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A two-step super-Gaussian independent component analysis approach for fMRI data.
Ge, Ruiyang; Yao, Li; Zhang, Hang; Long, Zhiying.
Afiliación
  • Ge R; State Key Laboratory of Cognitive Neuroscience and Learning& IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China; Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, 100875, China; College of Informa
  • Yao L; State Key Laboratory of Cognitive Neuroscience and Learning& IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China; Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, 100875, China; College of Informa
  • Zhang H; Paul C. Lauterbur Research Centers for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
  • Long Z; State Key Laboratory of Cognitive Neuroscience and Learning& IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China; Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, 100875, China. Electronic address
Neuroimage ; 118: 344-58, 2015 Sep.
Article en En | MEDLINE | ID: mdl-26057592
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Procesamiento de Señales Asistido por Computador / Encéfalo / Mapeo Encefálico / Imagen por Resonancia Magnética Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Año: 2015 Tipo del documento: Article
Texto completo
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Procesamiento de Señales Asistido por Computador / Encéfalo / Mapeo Encefálico / Imagen por Resonancia Magnética Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Año: 2015 Tipo del documento: Article