Real-time analysis of connectivity in the human brain using high-density electroecenphalography
KU Leuven University
1 or 2 semesters
While visualization of brain activity has well established practical applications such as real-time functional mapping or neurofeedback, visual representation of brain connectivity is not widely used. In addition, technically challenging ongoing connectivity estimation may have hindered practical usage of connectivity in real-time applications. Our lab has developed advanced methods for the offline estimation of brain connectivity from high-density (256-channel) EEG recordings, including tools for bad channel detection and interpolation, filtering, artifact removal, head modeling and source localization. In this project, we will develop algorithms that are capable of estimating and visualizing connectivity between brain sources in real time. We aim to demonstrate that connectivity patterns can be observed online during EEG measurements, which is a first step towards the implementation of connectivity-based neurofeedback protocols.
The project is available in the Fall and Spring semester.
The project is also open for recently graduated undergraduate students and for graduate students..
Number of places available: 2 per semester.
- C/C++ and MATLAB programming skills
- Experience with parallel processing and real-time applications
- Basic interest in neuroscientific questions
The department of Kinesiology is characterized by a multidisciplinary approach, spanning a broad range of disciplines that encompasses the behavioral sciences, neurosciences and movement sciences/kinesiology. In particular, research is aimed at understanding the neural basis of movement deficits, as well as at identifying novel approaches to enhance the human rehabilitation potential. State-of-the-art methodologies such as structural imaging, functional imaging with real-time kinematic recordings, electroencephalography and non-invasive transcranial stimulation are routinely used. Within the department of Kinesiology, the Brain Imaging and Neural dynamics (BIND) group investigates neuronal communication in large-scale networks at a variety of temporal and spatial scales, combining a set of different brain imaging and brain stimulation techniques. Our research endeavor is expected to deliver advanced brain imaging methods for neuroscientists studying different aspects of brain organization, as well as long-needed theoretical foundations and tools supporting individualized treatment of neurological and psychiatric patients.