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Campo DC | Valor | Lengua/Idioma |
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dc.contributor.author | Areces-Gonzalez, A | - |
dc.contributor.author | Paz-Linares, D | - |
dc.contributor.author | Lepage, C | - |
dc.contributor.author | Lewis, L | - |
dc.contributor.author | Toussaint, P.J | - |
dc.contributor.author | Bosch-Bayard, J | - |
dc.contributor.author | Valdés- Sosa, .PA | - |
dc.coverage.spatial | 1001206 | en_US |
dc.date.accessioned | 2021-11-10T15:44:48Z | - |
dc.date.available | 2021-11-10T15:44:48Z | - |
dc.date.issued | 2021-10 | - |
dc.identifier.uri | https://repositorio.uci.cu/jspui/handle/123456789/9714 | - |
dc.description.abstract | Structural and functional features, and their integration at the different levels of brain organization, are the key to explain all brain states observed in normal or abnormal conditions. Invivo imaging modalities such as functional MRI (fMRI), MEG and EEG capture functional features of neural populations at level that can be situated in structural MRI (sMRI) tissue-contrasts. However, function emerges locally due to the cortex columnar organization of cellular layers and axonal fibers, at a level only accessible through high resolution structural imaging, such as histology. Invivo multimodal-imaging adopting surface-based processing pipelines, which acknowledge such cortical organization, has been proposed by the Human Connectome Project (HCP) to improve the accuracy in determining the cortical multimodal features. We introduce a pipeline that bridges the gap between levels through sMRI HCP compatible processing of BigBrain high resolution histology, which is integrated with MEG and EEG source processing. This is denominated BigBrain-HCP-MEEG, which maps simultaneously onto BigBrain, and HCP native and FSAverage structural spaces the MEG and EEG electrophysiological source spectral topographies and topologies. This can be done following two paths: 1) BigBrain-ICBM152 HCP compatible source model and lead field template . | en_US |
dc.language.iso | spa | en_US |
dc.publisher | Ediciones Futuro | en_US |
dc.subject | MULTIMODAL IMAGING | en_US |
dc.subject | HUMAN CONNECTOME PROJECT | en_US |
dc.subject | ELCTROPHYSIOLOGICAL SOURCE IMAGING | en_US |
dc.subject | BIG BRAIN | en_US |
dc.title | Registro de imágenes de fuentes electrofisiológicas con BigBrain utilizando herramientas compatibles con el HCP | en_US |
dc.title.alternative | Registration of electrophysiological source imaging with the BigBrain using the HCP compatible pipelines | en_US |
dc.type | conferenceObject | en_US |
dc.rights.holder | Universidad de las Ciencias Informáticas | en_US |
dc.source.title | UCIENCIA 2021 | en_US |
dc.source.conferencetitle | IV Taller internacional de Matemática Computacional y Bioinformática | en_US |
Aparece en las colecciones: | UCIENCIA 2021 |
Ficheros en este ítem:
Fichero | Tamaño | Formato | |
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UCIENCIA_2021_paper_260.pdf | 1.13 MB | Adobe PDF | Visualizar/Abrir |
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