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Conference Paper

Functional Magnetic Resonance Imaging based BCI for Neurorehabilitation

MPS-Authors
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Veit,  R
Former Department MRZ, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Uludag,  K
Former Department MRZ, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Gaber,  TJ
Former Department MRZ, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

External Resource

https://www.semanticscholar.org/paper/Functional-Magnetic-Resonance-Imaging-based-BCI-for-Sitaram-VeitRCaria/4a6f73180600d8395ae3bc89ab8524bc7cfafb50
(Abstract)

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Citation

Sitaram, R., Veit, R., Caria, A., Uludag, K., Gaber, T., Kuebler, A., et al. (2006). Functional Magnetic Resonance Imaging based BCI for Neurorehabilitation. In G. Müller-Putz (Ed.), 3rd International Brain-Computer Interface Workshop and Training Course 2006 (pp. 106-107). Graz, Austria: Verlag der Technischen Universität Graz.


Cite as: https://hdl.handle.net/21.11116/0000-0004-99E0-2
Abstract
We have developed a Brain-Computer Interface (BCI) based on functional magnetic resonance imaging (fMRI) that provides real-time feedback of blood oxygen level-dependent (BOLD) response from specific, localized regions of the brain. The approach presents new opportunities for behaviour therapy by training patients to control abnormal activity in selected brain regions. Study of neuroplasticity and functional reorganisation for recovery after neurological diseases, such as stroke, is of clinical importance. Here, we report results of self-regulation training of supplementary motor area (SMA) on 4 healthy volunteers.