title: The role of blood vessels in high-resolution volume conductor head modeling of EEG.
abstract: Reconstruction of the electrical sources of human EEG activity at high spatio-temporal accuracy is an important aim in neuroscience and neurological diagnostics. Over the last decades, numerous studies have demonstrated that realistic modeling of head anatomy improves the accuracy of source reconstruction of EEG signals. For example, including a cerebro-spinal fluid compartment and the anisotropy of white matter electrical conductivity were both shown to significantly reduce modeling errors. Here, we for the first time quantify the role of detailed reconstructions of the cerebral blood vessels in volume conductor head modeling for EEG. To study the role of the highly arborized cerebral blood vessels, we created a submillimeter head model based on ultra-high-field-strength (7T) structural MRI datasets. Blood vessels (arteries and emissary/intraosseous veins) were segmented using Frangi multi-scale vesselness filtering. The final head model consisted of a geometry-adapted cubic mesh with over 17×10(6) nodes. We solved the forward model using a finite-element-method (FEM) transfer matrix approach, which allowed reducing computation times substantially and quantified the importance of the blood vessel compartment by computing forward and inverse errors resulting from ignoring the blood vessels. Our results show that ignoring emissary veins piercing the skull leads to focal localization errors of approx. 5 to 15mm. Large errors (>2cm) were observed due to the carotid arteries and the dense arterial vasculature in areas such as in the insula or in the medial temporal lobe. Thus, in such predisposed areas, errors caused by neglecting blood vessels can reach similar magnitudes as those previously reported for neglecting white matter anisotropy, the CSF or the dura - structures which are generally considered important components of realistic EEG head models. Our findings thus imply that including a realistic blood vessel compartment in EEG head models will be helpful to improve the accuracy of EEG source analyses particularly when high accuracies in brain areas with dense vasculature are required.
authors.affiliation: Intracranial EEG and Brain Imaging Lab, Epilepsy Center, University Hospital Freiburg, Germany; Neurobiology and Biophysics, Faculty of Biology, University of Freiburg, Germany; BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany; Bernstein Center Freiburg, University of Freiburg, Germany. Electronic address: lukas.fiederer@uniklinik-freiburg.de.
authors.forename: L D J
authors.initials: LDJ
authors.lastname: Fiederer
authors.affiliation: Institute for Biomagnetism and Biosignalanalysis, University of Münster, Germany.
authors.forename: J
authors.initials: J
authors.lastname: Vorwerk
authors.affiliation: Institute for Biomagnetism and Biosignalanalysis, University of Münster, Germany; Institute for Computational and Applied Mathematics, University of Münster, Germany; Department of Computer Science, University College London, WC1E 6BT London, UK.
authors.forename: F
authors.initials: F
authors.lastname: Lucka
authors.affiliation: Scientific Computing and Imaging Institute, 72 So. Central Campus Drive, Salt Lake City, Utah 84112, USA; Center for Integrative Biomedical Computing, University of Utah, 72 S. Central Campus Drive, 84112, Salt Lake City, UT, USA.
authors.forename: M
authors.initials: M
authors.lastname: Dannhauer
authors.affiliation: Dept. of Biomedical Magnetic Resonance, Otto-von-Guericke University Magdeburg, Germany.
authors.forename: S
authors.initials: S
authors.lastname: Yang
authors.affiliation: Intracranial EEG and Brain Imaging Lab, Epilepsy Center, University Hospital Freiburg, Germany; BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany.
authors.forename: M
authors.initials: M
authors.lastname: Dümpelmann
authors.affiliation: BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany; Bernstein Center Freiburg, University of Freiburg, Germany.
authors.forename: A
authors.initials: A
authors.lastname: Schulze-Bonhage
authors.affiliation: Neurobiology and Biophysics, Faculty of Biology, University of Freiburg, Germany; Bernstein Center Freiburg, University of Freiburg, Germany.
authors.forename: A
authors.initials: A
authors.lastname: Aertsen
authors.affiliation: Dept. of Biomedical Magnetic Resonance, Otto-von-Guericke University Magdeburg, Germany; Leibniz Institute for Neurobiology, Magdeburg, Germany; German Center for Neurodegenerative Diseases (DZNE), Site Magdeburg, Germany; Center for Behavioral Brain Sciences, Magdeburg, Germany.
authors.forename: O
authors.initials: O
authors.lastname: Speck
authors.affiliation: Institute for Biomagnetism and Biosignalanalysis, University of Münster, Germany.
authors.forename: C H
authors.initials: CH
authors.lastname: Wolters
authors.affiliation: Intracranial EEG and Brain Imaging Lab, Epilepsy Center, University Hospital Freiburg, Germany; BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany; Bernstein Center Freiburg, University of Freiburg, Germany.
authors.forename: T
authors.initials: T
authors.lastname: Ball
mesh_terms: D001921:Brain / Q000098:blood supply*; D002560:Cerebrovascular Circulation; D004569:Electroencephalography; D020342:Finite Element Analysis; D006257:Head / Q000033:anatomy & histology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008953:Models, Anatomic; D008959:Models, Neurological
keywords: 7T MRI; Blood vessel modeling; EEG source localization; Extended source model; FEM; Forward problem; Inverse problem; Submillimeter volume conductor head model