Catharina Zich, PhD Candidate
Department für Psychologie
Tel.: +49 (0)441 - 798-5510
Fax.:+49 (0)441 - 798-5522
Raum: Gebäude A07–0–049
I am interested in the application of EEG based neurofeedback as a rehabilitation approach for patients suffering from neuromuscular disabilities. My current objective is to better understand the neuronal mechanisms of motor imagery, as movement imagination is a good strategy to control brain computer interfaces (BCI) when real movements are not possible. Furthermore I want to explore if the ability to control a BCI using motor imagery can be trained and how the underlying neural mechanisms change during long-term practice. Therefore I am using high-density EEG in the lab as well as individualized low-density EEG systems in daily-life environments and concurrent EEG-fMRI.
Education - Career
PhD student at the Carl von Ossietzky University Oldenburg, Oldenburg, Germany
M.Sc. Neurocognitive Psychology, Carl von Ossietzky University Oldenburg, Germany
B.A. Philosophy-Neuroscience-Cognition, Otto-von-Guericke-University-Magdeburg, Germany
Kranczioch C, Zich C, Schierholz I, Sterr A.
Mobile EEG and its potential to promote the theory and application of imagery-based motor rehabilitation.
Int. J. Psychophysiol. (2013), http://dx.doi.org/10.1016/j.ijpsycho.2013.10.004.
Zich C, De Vos M, Kranczioch C, Debener S.
Wireless EEG with individualized channel layout enables efficient motor imagery training.
Clin Neurophysiol. (2014), DOI:10.1016/j.clinph.2014.07.007.
Zich C, Debener S, De Vos M, Kranczioch C, Gutberlet I.
Real-time artifact correction enables EEG-based feedback inside the fMRI scanner.
Proceedings of the 6th International Brain-Computer Interface Conference 2014, Verlag der Technischen Universität Graz. (2014). DOI:10.3217/978-3-85125-378-8-25.
Zich C, Debener S, Kranczioch C, Bleichner MG, Gutberlet I, De Vos M.
Real-time EEG feedback during simultaneous EEG-fMRI identifies the cortical signature of motor imagery.
NeuroImage (under rev.). Zich C, Debener S, De Vos M, Frerichs S, Maurer S, Kranczioch C. Lateralization patterns of covert but not overt movements change with age: An EEG neurofeedback study. NeuroImage (under rev.).
- IEEE Journal of Biomedical and Health Informatics
- Journal of Neuroscience Methods
Best Student Paper/Talk Award, 6th International Brain-Computer Interface Conference 2014, Graz
MASTER THESIS AND PRACTIAL PROJECT OPPORTUNITIES
Help the brain-computer interface illiterates to learn motor imagery using a new rich feedback
A non-negligible portion of individuals cannot control a Brain-computer interface (BCI), understanding and solving the problem of BCI illiteracy is one of the biggest research challenges in the field. Our recent study, combining EEG and fMRI to study motor imagery, provides new findings on the subject. In future we want to investigate whether BCI illiterates can learn to control a BCI by using a new rich feedback. If you are interessted in this or related topics just email me (catharina.zich(at)uni-oldenburg.de).