Reconstructing anatomy from electro-physiological data
ABSTRACT: Here we show how it is possible to make estimates of brain structure based on MEG data. We do this by reconstructing functional estimates onto distorted cortical manifolds parameterised in terms of their spherical harmonics. We demonstrate that both empirical and simulated MEG data give ri...
- Autores:
-
López Hincapié, José David
Valencia, Felipe
Flandin, Guillaume
Penny, Will D.
Barnes, Gareth Robert
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2017
- Institución:
- Universidad de Antioquia
- Repositorio:
- Repositorio UdeA
- Idioma:
- eng
- OAI Identifier:
- oai:bibliotecadigital.udea.edu.co:10495/41654
- Acceso en línea:
- https://hdl.handle.net/10495/41654
- Palabra clave:
- Encéfalo - diagnóstico por imagen
Brain - diagnostic imaging
Algoritmos
Algorithms
Simulación por Computador
Computer Simulation
Interpretación de Imagen Asistida por Computador
Image Interpretation, Computer-Assisted
Magnetoencefalografía
Magnetoencephalography
Modelos Neurológicos
Models, Neurological
https://id.nlm.nih.gov/mesh/D001921
https://id.nlm.nih.gov/mesh/D000465
https://id.nlm.nih.gov/mesh/D003198
https://id.nlm.nih.gov/mesh/D007090
https://id.nlm.nih.gov/mesh/D015225
https://id.nlm.nih.gov/mesh/D008959
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by/2.5/co/
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| dc.title.spa.fl_str_mv |
Reconstructing anatomy from electro-physiological data |
| title |
Reconstructing anatomy from electro-physiological data |
| spellingShingle |
Reconstructing anatomy from electro-physiological data Encéfalo - diagnóstico por imagen Brain - diagnostic imaging Algoritmos Algorithms Simulación por Computador Computer Simulation Interpretación de Imagen Asistida por Computador Image Interpretation, Computer-Assisted Magnetoencefalografía Magnetoencephalography Modelos Neurológicos Models, Neurological https://id.nlm.nih.gov/mesh/D001921 https://id.nlm.nih.gov/mesh/D000465 https://id.nlm.nih.gov/mesh/D003198 https://id.nlm.nih.gov/mesh/D007090 https://id.nlm.nih.gov/mesh/D015225 https://id.nlm.nih.gov/mesh/D008959 |
| title_short |
Reconstructing anatomy from electro-physiological data |
| title_full |
Reconstructing anatomy from electro-physiological data |
| title_fullStr |
Reconstructing anatomy from electro-physiological data |
| title_full_unstemmed |
Reconstructing anatomy from electro-physiological data |
| title_sort |
Reconstructing anatomy from electro-physiological data |
| dc.creator.fl_str_mv |
López Hincapié, José David Valencia, Felipe Flandin, Guillaume Penny, Will D. Barnes, Gareth Robert |
| dc.contributor.author.none.fl_str_mv |
López Hincapié, José David Valencia, Felipe Flandin, Guillaume Penny, Will D. Barnes, Gareth Robert |
| dc.contributor.researchgroup.spa.fl_str_mv |
Sistemas Embebidos e Inteligencia Computacional (SISTEMIC) |
| dc.subject.decs.none.fl_str_mv |
Encéfalo - diagnóstico por imagen Brain - diagnostic imaging Algoritmos Algorithms Simulación por Computador Computer Simulation Interpretación de Imagen Asistida por Computador Image Interpretation, Computer-Assisted Magnetoencefalografía Magnetoencephalography Modelos Neurológicos Models, Neurological |
| topic |
Encéfalo - diagnóstico por imagen Brain - diagnostic imaging Algoritmos Algorithms Simulación por Computador Computer Simulation Interpretación de Imagen Asistida por Computador Image Interpretation, Computer-Assisted Magnetoencefalografía Magnetoencephalography Modelos Neurológicos Models, Neurological https://id.nlm.nih.gov/mesh/D001921 https://id.nlm.nih.gov/mesh/D000465 https://id.nlm.nih.gov/mesh/D003198 https://id.nlm.nih.gov/mesh/D007090 https://id.nlm.nih.gov/mesh/D015225 https://id.nlm.nih.gov/mesh/D008959 |
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https://id.nlm.nih.gov/mesh/D001921 https://id.nlm.nih.gov/mesh/D000465 https://id.nlm.nih.gov/mesh/D003198 https://id.nlm.nih.gov/mesh/D007090 https://id.nlm.nih.gov/mesh/D015225 https://id.nlm.nih.gov/mesh/D008959 |
| description |
ABSTRACT: Here we show how it is possible to make estimates of brain structure based on MEG data. We do this by reconstructing functional estimates onto distorted cortical manifolds parameterised in terms of their spherical harmonics. We demonstrate that both empirical and simulated MEG data give rise to consistent and plausible anatomical estimates. Importantly, the estimation of structure from MEG data can be quantified in terms of millimetres from the true brain structure. We show, for simulated data, that the functional assumptions which are closer to the functional ground-truth give rise to anatomical estimates that are closer to the true anatomy. |
