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Sekihara, Kensuke.

Electromagnetic Brain Imaging : A Bayesian Perspective by Kensuke Sekihara, Srikantan S. Nagarajan. - Cham, Switzerland Springer 2015 - 1 recurso en línea (XIV, 270 p.) 32 ilustraciones, 27 ilustraciones en color

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 Phaseâ€litude Coupling in MEG Source Space: An Empirical Study.

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. Â 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. Âs textbook will not only appeal to graduate students but all scientists and engineers engaged in research on electromagnetic brain imaging.

ISBN: 9783319149479

Standard No.: 10.1007/978-3-319-14947-9 doi

Subjects--Topical Terms:
Neurobiología
Ingeniería biomédica
Neurobiología
Medicina
Neurociencias
Neurociencias

LC Class. No.: RC386.6.M36 / S455 2015

Dewey Class. No.: 612.8