Parkinson’s disease is the second most common neurodegenerative disorder in adults. It severely impairs motor functions causing muscle stiffness, shaking of limbs, slowing and even loss of body movements. Parkinson’s disease is a major cause for motor disability in elderly people and responsible for high treatment costs.
My PhD will focus on developing new protocols of neurofeedback training for Parkinson’s disease patients employing EEG and fMRI. This will involve the exploration and testing of potential electrophysiological biomarkers.
PS1018 – I provide tutorials for 1st year Psychology students (basic statistics, report writing) and mark their course work.
Full list of publications
Research topics and related papersNeurofeedback training
My main interest is the development and application of non-invasive neurotechnology for the rehabilitation and treatment of psychiatric and neurological conditions. In particular, I am fascinated by neurofeedback training and its potential to become an add-on treatment in Neurology and Psychiatry in the near future. Essentially, during neurofeedback training patients engage in mental imagery while being provided with a feedback about the activity of a certain brain region or network of interest. Thereby, patients learn to up or down regulate this activity, which modulates symptom severity. Recent real-time fMRI neurofeedback studies have shown encouraging results in reducing symptoms for neurological (e.g. Parkinson’s disease) as well for psychiatric conditions (e.g. major depressive disorder).
Sulzer, J., Haller, S., Scharnowski, F., et al. (2013). Real-time fMRI neurofeedback: progress and challenges. Neuroimage, 76, 386-399
Motor learning in redundant systems
The biomechanics of the human limbs equip us with more joints than we would need to fulfil a motor task in the 3-dimensional space that we live in. To date we know very little about the learning principles that can describe and predict how the brain learns new movements when being confronted with a redundant task setting. This becomes especially relevant when joint control is impaired due to neural loss (e.g. after stroke) and patients need to “re-learn” physiological movements involving multiple joints. Thus, a better understanding of the relevant learning principles will enable scientists to design more efficient and specific neurorehabilitation regimes.
Wolpert, D. M., Diedrichsen, J., & Flanagan, J. R. (2011). Principles of sensorimotor learning. Nat Rev Neurosci, 12(12), 739-751.
National Institute for Social Care and Health Research (NISCHR)
Dr Jörn Diedrichsen, Institute of Cognitive Neuroscience, University College London
Prof Patricia Ohrmann, Department of Psychiatry & Psychotherapy, University Hospital Münster, Germany
Dr Alexandra Reichenbach, Research and Early Development, Roche Pharmaceuticals, Basel, Switzerland
2013 –2014: Exchange year in Clinical Medicine, Cardiff University School of Medicine
2012 – 2013: Part-time distance studies in Psychology, Fernuniversität in Hagen, Germany
2009 –2012: Studies in Medicine, University of Münster, Germany
2012 – 2013: MD dissertation project, motor control group, Institute of Cognitive Neuroscience, University College London
Thesis title: Robot assisted motor reinforcement learning – reducing natural motor variability in a redundant reaching task.
2010 – 2014: Heinrich Böll Foundation, studentship
2012 – 2014: ERASMUS studentship (London, Cardiff)
2012: German Academic Exchange Service (DAAD), travel grant
2011 – 2012: Research Assistant, Institute of Biomagnetism & Biosignalanalysis,
University of Münster
2010 – 2012: Tutor for 1st and 2nd year medical students in Neuroanatomy, Histology and Biochemistry, University of Münster
2009 & 2010: Visiting research student with Prof Greg Ball and Prof Peter Holland, Department of Psychological & Brain Sciences, Johns Hopkins University