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Development and validation of methods for localisation of brain activity using the finite element method (FEMINVERS)

Project description

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.

Image 1: Reconstructed nerve fibre tracks of the rabbit brain (coronary view) on top of a T2-weighted MRI slice. Colour-coded are fibre tracks pervading the following brain structures: Corpus callosum genu (yellow), Corpus callosum splenium (blue), Capsula interna anterior (red), brain stem (light blue) and a cranial nerve leading to frontal head areas (pink)

Project partner

  • Institute for Biomagnetism and Biosignalanalysis, University of Münster
  • Max-Planck-Institute of Mathematics in the Sciences, Leipzig
  • Max-Planck-Institute for Human Cognitive and Brain Science, Leipzig
  • Biomagnetic Center Jena, University Hospital, Friedrich-Schiller-University Jena

Publications & patents

  • Jochmann, T., Güllmar,D., Haueisen, J., Reichenbach, J.R.: Influence of tissue conductivity changes on the EEG signal in the human brain – A simulation study, Z. Med. Phys. 21(2):102-12, 2011
  • Güllmar, D., Haueisen, J., Reichenbach, J.R.: Influence of anisotropic electrical conductivity in white matter tissue on the EEG/MEG forward and inverse solution. A high resolution whole head simulation study. Neuroimage, 51: 145–163, 2010
  • Ramon,C., Freeman,W.J., Holmes,M,D., Ishimaru,A., Haueisen,J., Schimpf,P.H.,  Rezvanian,E.: Similarities between Simulated Spatial Spectra of Scalp EEG, MEG and Structural MRI. Brain Topography, 22(3):191-6, 2009
  • Güllmar,D., Haueisen,J., Eiselt,M., Gießler,F., Flemming,L., Anwander,A., Knösche,T.R., Wolters,C.H., Dümpelmann,M., Tuch,D.S., Reichenbach,J.R.: Influence of anisotropic conductivity on EEG source reconstruction: Investigations in a rabbit model. IEEE Transactions on Biomedical Engineering, 53:1841-1850, 2006
  • Schimpf,P.H., Liu,H., Ramon,C., Haueisen,J.: Efficient Electromagnetic Source Imaging With Adaptive Standardized LORETA/FOCUSS. IEEE Transactions on Biomedical Engineering, 52(5): 901 - 908, 2005
  • Schimpf,P.H., Haueisen,J., Ramon,C.: Ellipsoidal refinement of the minimum norm: Performance in an anatomically realistic EEG model. IEEE Transactions on Biomedical Engineering, 51(4): 679-683, 2004
  • Ramon,C., Schimpf,P., Haueisen,J., Holmes,M., Ishimaru,A.: Role of soft bone, CSF and gray matter in EEG simulations. Brain Topography 16(4):245-248 2004
  • Baysal,U. and Haueisen,J.: Use of a priori information in estimating tissue resistivities - application to human data in vivo. Physiological Measurement, 25 (3): 737-748, 2004
  • Haueisen,J., Tuch,D.S., Ramon,C., Schimpf,P.H., Wedeen,V.J., George, J.S., Belliveau,J.W.: The influence of brain tissue anisotropy on human EEG and MEG. Neuroimage, 15, 159-166, 2002
  • Schimpf,P.H., Ramon,C., Haueisen,J.: Dipole Models for the EEG and MEG. IEEE Transactions on Biomedical Engineering, 49, 409-418,
  • 2002Czapski,P., Ramon,C., Haueisen,J., Huntsmann,L.L., Nowak,H., Bardy,G.H., Leder,U., Kim,Y.:  MCG simulations of myocardial infarctions with a realistic heart-torso model. IEEE Transactions on Biomedical Engineering 45(11), 1313-1322, 1998
  • Ramon.C., Czapski,P., Haueisen,J., Huntsman,L.L., Nowak,H., Bardy,G.H., Leder,U., Kim,Y., Nelson,J.A.:  MCG Simulations with a realistic heart-torso model. IEEE Transactions on Biomedical Engineering, 45(11), 1323-1331, 1998
  • Haueisen,J., Ramon,C., Eiselt,M., Nowak,H., Brauer,H.: Influence of Tissue Resistivities on Neuromagnetic Fields and Potentials studied with a Finite Element Model of the Head. IEEE Transactions on Biomedical Engineering, 44(8), 727 - 735, 1997