Influence of atlas-based and patient dependent forward models in EEG source reconstruction
Abstract: Electroencephalography Source Imaging (ESI) techniques have become the most attractive alternative to support the estimation of neuronal activity through the mapping of electrical potentials measured over the scalp. It takes advantage of the low implementation cost, the high temporal resol...
- Autores:
-
Céspedes Villar, Yohan Ricardo
- Tipo de recurso:
- Fecha de publicación:
- 2017
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/62118
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/62118
http://bdigital.unal.edu.co/61026/
- Palabra clave:
- 61 Ciencias médicas; Medicina / Medicine and health
62 Ingeniería y operaciones afines / Engineering
EEG
Modelo directo
ESI
BMS
Electrónica médica
Electroencefalografía
EEG
Forward model
ESI
BMS
Electroencephalography
Medical electronics
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
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Universidad Nacional de Colombia |
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|
dc.title.spa.fl_str_mv |
Influence of atlas-based and patient dependent forward models in EEG source reconstruction |
title |
Influence of atlas-based and patient dependent forward models in EEG source reconstruction |
spellingShingle |
Influence of atlas-based and patient dependent forward models in EEG source reconstruction 61 Ciencias médicas; Medicina / Medicine and health 62 Ingeniería y operaciones afines / Engineering EEG Modelo directo ESI BMS Electrónica médica Electroencefalografía EEG Forward model ESI BMS Electroencephalography Medical electronics |
title_short |
Influence of atlas-based and patient dependent forward models in EEG source reconstruction |
title_full |
Influence of atlas-based and patient dependent forward models in EEG source reconstruction |
title_fullStr |
Influence of atlas-based and patient dependent forward models in EEG source reconstruction |
title_full_unstemmed |
Influence of atlas-based and patient dependent forward models in EEG source reconstruction |
title_sort |
Influence of atlas-based and patient dependent forward models in EEG source reconstruction |
dc.creator.fl_str_mv |
Céspedes Villar, Yohan Ricardo |
dc.contributor.advisor.spa.fl_str_mv |
Castellanos Domínguez, Cesar Germán (Thesis advisor) |
dc.contributor.author.spa.fl_str_mv |
Céspedes Villar, Yohan Ricardo |
dc.subject.ddc.spa.fl_str_mv |
61 Ciencias médicas; Medicina / Medicine and health 62 Ingeniería y operaciones afines / Engineering |
topic |
61 Ciencias médicas; Medicina / Medicine and health 62 Ingeniería y operaciones afines / Engineering EEG Modelo directo ESI BMS Electrónica médica Electroencefalografía EEG Forward model ESI BMS Electroencephalography Medical electronics |
dc.subject.proposal.spa.fl_str_mv |
EEG Modelo directo ESI BMS Electrónica médica Electroencefalografía EEG Forward model ESI BMS Electroencephalography Medical electronics |
description |
Abstract: Electroencephalography Source Imaging (ESI) techniques have become the most attractive alternative to support the estimation of neuronal activity through the mapping of electrical potentials measured over the scalp. It takes advantage of the low implementation cost, the high temporal resolution, and non-invasiveness in the patient. ESI techniques require a volumetric conductor model (commonly named Electroencephalography (EEG) Forward Model), including information about the physiological and geometrical properties of the head, and modeling the electromagnetic field propagation of the neuronal activity throughout the head tissues to reach the scalp. In this regard, the accuracy of ESI solutions depends partially on the capabilities of the forward model to correctly describe the structural information provided by a Magnetic Resonance Image (MRI). However, acquiring MRIs for generating personalized head models is expensive, slow, and in some cases unpractical. In this work, we investigate how the head model influences the source reconstruction based on EEG when progressively including different levels of prior structural information. Hence, we evaluate two approaches to enhance the model of brain structure in the EEG forward problem formulation. First, the incorporation of different brain tissue morphology, mainly, based on a Generic MRI, based on a target population Atlas, or based on a patient-specific MRI. Second, the variation of the tissue model complexity in the number of segmented brain layers. All the head models are build using the Finite Difference Reciprocity Method (FDRM). Model comparison is carried out under a Parametric Empirical Bayesian (PEB) framework using Event-Related Potentials (ERPs) taken from the studied population. Obtained results show that the more realistic and subject dependent model, the better performance of the ESI solution |
