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Priv.-Doz. Dr. Carsten Wolters Dr.rer.nat. Harald Kugel Drd. Gabriel Möddel

Moderne nicht-invasive Methoden zur Erforschung des menschlichen Gehirns: Einführung und Motivation(Teil 2). Priv.-Doz. Dr. Carsten Wolters Dr.rer.nat. Harald Kugel Dr.med. Gabriel Möddel Priv.Doz. Dr. med. Christoph Kellinghaus. Vorlesung, 29.Oktober 2013. Outline.

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Priv.-Doz. Dr. Carsten Wolters Dr.rer.nat. Harald Kugel Drd. Gabriel Möddel

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  1. Moderne nicht-invasive Methoden zur Erforschung des menschlichen Gehirns:Einführung und Motivation(Teil 2) Priv.-Doz. Dr. Carsten Wolters Dr.rer.nat. Harald Kugel Dr.med. Gabriel Möddel Priv.Doz. Dr. med. Christoph Kellinghaus Vorlesung, 29.Oktober 2013

  2. Outline • Updated planning for the lecture • Further introduction to the lecture • Serving as a subject in our DFG-project

  3. Aktuelle Vorlesungsplanung • 15.Oktober: Vorbesprechung und erste Einführung und Motivation (Wolters) • 22.Oktober: Einführung Magnetresonanztomographie (MRT) (Kugel) • 29.Oktober: Weitere Einführung und Motivation zur Vorlesung (Vorwerk, Wagner, Lucka, Wolters) • 5.Nov.: Einführung Magnetresonanztomographie (MRT), Teil 2 (DTI, fMRI, k-Raum) (Kugel) • 12.Nov.: Mathematisch-physikalische Modellierungsgrundlagen zu EEG und MEG (Wolters) • 19.Nov.: Grundlagen von Epilepsie und EEG (Kellinghaus) • 26.Nov.: Epileptische Anfälle und ihre Behandlung (Kellinghaus) • 3.Dez.: Registrierung von MRT: Teil 1 (Wolters) • 10.Dez3.: Registrierung von MRT: Teil 2 (Wolters) • 17.Dez.: Segmentierung von MRT (Wolters) • 7.Jan.: Mathematik des EEG/MEG Vorwärtsproblems, Teil 1 (Wolters) • 14.Jan.: Mathematik des EEG/MEG Vorwärtsproblems, Teil 2 (Wolters) • 21.Jan.: Mathematik des EEG/MEG inversen Problems, Teil 1 (Wolters) • 28.Jan.: Mathematik des EEG/MEG inversen Problems, Teil 2 (Wolters) • 4.Feb.: Epilepsiechirurgie, Teil 3 (Möddel)

  4. Outline • Updated planning for the lecture • Further introduction to the lecture • Serving as a subject in our DFG-project

  5. EEG and MEG source analysis: Source model and the forward problem

  6. Gray and White Matter Gray matter (GM) White matter (WM) T1 weighted Magnetic Resonance Image (T1-MRI)

  7. The source model Microscopic current flow (~5×10-5 nAm) cortex + - source synapse + - - sink cell body Equivalent Current Dipole (Primary current) (~50 nAm) parameters: Size of Macroscopic Neural Activity position : x0 moment : M ~30 mm2 = 5.5×5.5 mm2

  8. EEG forward problem Place a dipole Compute the EEG Simulate quasistatic Maxwell equations

  9. MEG forward problem Place a dipole Compute the MEG Simulate quasistatic Maxwell equations

  10. A 5 compartment volume conductor model

  11. Three-layered human skull

  12. Anisotropy of white matter (WM) Transversally: 1 Longitudinally: 9

  13. Volume conductor modeling Finite Element (FE) Boundary element Spherical shells

  14. State-of-the-art finite element volume conductor model [Pursiainen, Lucka & Wolters, Phys Med Biol, 2012] [Drechsler, Wolters, Dierkes & Grasedyck, NeuroImage, 2009] [Lew, Wolters, Dierkes, Röer & MacLeod, Appl. Num. Math., 2009] [Wolters, Köstler, Möller, Härtlein, Grasedyck & Hackbusch, SIAM Journal on Scientific Computing, 2007] [Wolters, Anwander, Berti & Hartmann, IEEE Trans Biomed.Eng., 2007] [Wolters, Anwander, Reitzinger & Kuhn, Comp.Vis.Sci., 2002]

  15. Validation of forward and inverse modeling

  16. Multilayer sphere model 4-layer sphere model with 3-layer skull: Radii: 92, 86:84:82:80, 78mm; Cond.: 0.33, 0.0062:0.021:0.0049, 1.79, 0.33 S/m Sources: Depth from midpoint to CSF boundary 134 regularly distributed electrodes: On a sphere with radius: 92mm Needle electrode (“point in space”)

