Projects
Brain Computer interfacing: from visual to motion and speech decoding/Detection of enhancement and decline in cognitive abilities from EEG responses KU Leuven
In Brain-Computer Interfacing (BCI), brain activity is recorded and translated into user-intended actions. Several studies have successfully employed BCIs to replace lost or impaired functionality in patients by circumventing disconnected or disfunctional neural pathways. In our work we focus on scalp EEG as well as Electrocorticography (ECoG), a partially invasive recording technique, for which develop stimuluation paradigms and decoders ...
Optimizing the rehabilitation of aphasia patients using quantitative EEG biomarkers for neuroplasticity Ghent University
Aphasia is a disorder that affects the ability to speak, write and/or understand language and is caused by an injury or damage to the brain. There is scientific evidence that event related potentials (ERPs) can be used to diagnose aphasia and follow-up the neuroplasticity of the brain during treatment. ERP components are usually quantified in the average ERP of the patient for a specific task. However, it is known that late ERP components, ...
Bridging the gap between neurally principled models of choice RT and EEG data KU Leuven
In speeded choice response time experiments, participants are asked to make a series of fast choices in response to a series of stimuli as they are presented (“is the object shown on the screen red or green?”). The last few decades, diffusion models have been adopted as the golden standard for describing these data. As the name suggests, diffusion models propose that the process leading up to the choice is inherently noisy: It is said to be a ...
Real-time analysis of high-density EEG signals for neurofeedback applications KU Leuven
The brain is the most complex organ of our body, and a large bulk of research is conducted to understand its basic mechanisms and its impairments associated with neurological deficits. Notably, there are a variety of empirical methods that allow scientists to examine brain functioning. In particular, it is necessary to rely on non-invasive techniques to study brain activity in healthy people and patients. An emerging technique for brain ...
High-end, modular EEG equipment for Brain Computer Interfacing (Flanders BCI Lab) KU Leuven
With Brain Computer Interfaces (BCI's) subjects can control the environment from their brain activity directly, bypassing the need for speech or other forms of muscular activity. Evidently, this has raised great hopes for patients suffering from severe disabilities. After the initial successes, three challenging topics have emerged for the future. First, the hybrid BCI's that aim to achieve a faster and more reliable communication by ...
Distributed digital signal processing algorithms for highdensity wireless EEG sensor networks with application to ASSR based objective hearing thresholds estimation KU Leuven
Electroencephalography (EEG) is used to analyze brain activity and detect brain responses to specific stimuli. It offers a high temporal resolution versus a low spatial resolution. A higher spatial resolution may be obtained by adopting a higher electrodes density together with powerful digital signal processing (DSP) algorithms. However, hundreds of electrodes then have to be wired to an output device that collects and processes all ...
Pinpointing obsessive-compulsive symptom severity: Assessing hypersensitivity for symptom-eliciting visual cues using (frequency-tagging) EEG, eye tracking and stress physiology responses KU Leuven
Obsessive Compulsive Disorder (OCD) is a disabling psychiatric disorder affecting 2-2.5% of the population. It is characterized by anxiety-provoking obsessions and time-consuming compulsions. The clinical expression of OCD is highly heterogenous and available assessment tools entail many limitations. In addition, OCD is associated with numerous comorbidities, which complicate diagnosis and personalized treatment. Against this background, ...
Localizing Cortical Reward Prediction Error Signals Using Combined EEG and fMRI Ghent University
ACC may be involved in reward processing, which is reflected in EEG as 'reward positivity' . We aim to eatablish which part of the brain is producing the reward positivity. A novel design--a combined fMRI/EEG study with a modified time-estimation task will be conducted to explore this question, which will also help clear the role of ACC in reinforcement learning.
Diagnostics of the auditory system using deep-learning-based analysis of EEG signals KU Leuven
When a person listens to sound, various parts of the auditory system are activated, including the brain. We can then measure the brain waves using EEG, decode them and draw conclusions about the auditory system. We aim to develop a computational model of the auditory system, based on state-of-the art, deep-neural-network-based systems for automatic speech recognition. The model will be constructed by letting people listen to natural speech ...