Quantifying the performance of MEG source reconstruction using resting state data
ABSTRACT: In magnetoencephalography (MEG) research there are a variety of inversion methods to transform sensor data into estimates of brain activity. Each new inversion scheme is generally justified against a specific simulated or task scenario. The choice of this scenario will however have a large...
- Autores:
-
López Hincapié, José David
Little, Simon
Bonaiuto, James
S. Meyer, Sofie
Bestmann, Sven
Barnes, Gareth
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2018
- Institución:
- Universidad de Antioquia
- Repositorio:
- Repositorio UdeA
- Idioma:
- eng
- OAI Identifier:
- oai:bibliotecadigital.udea.edu.co:10495/41650
- Acceso en línea:
- https://hdl.handle.net/10495/41650
- Palabra clave:
- Diagnóstico por Imagen
Diagnostic Imaging
Magnetoencefalografía
Magnetoencephalography
Corteza Cerebral
Cerebral Cortex
Neuroimagen Funcional
Functional Neuroimaging
Procesamiento de Imagen Asistido por Computador
Image Processing, Computer-Assisted
Imagen por Resonancia Magnética
Magnetic Resonance Imaging
Modelos Anatómicos
Models, Anatomic
Modelos Teóricos
Models, Theoretical
Descanso
Rest
http://id.nlm.nih.gov/mesh/D003952
http://id.nlm.nih.gov/mesh/D015225
https://id.nlm.nih.gov/mesh/D002540
https://id.nlm.nih.gov/mesh/D059907
https://id.nlm.nih.gov/mesh/D007091
https://id.nlm.nih.gov/mesh/D008279
https://id.nlm.nih.gov/mesh/D008953
https://id.nlm.nih.gov/mesh/D008962
https://id.nlm.nih.gov/mesh/D012146
- Rights
- openAccess
- License
- https://creativecommons.org/licenses/by/4.0/