  17. [Drechsler, Wolters, Dierkes, Si & Grasedyck, NeuroImage, 2009] Constrained Delaunay Tetrahedralization Tetrahedra mesh: Coarse in brain, fine in CSF/skull/skin compartment: Nodes: 360,056 Elements: 2,165,281

  18. Validation: FEM validated with analytic [Drechsler, Wolters, Dierkes & Grasedyck, NeuroImage, 2009] [Lew, Wolters, Dierkes, Röer & MacLeod, Appl. Num. Math., 2009] [Wolters, Köstler, Möller, Härtlein, Grasedyck & Hackbusch, SIAM Journal on Scientific Computing, 2007] [Wolters, Anwander, Berti & Hartmann, IEEE Trans Biomed.Eng., 2007] [Wolters, Anwander, Reitzinger & Kuhn, Comp.Vis.Sci., 2002] 4% 3% 2% 1% 0% 15% 10% 5% 0%

  19. Analytic forward, FEM based dipole fit inverse:localization error due to numerical error

  20. Evoked Potentials (EP) and Fields (EF)

  21. Auditory evoked potentials (AEP) and Fields (AEF)

  22. [Gazzaniga, Ivry & Mangun, Cognitive Neuroscience, 2nd ed., W.W.Norton & Company, 2002] Evoked responses

  23. [Gazzaniga, Ivry & Mangun, Cognitive Neuroscience, 2nd ed., W.W.Norton & Company, 2002] Auditory evoked potential (AEP) Only contralateral path is shown.

  24. Tonotopy in auditory cortex:Preliminary results • Combined EEG/MEG measurement in lying position • presentation of 800ms sine tones • 350, 1400 and 5600Hz • Stimulus Offset Asynchrony (SOA) of 3.5 to 4.5sec • 3rd order synthetic gradiometer • Baseline correction using -200ms to 0ms • 1-20 Hz filter • Voltage-threshold-based eye artefact rejection

  25. MGFP

  26. SNR

  27. 350 Hz Example Signals A0206 MEG SNR: 14.0 EEG SNR: 18.2 MEG SNR: 8.3 EEG SNR: 12.5 5600 Hz 1400 Hz MEG SNR: 14.5 EEG SNR: 13.9

  28. Example Topographies A0206 350 Hz 5600 Hz 1400 Hz

  29. Two dipole Solution

  30. Auditory tonotopy: Preliminary results Discussion and outlook Result1: 2 of 3 subjects show a trend of more medially localized dipoles with increasing frequency, in agreement with findings of (Pantev et al., 1988; Yamamato et al., 1988; Lütkenhöner et al., 1998). Result2: No trend was observed for inferior-superior or anterior-posterior locations. Outlook: Additional subjects will be studied to obtain statistically more significant results.

  31. Somatosensory evoked potentials (SEP) and Fields (SEF)

  32. SEP/SEF source analysis using the FEM

  33. EEG/MEG calibration using SEP/SEF data [Wolters, Lew, Hämäläinen & MacLeod, Proc. DGBMT, 2010] EEG SNR: 24dB MEG SNR: 30dB • Brain conductivity of 0.332 S/m • Skull conductivity of 0.0133 S/m (=> brain:skull ratio of 25) • Explained variance; SEP 93%, SEF 96.1%

  34. [Lanfer, diploma thesis, 2007] SEP/SEF source analysis results SEP dipole (red) and SEF dipole (blue)

  35. S1 and M1 homunculi

  36. [Roberts, Poeppel and Rowley, MEG and magnetic source imaging, Neuropsychiatry Neuropsych.Behav.Neurol., 11, pp.49-64, 1998] Clinical applicability of SEP/SEF source analysis Tumor near the central sulcus

  37. [Roberts, Poeppel and Rowley, MEG and magnetic source imaging, Neuropsychiatry Neuropsych.Behav.Neurol., 11, pp.49-64, 1998] Clinical applicability of SEP/SEF source analysis Tactile stimulation of the right index finger: SEF (left) and fitted dipole (right)

  38. [Roberts, Poeppel and Rowley, MEG and magnetic source imaging, Neuropsychiatry Neuropsych.Behav.Neurol., 11, pp.49-64, 1998] Clinical applicability of SEP/SEF source analysis Tumor (green) and MEG dipole fits (red) for continuous stimulation of fingers and toes

  39. Outline • Literature for this lecture • Introduction to the lecture • Serving as a subject in our DFG-project

  40. Serving as a subject for our epilepsy project Institut für Biomagnetismus und Biosignalanalyse Malmedyweg 15 Direkt hinter der HNO Klinik http://biomag.uni-muenster.de carsten.wolters@uni-muenster.de

  41. Thank you for your attention!

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