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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Bibliographic Details
Main Authors: Sekihara, Kensuke (Author), Nagarajan, Srikantan S. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2015.
Subjects:
Online Access:Full Text via HEAL-Link
Table of Contents:
  • 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.