| publishDate |
2017 |
| dc.date.issued.none.fl_str_mv |
2017 |
| dc.date.accessioned.none.fl_str_mv |
2024-08-31T12:28:02Z |
| dc.date.available.none.fl_str_mv |
2024-08-31T12:28:02Z |
| dc.type.spa.fl_str_mv |
Artículo de investigación |
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J.D. López, F. Valencia, G. Flandin, W. Penny, G.R. Barnes, Reconstructing anatomy from electro-physiological data, NeuroImage, Volume 163, 2017, Pages 480-486, ISSN 1053-8119, https://doi.org/10.1016/j.neuroimage.2017.06.049 (https://www.sciencedirect.com/science/article/pii/S1053811917305207) |
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1053-8119 |
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https://hdl.handle.net/10495/41654 |
| dc.identifier.doi.none.fl_str_mv |
10.1016/j.neuroimage.2017.06.049 |
| dc.identifier.eissn.none.fl_str_mv |
1095-9572 |
| identifier_str_mv |
J.D. López, F. Valencia, G. Flandin, W. Penny, G.R. Barnes, Reconstructing anatomy from electro-physiological data, NeuroImage, Volume 163, 2017, Pages 480-486, ISSN 1053-8119, https://doi.org/10.1016/j.neuroimage.2017.06.049 (https://www.sciencedirect.com/science/article/pii/S1053811917305207) 1053-8119 10.1016/j.neuroimage.2017.06.049 1095-9572 |
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https://hdl.handle.net/10495/41654 |
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eng |
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eng |
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Neuroimage |
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486 |
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480 |
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163 |
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NeuroImage |
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7 páginas |
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application/pdf |
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Elsevier |
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Orlando, Estados Unidos |
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López Hincapié, José DavidValencia, FelipeFlandin, GuillaumePenny, Will D.Barnes, Gareth RobertSistemas Embebidos e Inteligencia Computacional (SISTEMIC)2024-08-31T12:28:02Z2024-08-31T12:28:02Z2017J.D. López, F. Valencia, G. Flandin, W. Penny, G.R. Barnes, Reconstructing anatomy from electro-physiological data, NeuroImage, Volume 163, 2017, Pages 480-486, ISSN 1053-8119, https://doi.org/10.1016/j.neuroimage.2017.06.049 (https://www.sciencedirect.com/science/article/pii/S1053811917305207)1053-8119https://hdl.handle.net/10495/4165410.1016/j.neuroimage.2017.06.0491095-9572ABSTRACT: Here we show how it is possible to make estimates of brain structure based on MEG data. We do this by reconstructing functional estimates onto distorted cortical manifolds parameterised in terms of their spherical harmonics. We demonstrate that both empirical and simulated MEG data give rise to consistent and plausible anatomical estimates. Importantly, the estimation of structure from MEG data can be quantified in terms of millimetres from the true brain structure. We show, for simulated data, that the functional assumptions which are closer to the functional ground-truth give rise to anatomical estimates that are closer to the true anatomy.COL00107177 páginasapplication/pdfengElsevierOrlando, Estados Unidoshttp://creativecommons.org/licenses/by/2.5/co/https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Reconstructing anatomy from electro-physiological dataArtículo de investigaciónhttp://purl.org/coar/resource_type/c_2df8fbb1https://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionEncéfalo - diagnóstico por imagenBrain - diagnostic imagingAlgoritmosAlgorithmsSimulación por ComputadorComputer SimulationInterpretación de Imagen Asistida por ComputadorImage Interpretation, Computer-AssistedMagnetoencefalografíaMagnetoencephalographyModelos NeurológicosModels, Neurologicalhttps://id.nlm.nih.gov/mesh/D001921https://id.nlm.nih.gov/mesh/D000465https://id.nlm.nih.gov/mesh/D003198https://id.nlm.nih.gov/mesh/D007090https://id.nlm.nih.gov/mesh/D015225https://id.nlm.nih.gov/mesh/D008959Neuroimage486480163NeuroImagePublicationCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; 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