI: 10.1371/journal.pone.0206675.].

A group of 23 healthy scanner naïve 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 respir...

Participation in magnetic resonance imaging (MRI) scanning is associated with increased anxiety, thus possibly impacting baseline recording for functional MRI studies. The goal of the paper is to elucidate the significant hemispheric asymmetry between blood-oxygenation-level-dependent (BOLD) signals from precentral gyrus (PCG) and insula in 23 heal...

Participation in a MRI scan is associated with increased anxiety, thus possibly impacting baseline recording for functional MRI studies. We investigated in 23 healthy individuals without any former MRI experience (scanner-naive) the relations between anxiety, 0.1-Hz BOLD oscillations and heart rate variability (HRV) in two separate resting state se...

Low frequency oscillations with a dominant frequency at 0.1 Hz are one of the most influential intrinsic blood-oxygen-level dependent (BOLD) signals. This raises the question if vascular BOLD oscillations (originating from blood flow in the brain) and intrinsic slow neural activity fluctuations (neural BOLD oscillations) can be differentiated. In t...

Non-invasive steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) systems offer high bandwidth compared to other BCI types and require only minimal calibration and training. Virtual reality (VR) has been already validated as effective, safe, affordable and motivating feedback modality for BCI experiments. Augmented real...

In the resting state, blood oxygen level-dependent (BOLD) oscillations with a frequency of about 0.1 Hz are conspicuous. Whether their origin is neural or vascular is not yet fully understood. Furthermore, it is not clear whether these BOLD oscillations interact with slow oscillations in heart rate (HR). To address these two questions, we estimated...

Objectives: In the brain and heart, oscillations at about 0.1Hz are conspicuous. It is therefore worthwhile to study the interaction between intrinsic BOLD oscillations (0.1Hz) and slow oscillations in heart rate interval (RRI) signals and differentiate between their neural and vascular origin. Methods: We studied the phase-coupling with a 3T sc...

Recently we hypothesized that the intention to initiate a voluntary movement at free will may be related to the dynamics of hemodynamic variables, which may be supported by the intertwining of networks for the timing of voluntary movements and the control of cardiovascular variables in the insula. In the present study voluntary movements of 3 healt...

Background / Purpose: A temporal clustering analysis approach was used in order to evaluate the functional brain connectivity at oscillations around 0.1Hz at rest or under task conditions. Therefore, we aim to evaluate the relationship between brain regions in terms of these oscillations Hz under the hypotheses that functionally interconnected br...

Entrainment in physiological systems can be manifest in cases where phase-coupling (synchronization) between slow intrinsic oscillations and periodic motor responses, or vice versa, takes place. To test whether voluntary movement has something in common with entrainment of slow hemodynamic oscillations to motor responses, we studied blood pressure...

Operating a brain-computer interface (BCI) is a skill that individuals must learn. A recent study demonstrated that successful skill acquisition enables human individuals to control telepresence robotic devices in three-dimensional physical space using the non-invasive electroencephalogram (EEG). Although the results are very promising, there is ro...

Objectives: This review outlines the method -ological fundamentals of the most frequently used non-parametric time-frequency analysis techniques in biomedicine and their main properties, as well as providing decision aids concerning their applications. Methods: The short-term Fourier transform (STFT), the Gabor transform (GT), the S-transform (ST),...

Cue-paced motor imagery (MI) is a frequently used mental strategy to realize a Brain-Computer Interface (BCI). Recently it has been reported that two MI tasks can be separated with a high accuracy within the first second after cue presentation onset. To investigate this phenomenon in detail we studied the dynamics of motor cortex beta oscillations...

In this paper, we describe a multimodal brain–computer interface (BCI) experiment, situated in a highly immersive CAVE. A subject sitting in the virtual environment controls the main character of a virtual reality game: a penguin that slides down a snowy mountain slope. While the subject can trigger a jump action via the BCI, additional steering wi...

There is increasing interest in the intrinsic activity in the resting brain, especially that of ultraslow and slow oscillations. Using near-infrared spectroscopy (NIRS), electroencephalography (EEG), blood pressure (BP), respiration and heart rate recordings during 5 minutes of rest, combined with cross spectral and sliding cross correlation calcul...

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...

Brain–Computer Interfaces (BCI) are communication systems which can convey messages through brain activity alone. Recently BCIs were gaining interest among the virtual reality (VR) community since they have appeared as promising interaction devices for virtual environments (VEs). Especially these implicit interaction techniques are of great interes...

Beta rebound is the term for bursts of EEG activity in the beta band observable after movement or somatosensory stimulation. It is assumed to reflect an active inhibition process. Our aim was to investigate the differences in the beta rebound between movement termination and withholding of movement, and the withholding of overt and covert movement....

In the last 15 years, a recognizable surge in the field of Brain Computer Interface (BCI) research and development has emerged. This emergence has sprung from a variety of factors. For one, inexpensive computer hardware and software is now available and can support the complex high-speed analyses of brain activity that is essential is BCI. Another...

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...