publishDate |
2017 |
dc.date.issued.spa.fl_str_mv |
2017 |
dc.date.accessioned.spa.fl_str_mv |
2019-07-02T20:51:29Z |
dc.date.available.spa.fl_str_mv |
2019-07-02T20:51:29Z |
dc.type.spa.fl_str_mv |
Trabajo de grado - Maestría |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/masterThesis |
dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
dc.type.content.spa.fl_str_mv |
Text |
dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/TM |
status_str |
acceptedVersion |
dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/62118 |
dc.identifier.eprints.spa.fl_str_mv |
http://bdigital.unal.edu.co/61026/ |
url |
https://repositorio.unal.edu.co/handle/unal/62118 http://bdigital.unal.edu.co/61026/ |
dc.language.iso.spa.fl_str_mv |
spa |
language |
spa |
dc.relation.ispartof.spa.fl_str_mv |
Universidad Nacional de Colombia Sede Manizales Facultad de Ingeniería y Arquitectura Departamento de Ingeniería Eléctrica, Electrónica y Computación Departamento de Ingeniería Eléctrica, Electrónica y Computación |
dc.relation.references.spa.fl_str_mv |
Céspedes Villar, Yohan Ricardo (2017) Influence of atlas-based and patient dependent forward models in EEG source reconstruction. Maestría thesis, Universidad Nacional de Colombia - Sede Manizales. |
dc.rights.spa.fl_str_mv |
Derechos reservados - Universidad Nacional de Colombia |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.license.spa.fl_str_mv |
Atribución-NoComercial 4.0 Internacional |
dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/licenses/by-nc/4.0/ |
dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Atribución-NoComercial 4.0 Internacional Derechos reservados - Universidad Nacional de Colombia http://creativecommons.org/licenses/by-nc/4.0/ http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
dc.format.mimetype.spa.fl_str_mv |
application/pdf |
institution |
Universidad Nacional de Colombia |
bitstream.url.fl_str_mv |
https://repositorio.unal.edu.co/bitstream/unal/62118/1/1053829689.2017.pdf https://repositorio.unal.edu.co/bitstream/unal/62118/2/1053829689.2017.pdf.jpg |
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MD5 MD5 |
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Repositorio Institucional Universidad Nacional de Colombia |
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repositorio_nal@unal.edu.co |
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1814089985599471616 |
spelling |
Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Castellanos Domínguez, Cesar Germán (Thesis advisor)55b90292-4739-4ae2-afba-e0ecc1255dff-1Céspedes Villar, Yohan Ricardo82c1a6a0-c86f-4279-a116-20a131ff87753002019-07-02T20:51:29Z2019-07-02T20:51:29Z2017https://repositorio.unal.edu.co/handle/unal/62118http://bdigital.unal.edu.co/61026/Abstract: Electroencephalography Source Imaging (ESI) techniques have become the most attractive alternative to support the estimation of neuronal activity through the mapping of electrical potentials measured over the scalp. It takes advantage of the low implementation cost, the high temporal resolution, and non-invasiveness in the patient. ESI techniques require a volumetric conductor model (commonly named Electroencephalography (EEG) Forward Model), including information about the physiological and geometrical properties of the head, and modeling the electromagnetic field propagation of the neuronal activity throughout the head tissues to reach the scalp. In this regard, the accuracy of ESI solutions depends partially on the capabilities of the forward model to correctly describe the structural information provided by a Magnetic Resonance Image (MRI). However, acquiring MRIs for generating personalized head models is expensive, slow, and in some cases unpractical. In this work, we investigate how the head model influences the source reconstruction based on EEG when