{"id":{"repo_id":"aachen","oai_identifier":"oai:publications.rwth-aachen.de:56989"},"canonical_url":"https://search.dev.ndltd.org/etd/aachen/oai:publications.rwth-aachen.de:56989","repository":{"repo_id":"aachen","name":"RWTH Aachen University","base_url":"https://publications.rwth-aachen.de/oai2d"},"display":{"title":"Zeitabhängige Stromdichterekonstruktion in einem standardisierten Finite-Elemente-Kopfmodell","abstract":"The content of this work was the reconstruction of neuronal activity in a standardized headmodel under consideration of additional constraints on the time course of the solution. The thesis is divided into five chapters which describe the physiological basis of the neuronal generators of the electromagnetic fields and potentials, the finite element solution of the bioelectromagnetic forward solution, the solution of the inverse problem, the validation of the proposed algorithms and solutions and the implementation of a eeg-data analysis software package. The aim of the work was the extension and improvement of the existing sourcemodels by introducing an additional temporal modelterm and the simplification of the forward solution of realistic model by using a standardized head. The fMRI phantom created by Collins et al. was chosen as a generic model of the head. Based on voxel intensities of this MR image a cubic FE mesh with 2.5 mm sidelength was created. On the surface of this model, a larger number of equally spaced electrode positions was created and the a solution for all sensors was calculated for sourcelocations on a regular grid within the cortex. In order to verify the model, sources in individual head models were simulated and then reconstructed with the aid of the standard model. The localization error of the reconstructed sources was found to be less than one gridlength of the cortical reconstruction grid. In order to expand the source model such that a priori knowledge about the timecourse of the sources could be incorporated, a bayesian approach to inverse problem was used. Two basic temporal constraints were introduced, smoothness of first order and smoothness of second order and the properties of the temporal constrained source reconstruction were compared to spatial constrained reconstruction methods (e.g. minimum, LORETA). Two measures were used, the localization error of the sources and the correlation coefficient between the original and the reconstructed timecourses of the sources.Additonal physiological boundary conditions for the temporal constraints were introduced and a modified numerical efficient algorithm for the solution of the temporal constrained problem was proposed. The localization error and the correlation were analyzed for simulations on a planar model and also on a realistically shaped headmodel. Under assumption of biological noise, the temporal constrained methods yielded improved reconstruction results. The methods were also tested on experimental data. Three stimulation setups were used, i.e an acoustic, a visual and somatosensoric stimulus were presented and source reconstruction was done using spatially constrained and temporal constrained methods. All described methods and algorithms were implemented in an easi-to-use software package for efficient data processing.","abstract_html":"The content of this work was the reconstruction of neuronal activity in a standardized headmodel under consideration of additional constraints on the time course of the solution. The thesis is divided into five chapters which describe the physiological basis of the neuronal generators of the electromagnetic fields and potentials, the finite element solution of the bioelectromagnetic forward solution, the solution of the inverse problem, the validation of the proposed algorithms and solutions and the implementation of a eeg-data analysis software package. The aim of the work was the extension and improvement of the existing sourcemodels by introducing an additional temporal modelterm and the simplification of the forward solution of realistic model by using a standardized head. The fMRI phantom created by Collins et al. was chosen as a generic model of the head. Based on voxel intensities of this MR image a cubic FE mesh with 2.5 mm sidelength was created. On the surface of this model, a larger number of equally spaced electrode positions was created and the a solution for all sensors was calculated for sourcelocations on a regular grid within the cortex. In order to verify the model, sources in individual head models were simulated and then reconstructed with the aid of the standard model. The localization error of the reconstructed sources was found to be less than one gridlength of the cortical reconstruction grid. In order to expand the source model such that a priori knowledge about the timecourse of the sources could be incorporated, a bayesian approach to inverse problem was used. Two basic temporal constraints were introduced, smoothness of first order and smoothness of second order and the properties of the temporal constrained source reconstruction were compared to spatial constrained reconstruction methods (e.g. minimum, LORETA). Two measures were used, the localization error of the sources and the correlation coefficient between the original and the reconstructed timecourses of the sources.Additonal physiological boundary conditions for the temporal constraints were introduced and a modified numerical efficient