This chapter describes and illustrates the electroencephalographic changes following motor imagery practice. Specifically, it considers the sensorimotor activation and deactivation through event-related (de)synchronization pattern recordings. It shows that measuring the neuronal activity with high temporal resolution brings researchers a reliable t...

This chapter considers the brain/computer used to drive robots from the brain activity during imagined actions, as it opens new possibilities for helping patients with various forms of paralysis. It shows that motor imagery is an efficient strategy to operate a brain- computer interface through the imagery-related encephalographic changes, classifi...

Characteristically within the resting brain there are slow fluctuations (around 0.1Hz) of EEG and NIRS-(de)oxyhemoglobin ([deoxy-Hb], [oxy-Hb]) signals. An interesting question is whether such slow oscillations can be related to the intention to perform a motor act. To obtain an answer we analyzed continuous blood pressure (BP), heart rate (HR), pr...

The present work examines the close interaction between brain and heart and shows that slow (de)oxyhemoglobin oscillations in the prefrontal cortex and changes in blood pressure and heart rate are coupled with a cyclic EEG alpha and beta power decreases in motor areas in the resting brain.

Near-infrared spectroscopy (NIRS) is a non-invasive optical technique for the assessment of functional activity in the human brain. Task-specific hemodynamic responses, i.e., concentration changes of oxy- and deoxyhemoglobin (oxy-Hb, deoxy-Hb) during cognitive, visual, visuo-motor, and motor tasks can be detected and used for brain-computer interfa...

One important feature of the baroreflex loop is its strong preference for oscillations around 0.1 Hz. In this study, we investigated heart rate intervals, arterial blood pressure (BP), and prefrontal oxyhemoglobin changes during 5 min rest and during brisk finger movements in 19 healthy subjects. We analyzed the phase coupling around 0.1 Hz between...

Near-infrared spectroscopy (NIRS) is a non-invasive optical technique that can be used for brain-computer interfaces (BCIs) systems. A common challenge for BCIs is a stable and reliable classification of single-trial data, especially for cognitive (mental) tasks. With antagonistic activation pattern, recently found for mental arithmetic (MA) tasks,...

The baroreflex is mainly involved in short-term blood pressure regulation and strongly influenced by activations of medullary circulation centres in the brain stem and higher brain centres. One important feature of the baroreflex is its strong preference for oscillations around 0.1Hz, which can be seen as resonance or "eigenfrequency" (EF) of the c...

A brain-computer interface (BCI) provides a direct connection between the human brain and a computer. One type of BCI can be realized using steady-state visual evoked potentials (SSVEPs), resulting from repetitive stimulation. The aim of this study was the realization of an asynchronous SSVEP-BCI, based on canonical correlation analysis, suitable f...

About 300,000 people in Europe alone suffer from a spinal cord injury (SCI), with 11,000 new injuries per year [20]. SCI is caused primarily by traffic and work accidents, and an increasing percentage of the total population also develops SCI from diseases like infections or tumors. About 70% of SCI cases occur in men. 40% are tetraplegic patients...

Brain–computer interface (BCI) systems detect changes in brain signals that reflect human intention, then translate these signals to control monitors or external devices (for a comprehensive review, see [1]). BCIs typically measure electrical signals resulting from neural firing (i.e. neuronal action potentials, Electroencephalogram (ECoG), or Elec...

Many BCI systems rely on imagined movement. The brain activity associated with real or imagined movement produces reliable changes in the EEG. Therefore, many people can use BCI systems by imagining movements to convey information. The EEG has many regular rhythms. The most famous are the occipital alpha rhythm and the central mu and beta rhythms....

During the past decades several groups have dedicated research on the field of brain- computer interaction as a communication and control support for paralyzed patients. Brain-computer interface (BCI) systems are normally based on the EEG. Beside EEG, such systems have also been realized with MEG and recently with fMRI methods. However, the use of...

Brain-computer interface (BCI) systems allow people to send messages or commands without moving, and hence can provide an alternative communication and control channel for people with limited motor function. In this study, we demonstrate a BCI system for orthosis control. Our BCI was asynchronous, meaning that subjects could move the orthosis whene...

A P300 spelling system is one of the most popular EEG-based spelling systems. This system is normally presented as a matrix and allows its users to select one of many options by focused attention. It is possible to use large matrices as a large menu (computer keyboard, etc.), but then more time is required for each selection, because all rows and c...

For individuals with a high spinal cord injury (SCI) not only the lower limbs, but also the upper extremities are paralyzed. A neuroprosthesis can be used to restore the lost hand and arm function in those tetraplegics. The main problem for this group of individuals, however, is the reduced ability to voluntarily operate device controllers. A brain...

Nowadays, everybody knows what a hybrid car is. A hybrid car normally has two engines to enhance energy efficiency and reduce CO2 output. Similarly, a hybrid brain-computer interface (BCI) is composed of two BCIs, or at least one BCI and another system. A hybrid BCI, like any BCI, must fulfill the following four criteria: (i) the device must rely o...

n this paper, we present a first proof-of-concept for using a mobile Brain-Computer Interface (BCI) coupled to a wearable computer as an ambient input device for a ubiquitous computing service. BCI devices, such as electroencephalogram (EEG) based BCI, can be used as a novel form of human-computer interaction device. A user can log into a nearby co...