progressively including different levels of prior structural information. Hence, we evaluate two approaches to enhance the model of brain structure in the EEG forward problem formulation. First, the incorporation of different brain tissue morphology, mainly, based on a Generic MRI, based on a target population Atlas, or based on a patient-specific MRI. Second, the variation of the tissue model complexity in the number of segmented brain layers. All the head models are build using the Finite Difference Reciprocity Method (FDRM). Model comparison is carried out under a Parametric Empirical Bayesian (PEB) framework using Event-Related Potentials (ERPs) taken from the studied population. Obtained results show that the more realistic and subject dependent model, the better performance of the ESI solutionResumen: Las técnicas de reconstrucción de fuentes basadas en Electroencefalografía (ESI) son la alternativa más interesante para la estimación de fuentes mediante los potenciales eléctricos medidos sobre el cuero cabelludo, aprovechando el bajo costo de implementación, la alta resolución temporal, y la poca invasión que requiere en el paciente. Es por esto, que estas técnicas requieren un modelo de conducción volumétrico (comúnmente llamado modelo directo), que incluye información de las propiedades físicas y geométricas de la cabeza, además de modelar la propagación del campo electromagnético generado por la actividad neuronal a través de los diferentes tejidos de la cabeza hasta alcanzar el cuero cabelludo. En este sentido, el correcto desempeño de las técnicas ESI depende directamente de las capacidades del modelo directo para describir de manera apropiada la información estructural aportada por una Imagen por Resonancia Magnética (MRI). Sin embargo, adquirir MRIs para generar modelos de la cabeza personalizados, es costoso, lento, y en algunos casos poco práctico. En este trabajo, se investiga la manera en que el modelo directo influencia la tarea de reconstrucción de fuentes basada en EEG, incluyendo de manera progresiva diferentes niveles de información estructural relacionada al paciente. Así, se evaluan dos enfoques específicos para mejorar el modelo de la estructura cerebral en la formulación del problema directo de EEG. El primer enfoque está relacionado con la incorporación de diferentes morfologías de tejido cerebral, principalmente, basadas en un MRI genérico, un atlas de la población estudiada, ó en el MRI específico del paciente. El segundo enfoque es la variación de la complejidad del modelo en términos de el número de tejidos segmentados en el cerebro. En este trabajo el modelo directo se soluciona usando el Método de Diferencias Finitas con Reciprocidad (FDRM). La comparación de modelos se realiza bajo un framework Bayesiano Empírico Paramétrico (PEB), que permite contrastar los diferentes enfoques del modelo directo, usando datos reales. En general, los resultados obtenidos muestran que usar modelos más realistas y más dependientes de la población de estudio, mejora significativamente el desempeño de las técnicas ESIMaestríaapplication/pdfspaUniversidad Nacional de Colombia Sede Manizales Facultad de Ingeniería y Arquitectura Departamento de Ingeniería Eléctrica, Electrónica y ComputaciónDepartamento de Ingeniería Eléctrica, Electrónica y ComputaciónCéspedes Villar, Yohan Ricardo (2017) Influence of atlas-based and patient dependent forward models in EEG source reconstruction. Maestría thesis, Universidad Nacional de Colombia - Sede Manizales.61 Ciencias médicas; Medicina / Medicine and health62 Ingeniería y operaciones afines / EngineeringEEGModelo directoESIBMSElectrónica médicaElectroencefalografíaEEGForward modelESIBMSElectroencephalographyMedical electronicsInfluence of atlas-based and patient dependent forward models in EEG source reconstructionTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMORIGINAL1053829689.2017.pdfapplication/pdf12195869https://repositorio.unal.edu.co/bitstream/unal/62118/1/1053829689.2017.pdf5b876ca7ecf46e2554b5aaf99943ddf2MD51THUMBNAIL1053829689.2017.pdf.jpg1053829689.2017.pdf.jpgGenerated Thumbnailimage/jpeg5938https://repositorio.unal.edu.co/bitstream/unal/62118/2/1053829689.2017.pdf.jpgac5c2fe3f80bc9e1cb949266c057994cMD52unal/62118oai:repositorio.unal.edu.co:unal/621182024-04-22 23:21:30.826Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co |