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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| Format: | Electronic eBook |
| Language: | English |
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Springer International Publishing : Imprint: Springer,
2015.
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| 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.