Inst. Softwaretechnik und Theoretische Informatik

336 Items

Recent Submissions
Supporting domain modeling with automated knowledge acquisition and modeling recommendations

Agt-Rickauer, Henning (2020)

Domain modeling is an important model-driven engineering activity, which is typically used in the early stages of software projects. Domain models capture concepts and relationships of respective application fields using a modeling language and domain-specific terms. They are a key factor in achieving shared understanding of the problem area among stakeholders, improving communication in softwa...

Ad-Hoc stream query processing

Karimov, Jeyhun (2020)

Many modern applications require processing large amounts of data in a real-time fashion. As a result, distributed stream processing engines (SPEs) have gained significant attention as an important new class of big data processing systems. The central design principle of these SPEs is to handle queries that potentially run forever on data streams with a query-at-a-time model, i.e., each query i...

A local measure of symmetry and orientation for individual spikes of grid cells

Weber, Simon Nikolaus ; Sprekeler, Henning (2019-02-07)

Grid cells have attracted broad attention because of their highly symmetric hexagonal firing patterns. Recently, research has shifted its focus from the global symmetry of grid cell activity to local distortions both in space and time, such as drifts in orientation, local defects of the hexagonal symmetry, and the decay and reappearance of grid patterns after changes in lighting condition. Here...

Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity

Weber, Simon Nikolaus ; Sprekeler, Henning (2018-02-21)

Neurons in the hippocampus and adjacent brain areas show a large diversity in their tuning to location and head direction, and the underlying circuit mechanisms are not yet resolved. In particular, it is unclear why certain cell types are selective to one spatial variable, but invariant to another. For example, place cells are typically invariant to head direction. We propose that all observed ...

Analyzing Neuroimaging Data Through Recurrent Deep Learning Models

Thomas, Armin W. ; Heekeren, Hauke R. ; Müller, Klaus-Robert ; Samek, Wojciech (2019-12-10)

The application of deep learning (DL) models to neuroimaging data poses several challenges, due to the high dimensionality, low sample size, and complex temporo-spatial dependency structure of these data. Even further, DL models often act as black boxes, impeding insight into the association of cognitive state and brain activity. To approach these challenges, we introduce the DeepLight framewor...

Demand-based data stream gathering, processing, and transmission

Traub, Jonas (2019)

The Internet of Things (IoT) consists of billions of devices which form a cloud of network-connected sensor nodes. These sensor nodes supply a vast number of data streams with massive amounts of sensor data. Real-time sensor data enables diverse applications including traffic-aware navigation, machine monitoring, and home automation. Current stream processing pipelines are demand-oblivious, wh...

Behavior and confluence analysis of M-adhesive transformation systems using M-functors

Maximova, Maria (2019)

For modeling dynamic systems, various graphical modeling formalisms exist. In particular, rule-based graph transformation formalisms have proven to be adequate, both to capture system behavior and system adaptations. For some graph transformation-based formalisms there already exist well-established tools, enabling modelers to analyze important semantical properties of considered transformation...

Neurobehavioural patterns of alcohol abuse in adolescence

Matthis, Caroline (2019)

Excessive alcohol consumption has a detrimental effect on public health. Alcohol abuse is a top-ranked disorder of the brain with respect to total costs to economy and is linked to an estimated 3.8 % of global deaths. Often, first experiences with alcohol are made during adolescence, the time of transition between childhood and adulthood. Adolescence marks a period of complex social, biological...

Parallelization of legacy automotive control software for multi-core platforms

Lowinski, Martin (2019)

Automotive control-based applications become more and more sophisticated due to the continuous addition of new functionalities. At present, this functionality is implemented as runnables that are recurrently and sequentially executed inside software tasks. These computing-intensive tasks are typically concurrent to each other and hence can be executed in parallel on multi-core platforms. Due t...

Expanding the analysis of functional Near-Infrared Spectroscopy (fNIRS) data with multivariate techniques

Gemignani, Jessica (2019)

The use of functional Near-Infrared Spectroscopy is experiencing a rapid growth in use in every area of neuroscientific research, but one of the most prolific areas of application is the field of language development in children. If over the past decades there have been incredible advancements on the technology side, the same can not be said about data analysis techniques: for fNIRS, an ad-hoc ...

Real-time inference of word relevance from electroencephalogram and eye gaze

Wenzel, Markus A. ; Bogojeski, Mihail ; Blankertz, Benjamin (2017-08-16)

Objective. Brain-computer interfaces can potentially map the subjective relevance of the visual surroundings, based on neural activity and eye movements, in order to infer the interest of a person in real-time. Approach. Readers looked for words belonging to one out of five semantic categories, while a stream of words passed at different locations on the screen. It was estimated in real-time ...

Implicit relevance feedback from electroencephalography and eye tracking in image search

Golenia, Jan-Eike ; Wenzel, Markus A. ; Bogojeski, Mihail ; Blankertz, Benjamin (2018-01-24)

Objective. Methods from brain–computer interfacing (BCI) open a direct access to the mental processes of computer users, which offers particular benefits in comparison to standard methods for inferring user-related information. The signals can be recorded unobtrusively in the background, which circumvents the time-consuming and distracting need for the users to give explicit feedback to questio...