Brain-computer interface (BCI) systems do not work for all users. This article introduces a novel combination of tasks that could inspire BCI systems that are more accurate than conventional BCIs, especially for users who cannot attain accuracy adequate for effective communication. Subjects performed tasks typically used in two BCI approaches, name...

Near-infrared spectroscopy (NIRS) is a functional brain imaging method able to study hemodynamic changes during cortical activation. We studied the changes of oxy- and deoxyhemoglobin ([oxy-Hb], [deoxy-Hb]) with a 52-channel NIRS system during simple mental arithmetic in ten healthy volunteers over the prefrontal cortex. We found that eight of the...

This paper describes a method to recover task-related brain sources in the context of multiclass brain--computer interfaces (BCIs) based on noninvasive EEG. We extend the method joint approximate diagonalization (JAD) for spatial filtering using a maximum likelihood framework. This generic formulation: 1) bridges the gap between the common spatial...

Bringing a Brain-Computer Interface (BCI) out of the lab one of the main problems has to be solved: to shorten the training time. Finding a solution for this problem, the use of a BCI will be open not only for people who have no choice, e.g., persons in a locked-in state, or suffering from a degenerating nerve disease. By reducing the training time...

INTRODUCTION Adequate behaviour requires the control (execution/inhibition) of learned programs in a situational context. Inspired by the fMRI-work of Hummel the aim of this study was to investigate the appropriate control of acquired and memorized motor programs (to our knowledge the first time) with the NIRS method. METHODS Investigations were c...

This paper presents a reusable, highly configurable application framework that seamlessly integrates SSVEP stimuli within a desktop-based virtual environment (VE) on standard PC equipment. Steady-state visual evoked potentials (SSVEPs) are brain signals that offer excellent information transfer rates (ITR) within braincomputer interface (BCI) syste...

A brain-computer interface (BCI) is a new communication channel between humans and computers that translates brain activity into recognizable command and control signals. Attended events can evoke P300 potentials in the electroencephalogram. Hence, the P300 has been used in BCI systems to spell, control cursors or robotic devices, and other tasks....

This work introduces a hybrid brain-computer interface (BCI) composed of an imagery-based brain switch and a steady-state visual evoked potential (SSVEP)-based BCI. The brain switch (event related synchronization (ERS)-based BCI) was used to activate the four-step SSVEP-based orthosis (via gazing at a 8 Hz LED to open and gazing at a 13 Hz LED to c...

In a conventional brain-computer interface (BCI) system, users perform mental tasks that yield specific patterns of brain activity. A pattern recognition system determines which brain activity pattern a user is producing and thereby infers the user's mental task, allowing users to send messages or commands through brain activity alone. Unfortunatel...

This paper presents an asynchronous brain switch using one Laplacian electroencephalographic (EEG) derivation. The brain switch is operated through foot motor imagery (MI) and is based on the classification of event-related desynchronization (ERD) during a motor task or event-related synchronization (ERS) after the termination of the task (also kno...

Electroencephalograph (EEG) recordings during right and left hand motor imagery can be used to move a cursor to a target on a computer screen (such system is called BCI). Recently, we have proposed the detection method of error potential in order to add the fail safe function to BCI system. In this paper, feature extraction method based on morpholo...

Brain–computer interface (BCI) systems detect changes in brain signals that reflect human intention, then translate these signals to control monitors or external devices (for a comprehensive review, see [1]). BCIs typically measure electrical signals resulting from neural firing (i.e. neuronal action potentials, Electroencephalogram (ECoG), or Elec...

“Graz brain–computer interface (BCI)” transforms changes in oscillatory electroencephalogram (EEG) activity into control signals for external devices and feedback. Steady‐state evoked potentials (SSEPs) and event‐related desynchronization (ERD) are employed to encode user messages. User‐specific setup and training are important issues for robust an...

Slow oscillations around 0.1 Hz are characteristic features of both the cardiovascular and central nervous systems. Such oscillation have been reported, e.g. in blood pressure, heart rate, EEG and brain oxygenation. Hence, conscious intention of a motor act may occur only as a result of brain activity changes in frontal and related brain areas, or...

More intelligent persons (high IQ) typically present a higher cortical activity during tasks requiring the encoding of visuo-spatial information, namely higher alpha (about 10 Hz) event-related desynchronization (ERD; Doppelmayr et al., 2005). The opposite is true ("neural efficiency") during the retrieval of the encoded information, as revealed by...

This study investigates the influence of eye movement direction on patterns of brain activation. The processing of visual input was investigated by quantifying event-related desynchronization (ERD) in the electroencephalogram (EEG). Cue-based vertical and horizontal eye movements were measured with an eye tracker. Differences between vertical and h...