Electromagnetic Brain Imaging A Bayesian Perspective /

• Κύριοι συγγραφείς: Sekihara, Kensuke (Συγγραφέας), Nagarajan, Srikantan S. (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2015.
• Θέματα: Medicine.; Neurosciences.; Neurobiology.; Biomedical engineering.; Biomedicine.; Biomedical Engineering.

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...

Πίνακας περιεχομένων:

• 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.