Unsupervised classification of operator workload from brain signals

Schultze-Kraft, Matthias ; Dähne, Sven ; Gugler, Manfred ; Curio, Gabriel ; Blankertz, Benjamin (2016-04-14)

Objective. In this study we aimed for the classification of operator workload as it is expected in many real-life workplace environments. We explored brain-signal based workload predictors that differ with respect to the level of label information required for training, including entirely unsupervised approaches. Approach. Subjects executed a task on a touch screen that required continuous ef...

Active visual search in non-stationary scenes: coping with temporal variability and uncertainty

Ušćumlić, Marija ; Blankertz, Benjamin (2016-01-04)

Objective. State-of-the-art experiments for studying neural processes underlying visual cognition often constrain sensory inputs (e.g., static images) and our behavior (e.g., fixed eye-gaze, long eye fixations), isolating or simplifying the interaction of neural processes. Motivated by the non-stationarity of our natural visual environment, we investigated the electroencephalography (EEG) corre...

EEG-based classification of video quality perception using steady state visual evoked potentials (SSVEPs)

Acqualagna, Laura ; Bosse, Sebastian ; Porbadnigk, Anne K. ; Curio, Gabriel ; Müller, Klaus-Robert ; Wiegand, Thomas ; Blankertz, Benjamin (2015-03-13)

Objective. Recent studies exploit the neural signal recorded via electroencephalography (EEG) to get a more objective measurement of perceived video quality. Most of these studies capitalize on the event-related potential component P3. We follow an alternative approach to the measurement problem investigating steady state visual evoked potentials (SSVEPs) as EEG correlates of quality changes. U...

Wyrm: A Brain-Computer Interface Toolbox in Python

Venthur, Bastian ; Dähne, Sven ; Höhne, Johannes ; Heller, Hendrik ; Blankertz, Benjamin (2015-05-24)

In the last years Python has gained more and more traction in the scientific community. Projects like NumPy, SciPy, and Matplotlib have created a strong foundation for scientific computing in Python and machine learning packages like scikit-learn or packages for data analysis like Pandas are building on top of it. In this paper we present Wyrm (https://github.com/bbci/wyrm), an open source BCI ...

BNCI Horizon 2020: towards a roadmap for the BCI community

Brunner, Clemens ; Birbaumer, Niels ; Blankertz, Benjamin ; Guger, Christoph ; Kübler, Andrea ; Mattia, Donatella ; Millán, José del R. ; Miralles, Felip ; Nijholt, Anton ; Opisso, Eloy ; Ramsey, Nick ; Salomon, Patric ; Müller-Putz, Gernot R. (2015-02-10)

The brain-computer interface (BCI) field has grown dramatically over the past few years, but there are still no coordinated efforts to ensure efficient communication and collaboration among key stakeholders. The European Commission (EC) has recently renewed their efforts to establish such a coordination effort by funding a coordination and support action for the BCI community called ‘BNCI Horiz...

Integrating neurophysiologic relevance feedback in intent modeling for information retrieval

Jacucci, Giulio ; Barral, Oswald ; Daee, Pedram ; Wenzel, Markus A. ; Serim, Baris ; Ruotsalo, Tuukka ; Pluchino, Patrik ; Freeman, Jonathan ; Gamberini, Luciano ; Kaski, Samuel ; Blankertz, Benjamin (2019-03-12)

The use of implicit relevance feedback from neurophysiology could deliver effortless information retrieval. However, both computing neurophysiologic responses and retrieving documents are characterized by uncertainty because of noisy signals and incomplete or inconsistent representations of the data. We present the first‐of‐its‐kind, fully integrated information retrieval system that makes use ...

Is Neural Activity Detected by ERP-Based Brain-Computer Interfaces Task Specific?

Wenzel, Markus A. ; Almeida, Inês ; Blankertz, Benjamin (2016-10-28)

Objective: Brain-computer interfaces (BCIs) that are based on event-related potentials (ERPs) can estimate to which stimulus a user pays particular attention. In typical BCIs, the user silently counts the selected stimulus (which is repeatedly presented among other stimuli) in order to focus the attention. The stimulus of interest is then inferred from the electroencephalogram (EEG). Detecting ...

A large scale screening study with a SMR-based BCI: Categorization of BCI users and differences in their SMR activity

Sannelli, Claudia ; Vidaurre, Carmen ; Müller, Klaus-Robert ; Blankertz, Benjamin (2019-01-25)

Brain-Computer Interfaces (BCIs) are inefficient for a non-negligible part of the population, estimated around 25%. To understand this phenomenon in Sensorimotor Rhythm (SMR) based BCIs, data from a large-scale screening study conducted on 80 novice participants with the Berlin BCI system and its standard machine-learning approach were investigated. Each participant performed one BCI session wi...