Electromagnetic Brain Imaging : A Bayesian Perspective / by Kensuke Sekihara, Srikantan S. Nagarajan.

Format:

Book

Author/Creator:

Sekihara, Kensuke, author.

Nagarajan, Srikatan S., author.

Contributor:

SpringerLink (Online service)

Series:

Biomedical and Life Sciences (Springer-11642)

Language:

English

Subjects (All):

Neurosciences.

Biomedical engineering.

Neurobiology.

Biomedical Engineering and Bioengineering.

Local Subjects:

Neurosciences.

Biomedical Engineering and Bioengineering.

Neurobiology.

Physical Description:

1 online resource (XIV, 270 pages) : 32 illustrations, 27 illustrations in color

Edition:

First edition 2015.

Contained In:

Springer eBooks

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2015.

System Details:

text file PDF

Summary:

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.

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.

Other Format:

Printed edition:

ISBN:

978-3-319-14947-9

9783319149479

Access Restriction:

Restricted for use by site license.