Katharina Lingelbach

Carl von Ossietzky Universität Oldenburg · Department of Psychology

Deep reinforcement learning (RL) is used as a strategy to teach robot agents how to autonomously learn complex tasks. While sparsity is a natural way to define a reward in realistic robot scenarios, it provides poor learning signals for the agent, thus making the design of good reward functions challenging. To overcome this challenge learning from...

Introduction We investigated brain activation patterns of interacting emotional distractions and cognitive processes in a close-to-naturalistic functional near-infrared spectroscopy (fNIRS) study. Methods Eighteen participants engaged in a monitoring-control task, mimicking common air traffic controller requirements. The scenario entailed experien...

Humans’ performance varies due to the mental resources that are available to successfully pursue a task. To monitor users’ current cognitive resources in naturalistic scenarios, it is essential to not only measure demands induced by the task itself but also consider situational and environmental influences. We conducted a multimodal study with 18 p...

Humans’ performance varies due to the mental resources that are available to successfully pursue a task. To monitor users’ current cognitive resources in naturalistic scenarios, it is essential to not only measure demands induced by the task itself but also consider situational and environmental influences. We conducted a multimodal study with 18 p...

Since thoroughly validated naturalistic affective German speech stimulus databases are rare, we present here a novel validated database of speech sequences assembled with the purpose of emotion induction. The database comprises 37 audio speech sequences with a total duration of 92 minutes for the induction of positive, neutral, and negative emotion...

In modern workplaces with rapidly changing skill requirements, suitable training and learning environments play a key role for companies to remain competitive, effective and ensure job satisfaction. To provide an immersive, interactive, and engaging learning experience, Virtual Reality (VR) has emerged as a revolutionary technology. Especially when...

We investigated the effects of feedback on users’ performance during a cognitive task with concurrent emotional distraction. Our aim was to provide participants with insights into their current affective and cognitive state by measuring and decoding brain activity. Therefore, a real-time preprocessing, analyzing, and visualization routine was devel...

Peripheral physiological measures such as electrodermal activity (EDA), heart rate and pupil dilation, as well as neurophysiological measures such as electroencephalography (EEG), can inform us about individuals’ cognitive and emotional state. We are interested in exploiting such measures in real life situations. A challenge of interpreting physiol...

Motivation and Aim: In the past decade, theoretical models of modular architectures with cold cognitive and hot affective-emotional systems have been progressively revised [1-3]. Nowadays, these mechanisms are suggested to be interwoven [4-5] and even processed in shared underlying neurocircuitry (e.g., [1,3]). Particularly in naturalistic environm...

Motivation and Aim: Electroencephalographic (EEG) recordings allow to capture temporal activation patterns associated with the current level of workload or emotional states [1-4]. Decoding mental states from these activation patterns and reacting to them accordingly can increase performance, safety, and user experience during human-machine interact...

Motivation and Aim: Electroencephalographic (EEG) recordings allow to capture temporal activation patterns associated with the current level of workload or emotional states [1-4]. Decoding mental states from these activation patterns and reacting to them accordingly can increase performance, safety, and user experience during human-machine interact...

Motivation and Aim: For neuroergonomic applications, robust decoding of activation patterns indicating current affective or cognitive states is a crucial step to develop adaptive and collaborative human-machine systems leading to increased performance, safety, and user experience [1-6]. So far, most studies attempting to estimate affective and cogn...

The continuous acquisition of new digital competences and the development of situational learning assistance systems will become more important than ever in the coming years, because the world of work is becoming more complex, more informative and all above more data-driven. Jobs are changing due to increasing digitalisation, whereby the use of mod...

Psychologists with their expertise in statistics and regarding human perception and behavior can contribute valuable insights to the development of innovative and useful artificial intelligence (AI) systems. Therefore, we need to raise attention and curiosity for AI and foster the willingness to engage with it among psychology students. This requir...

