Adaptive Spatial Filters for Electromagn
β Kensuke Sekihara, Srikatan S. Nagarajan
π Library
π
2008
π Springer
π English
β¦ LIBER β¦
π
Electromagnetic Brain Imaging: A Bayesian Perspective
β Scribed by Kensuke Sekihara, Srikantan S. Nagarajan (auth.)
- Publisher
- Springer International Publishing
- Year
- 2015
- Tongue
- English
- Leaves
- 277
- Edition
- 1
- Category
- Library
β¬ Acquire This Volume
No coin nor oath required. For personal study only.
β¦ Synopsis
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 ready to pursue research in either the engineering or the neuroscientific aspects of electromagnetic brain imaging. This textbook will not only appeal to graduate students but all scientists and engineers engaged in research on electromagnetic brain imaging.
β¦ Table of Contents
Front Matter....Pages i-xiv
Introduction to Electromagnetic Brain Imaging....Pages 1-8
Minimum-Norm-Based Source Imaging Algorithms....Pages 9-28
Adaptive Beamformers....Pages 29-50
Sparse Bayesian (Champagne) Algorithm....Pages 51-74
Bayesian Factor Analysis: A Versatile Framework for Denoising, Interference Suppression, and Source Localization....Pages 75-117
A Unified Bayesian Framework for MEG/EEG Source Imaging....Pages 119-137
Source-Space Connectivity Analysis Using Imaginary Coherence....Pages 139-169
Estimation of Causal Networks: Source-Space Causality Analysis....Pages 171-198
Detection of PhaseβAmplitude Coupling in MEG Source Space: An Empirical Study....Pages 199-213
Back Matter....Pages 215-270
β¦ Subjects
Neurosciences; Biomedical Engineering; Neurobiology
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