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Prof. Dr.-Ing. habil. Jens Haueisen
Director of the BMTI Institute and head of Biomedical Engineering Group
Prof. Dr.-Ing. habil. Jens Haueisen
phone: +49 3677 69 2861
Understanding the maturation proces of the brain of neonates and its pathologies is a highly topical question in medical research. The characterisation of brain activity with high temporal and spatial resolution from EEG and MEG (source localisation) is highly suitable for this task due to its non-invasive nature. This, however, is very difficult in this developmental period, because the open fontanelles and sutures of the growing skull represent conductivity inhomogeneities which can not be accounted for with the currently established Boundary Element Method (BEM). Additionally, the BE method cannot model the directionality (anisotropy) of the electric conductivity that is present especially in the nerve fibres of the white brain matter. In these conventional models, the neglect of important bioelectrical material properties of the head tissue leads to an intolerable loss of accuracy for a multitude of applications of source reconstruction in basic neurological and medical research as well as in the clinical practice (pre-surgical mapping, epilepsy diagnostics).
The objective of this project is the development of a new approach for realistic modelling of conductivity and anisotropy distributions in the head using the finite element method (FEM) for which the computation time is only a few minutes even for high model resolutions. A FE model decomposes the head and brain in volume elements of arbitrary size, e.g. tetrahedra, with can be individual conductivity properties derived from a diffusion weighted MRI (Diffusion Tensor Imaging – DTI) such as the one in the figure to the left. Firstly, the sensitivity of the source reconstruction accuracy to the model resolution is investigated with computer simulations. Then, the absolute accuracy of the localisation of electromagnetic activity in the brain of animals and humans is validated experimentally. The project outcome will be the worlds first practical FE modelling method, which improves source localisation methodology and therefore leads to a more accurate diagnosis and to a more accurate results in the field of neuroscience.