The COVID-19 pandemic has a strong worldwide impact on not only the health and economic sectors but also the (socio-)psychological functioning of individuals. Since psychological health is an important protective factor to prevent diseases, it is crucial to identify individuals with increased vulnerability during the crisis. 275 adults participated...

We present forecasting models based on extreme gradient boosting to predict demand using real-world data of a German intermediary company in the media sector. The data set comprised the daily demand of 196,767 products from three years (mid-2017 to mid-2020) and meta information for each product including product type affiliation. Models were train...

During COVID-19, there has been a need to gather reliable empirical data on the consequences for behavior and psychological well-being in society as well as to inform and educate individuals comprehensively. The WIBCE online survey tool offers the possibility to (1) inform, reflect, and empower participants to be more self-aware regarding psycholog...

Several studies emphasize the great potential of rhythmic light stimulation to evoke steady-state visual evoked potentials (SSVEPs) measured via electroencephalographic (EEG) recordings as a safe method to modulate brain activity. In the current study, we investigated visual event-related potentials (ERPs) and oscillatory power evoked by perceptibl...

Objective and Background: To contain the COVID-19 pandemic, public health actions have changed the everyday life with an inevitable impact on individuals and their social life. Since intact (socio-)psychological functioning and mental health are protective factors contributing to the immune system and preventing diseases, it is crucial to identify...

Objective and Background: Decades of research in the field of steady-state visual evoked potentials (SSVEPs) have revealed great potential of rhythmic light stimulation for brain–computer interfaces. Additionally, rhythmic light stimulation provides a non-invasive method for entrainment of oscillatory activity in the brain. Especially effective pro...

Die COVID-19-Pandemie beeinflusst nicht nur den Gesundheits- und Wirtschaftssektor sehr, sondern es sind auch Auswirkungen auf soziale und psychologische Faktoren der Bevölkerung zu beobachten. Die Untersuchung dieser Auswirkungen ist besonders relevant, da soziale und psychologische Ressourcen wichtige Schutzfaktoren für Krankheiten darstellen. Da...

The COVID-19 pandemic has a strong worldwide impact on not only the health and economic sector but also the (socio-)psychological functioning of individuals. Since psychological health is an important protective factor to prevent diseases, it is crucial to identify individuals with increased vulnerability during the crisis. 275 adults participated...

Objective and Background: To contain the COVID-19 pandemic, public health actions have changed the everyday life with an inevitable impact on individuals and their social life. Since intact (socio-)psychological functioning and mental health are protective factors contributing to the immune system and preventing of diseases, it is crucial to identi...

During COVID-19, there has been a need to gather reliable empirical data on the consequences for behavior and psychological well-being in society as well as to inform and educate individuals comprehensively. The WIBCE online survey tool offers the possibility to (1) inform, reflect, and empower participants to be more self-aware regarding psycholog...

Affect monitoring is being discussed as a novel strategy to make adaptive systems more user-oriented. Basic knowledge about oscillatory processes and functional connectivity underlying affect during naturalistic human–computer interactions (HCI) is, however, scarce. This study assessed local oscillatory power entrainment and distributed functional...

Ziel dieses Positionspapiers ist es einen Ansatz zu präsentieren, der einen Austausch von Akteuren in einem Netzwerk für Daten ermöglicht. Sogenannte Ökosysteme für Daten und KI sind Netzwerke, in denen verschiedene Partner Daten untereinander teilen, gemeinsame Schnittstellen errichten, miteinander arbeiten und dadurch einflussreiche Fusionen scha...

Technological products for training the mind that support subjective well-being are gaining popularity in our daily lives. Using Electroencephalographic (EEG) signals for neurofeedback is helpful for learning and a promising approach to train the mind. We introduce MindTrain, a novel, gamified neurofeedback training environment that allows users to...

Previous research in voluntary retrieval suppression indicates that the right dorsolateral prefrontal cortex (rdlPFC) plays a key role in control mechanisms enabling inhibition of memory and consequently suppression induced forgetting. By using inhibitory repetitive transcranial magnetic stimulation (rTMS) simultaneously with the task, the study ex...