Electromagnetic Brain Imaging A Bayesian Perspective /

This graduate level textbook provides a coherent introduction to the body of main-stream algorithms used in electromagnetic brain imaging, with specific emphasis on novel Bayesian algorithms.  It helps readers to more easily understand literature in biomedical engineering and related fields, and be...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Sekihara, Kensuke (Autor), Nagarajan, Srikantan S. (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2015.
Edición:1st ed. 2015.
Temas:
Neurosciences.
Biomedical engineering.
Neuroscience.
Biomedical Engineering and Bioengineering.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Introduction to Electromagnetic Brain Imaging
  • Minimum-Norm-Based Source Imaging Algorithms
  • Adaptive Beamformers
  • Sparse Bayesian (Champagne) Algorithm
  • Bayesian Factor Analysis: A Versatile Framework
  • A Unified Bayesian Framework for MEG/EEG Source
  • Source-Space Connectivity Analysis Using Imaginary
  • Estimation of Causal Networks: Source-Space Causality Analysis
  • Detection of Phase-Amplitude Coupling in MEG Source Space: An Empirical Study.

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