algorithm for the solution of the temporal constrained problem was proposed. The localization error and the correlation were analyzed for simulations on a planar model and also on a realistically shaped headmodel. Under assumption of biological noise, the temporal constrained methods yielded improved reconstruction results. The methods were also tested on experimental data. Three stimulation setups were used, i.e an acoustic, a visual and somatosensoric stimulus were presented and source reconstruction was done using spatially constrained and temporal constrained methods. All described methods and algorithms were implemented in an easi-to-use software package for efficient data processing.","abstract_has_math":false,"creators":["Darvas, Felix"],"institution":"Publikationsserver der RWTH Aachen University","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Buchner, Helmut"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2002,"date_issued":"2002","date_published":"2002","updated_at":"2026-07-30T19:42:01Z","subjects":["info:eu-repo/classification/ddc/610","Medizin"],"languages":["ger"],"rights":["info:eu-repo/semantics/openAccess"],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["https://publications.rwth-aachen.de/search?p=id:%22RWTH-CONV-119061%22"],"render_values":[{"text":"https://publications.rwth-aachen.de/search?p=id:%22RWTH-CONV-119061%22","href":"https://publications.rwth-aachen.de/search?p=id:%22RWTH-CONV-119061%22","code":true}]}]},"links":{"outbound_url":"https://publications.rwth-aachen.de/record/56989","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Buchner, Helmut"]},{"key":"dc:creator","label":"Author","values":["Darvas, Felix"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:coverage","label":"Dc Coverage","values":["DE"]},{"key":"dc:date","label":"Dc Date","values":["2002"]},{"key":"dc:publisher","label":"Institution","values":["Publikationsserver der RWTH Aachen University"]},{"key":"dc:relation","label":"Dc Relation","values":["info:eu-repo/semantics/altIdentifier/urn/urn:nbn:de:hbz:82-opus-3623"]},{"key":"dc:type","label":"Dc Type","values":["info:eu-repo/semantics/doctoralThesis","info:eu-repo/semantics/publishedVersion"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["info:eu-repo/classification/ddc/610","Medizin"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["ger"]},{"key":"dc:rights","label":"Dc Rights","values":["info:eu-repo/semantics/openAccess"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://publications.rwth-aachen.de/record/56989","https://publications.rwth-aachen.de/search?p=id:%22RWTH-CONV-119061%22"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The content of this work was the reconstruction of neuronal activity in a standardized headmodel under consideration of additional constraints on the time course of the solution. The thesis is divided into five chapters which describe the physiological basis of the neuronal generators of the electromagnetic fields and potentials, the finite element solution of the bioelectromagnetic forward solution, the solution of the inverse problem, the validation of the proposed algorithms and solutions and the implementation of a eeg-data analysis software package. The aim of the work was the extension and improvement of the existing sourcemodels by introducing an additional temporal modelterm and the simplification of the forward solution of realistic model by using a standardized head. The fMRI phantom created by Collins et al. was chosen as a generic model of the head. Based on voxel intensities of this MR image a cubic FE mesh with 2.5 mm sidelength was created. On the surface of this model, a larger number of equally spaced electrode positions was created and the a solution for all sensors was calculated for sourcelocations on a regular grid within the cortex. In order to verify the model, sources in individual head models were simulated and then reconstructed with the aid of the standard model. The localization error of the reconstructed sources was found to be less than one gridlength of the cortical reconstruction grid. In order to expand the source model such that a priori knowledge about the timecourse of the sources could be incorporated, a bayesian approach to inverse problem was used. Two basic temporal constraints were introduced, smoothness of first order and smoothness of second order and the properties of the temporal constrained source reconstruction were compared to spatial constrained reconstruction methods (e.g. minimum, LORETA). Two measures were used, the localization error of the sources and the correlation coefficient between the original and the reconstructed timecourses of the sources.Additonal physiological boundary conditions for the temporal constraints were introduced and a modified numerical efficient algorithm for the solution of the temporal constrained problem was proposed. The localization error and the correlation were analyzed for simulations on a planar model and also on a realistically shaped headmodel. Under assumption of biological noise, the temporal constrained methods yielded improved reconstruction results. The methods were also tested on experimental data. Three stimulation setups were used, i.e an acoustic, a visual and somatosensoric stimulus were presented and source reconstruction was done using spatially constrained and temporal constrained methods. 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