UNIVERSITY DEPARTMENT OF NEUROLOGY

Neurocybernetics and Rehabilitation

Head

Dr. Catherine Sweeney-Reed, MBBS, BSc (Hons. Neuroscience), PhD (Cybernetics)

Staff

Tessa Huchtemann, assistent physician
Dr. Susanne Abdulla, assistent physician
Johanna Schwertner, doctoral student
Franziska Röhner, doctoral student

Collaborations

  • Prof. Adriano Andrade (Faculty of Electrical Engineering, Federal University of Uberlandia, Brazil)
  • Dr. Lars Buentjen (University Clinic for Stereotactic Neurosurgery, Magdeburg)
  • Dr. Ian Daly (School of Systems Engineering, University of Reading, UK)
  • Prof. Robert T. Knight (Helen Wills Neuroscience Institute and Department of Psychology, University of California, Berkeley, USA)
  • PD Dr. Kerstin Krauel (University Clinic for Child and Adolescent Psychiatry, Magdeburg)
  • Prof. Jose Millan (Biotechnology, Swiss Federal Institute of Technology in Lausanne, Geneva, Switzerland)
  • Prof. Slawomir Nasuto (School of Systems Engineering, University of Reading, UK)
  • Mr. Christoph Reichert (University Clinic for Neurology, Magdeburg)
  • Dr. Katharina Rufener (University Clinic for Child and Adolescent Psychiatry, Magdeburg)
  • Prof. Michael D. Rugg (Center for Vital Longevity and School of Behavioral and Brain Sciences, University of Texas, Dallas, USA)
  • Prof. Michael Sailer (Neurology und Restorative Neurology, Median Clinic: Neurological Rehabilitation Centre, Magdeburg)
  • Dr. Friedhelm Schmitt (University Clinic for Neurology, Magdeburg)
  • Dr. Martin Walter (University Clinic for Neurology, Magdeburg)
  • Dr. Tino Zaehle (University Clinic for Neurology, Magdeburg)

Topic

Cybernetics refers to the multidisciplinary study of control systems involving biological entities and encompasses fi elds ranging from neuroscience, medicine, and psychology to electrical, mechanical, and systems engineering. Rehabilitative cybernetic systems involve therapeutic communication between human and machine, in which feedback in either direction infl uences the ongoing interactions within the system. Neurocybernetics more specifi cally refers to such interaction between the nervous system and a computer or machine.
Our aim is to deepen our understanding of how the brain processes information through the application of neurocybernetic systems, in order to underpin the development of new diagnostic approaches and to facilitate functional recovery from neurological disease.
Neural signals are recorded from the brain using a range of modalities, including EEG (electroencephalogram: electrical brain signals recorded from electrodes on the scalp surface), ECoG (electrocorticogram: recording directly from the cortex), intracranial depth recordings (from subcortical structures), and fMRI (functional magnetic resonance imaging).

Current projects include the following:

  • BCI (brain computer interface) controlled functional neuromuscular stimulation of upper limb musculature to facilitate rehabilitation following acute stroke
  • Transcranial electrical stimulation of frontal and parietal brain regions to improve persistent working memory impairment following frontal lobe damage
  • The role of the anterior nucleus of the thalamus in human episodic memory formation

Selected References

Sweeney-Reed, C.M., Zaehle, T., Voges, J., Schmitt, F.C., Buentjen, L., Kopitzki, K., Richardson-Klavehn, A., Hinrichs, H., Heinze, H.-J., Knight, R.T., Rugg, M.D. (2016). Pre-stimulus thalamic theta power predicts human memory formation. NeuroImage, in press. doi: 10.1016/j.neuroimage.2016.05.042 [Epub ahead of print]

Sweeney-Reed, C.M., Zaehle, T., Voges, J., Schmitt, F.C., Buentjen, L., Kopitzki, K., Richardson-Klavehn, A., Hinrichs, H., Heinze, H.-J., Knight, R.T., Rugg, M.D. (2016). Neuropsychological profile and pre-stimulus dorsomedial thalamic nucleus theta power associated with successful memory formation in deep brain stimulation patients. Data in Brief, in press. doi:10.1016/j.dib.2016.06.008

Hausmann J, Sweeney-Reed CM, Sobieray U, Matzke M, Heinze HJ, Voges J, Buentjen L.J. (2015). Functional electrical stimulation through direct 4-channel nerve stimulation to improve gait in multiple sclerosis: a feasibility study. Neuroeng Rehabil. 12(1):100. doi: 10.1186/s12984-015-0096-3

Borchardt V, Krause AL, Li M, van Tol MJ, Demenescu LR, Buchheim A, Metzger CD, Sweeney-Reed CM, Nolte T, Lord AR, Walter M. (2015). Dynamic disconnection of the supplementary motor area after processing of dismissive biographic narratives. Brain Behav. 5(10):e00377. doi: 10.1002/brb3.377

Sweeney-Reed, C. M., Zaehle, T., Voges, J., Schmitt, F. C., Buentjen, L., Kopitzki, K., Hinrichs, H., Heinze, H.-J., Rugg, M.D., Knight, R.T., Richardson-Klavehn, A. (2015). Thalamic theta phase alignment predicts human memory formation and anterior thalamic cross-frequency coupling. eLife:10.7554/eL(May). doi:http://dx.doi.org/10.7554/eLife.07578

Körtvélyessy, P., Gukasjan, A., Sweeney-Reed, C.M., Heinze, H.-J., Thurner, L., Bittner, D.M. (2015). Progranulin and amyloid-β Levels: relationship to neuropsychology in frontotemporal and Alzheimer’s Disease. Journal of Alzheimer's Disease. 46(2):375-80. doi: 10.3233/JAD-150069

Sweeney-Reed, C. M., Zaehle, T., Voges, J., Schmitt, F. C., Buentjen, L., Kopitzki, K., Esslinger, C., Hinrichs, H., Heinze, H.-J-, Knight, R.T., Richardson-Klavehn, A. (2014). Corticothalamic phase synchrony and cross-frequency coupling predict human memory formation. eLife, 3:e05352:1–18. doi:10.7554/eLife.05352

Daly, I., Faller, J., Scherer, R., Sweeney-Reed, C. M., Nasuto, S. J., Billinger, M., Müller-Putz, G. R. (2014). Exploration of the neural correlates of cerebral palsy for sensorimotor BCI control. Frontiers in Neuroengineering, 7(July):1–11. doi:10.3389/fneng.2014.00020

Sweeney-Reed, C. M., Riddell, P. M., Ellis, J. A., Freeman, J. E., Nasuto, S. J. (2012). Neural correlates of true and false memory in mild cognitive impairment. PloS ONE, 7(10):e48357. doi:10.1371/journal.pone.0048357

Daly, I., Sweeney-Reed, C. M., Nasuto, S. J. (2012). Testing for signifi cance of phase synchronisation dynamics in the EEG. J. Comput. Neurosci. 34(3):411-32. doi:10.1007/s10827-012-0428-2

Sweeney-Reed, C. M., & Nasuto, S. J. (2009). Detection of neural correlates of self-paced motor activity using empirical mode decomposition phase locking analysis. Journal of Neuroscience Methods, 184(1):54–70. doi:10.1016/j.jneumeth.2009.07.023

Sweeney-Reed, C. M., & Nasuto, S. J. (2007). A novel approach to the detection of synchronisation in EEG based on empirical mode decomposition. Journal of Computational Neuroscience, 23(1):79–111. doi:10.1007/s10827-007-0020-3

Andrade, A. O., Nasuto, S., Kyberd, P., Sweeney-Reed, C. M., van Kanijn, F. R. (2006). EMG signal fi ltering based on Empirical Mode Decomposition, 1:44–55. doi:10.1016/j.bspc.2006.03.003

Andrade, A. O., Nasuto, S., Kyberd, P., Sweeney-Reed, C. M. (2005). Generative topographic mapping applied to clustering and visualization of motor unit action potentials, 82:273–284. doi:10.1016/j.biosystems.2005.09.004

 

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