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Brain Signals: Physics and Mathematics of MEG and EEG (Mit Press) [Hardcover]

InflatableMadness
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US $29.95
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Item specifics

Condition
Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
MPN
0262039826SRN
Brand
MIT Press
Style
ABIS_BOOK
Color
Black
ISBN
9780262039826

About this product

Product Identifiers

Publisher
MIT Press
ISBN-10
0262039826
ISBN-13
9780262039826
eBay Product ID (ePID)
3038287661

Product Key Features

Number of Pages
256 Pages
Language
English
Publication Name
Brain Signals : Physics and Mathematics of Meg and Eeg
Subject
Neurology, Neuroscience, Life Sciences / Neuroscience, Radiology, Radiotherapy & Nuclear Medicine
Publication Year
2019
Type
Textbook
Author
Risto J. Ilmoniemi, Jukka Sarvas
Subject Area
Science, Medical
Format
Hardcover

Dimensions

Item Height
0.7 in
Item Weight
24.9 Oz
Item Length
9.3 in
Item Width
7.3 in

Additional Product Features

Intended Audience
Trade
LCCN
2018-036973
Illustrated
Yes
Synopsis
A unified treatment of the generation and analysis of brain-generated electromagnetic fields. In Brain Signals , Risto Ilmoniemi and Jukka Sarvas present the basic physical and mathematical principles of magnetoencephalography (MEG) and electroencephalography (EEG), describing what kind of information is available in the neuroelectromagnetic field and how the measured MEG and EEG signals can be analyzed. Unlike most previous works on these topics, which have been collections of writings by different authors using different conventions, this book presents the material in a unified manner, providing the reader with a thorough understanding of basic principles and a firm basis for analyzing data generated by MEG and EEG.The book first provides a brief introduction to brain states and the early history of EEG and MEG, describes the generation of electromagnetic fields by neuronal activity, and discusses the electromagnetic forward problem. The authors then turn to EEG and MEG analysis, offering a review of linear and matrix algebra and basic statistics needed for analysis of the data, and presenting several analysis methods: dipole fitting; the minimum norm estimate (MNE); beamforming; the multiple signal classification algorithm (MUSIC), including RAP-MUSIC with the RAP dilemma and TRAP-MUSIC, which removes the RAP dilemma; independent component analysis (ICA); and blind source separation (BSS) with joint diagonalization., A unified treatment of the generation and analysis of brain-generated electromagnetic fields. In Brain Signals , Risto Ilmoniemi and Jukka Sarvas present the basic physical and mathematical principles of magnetoencephalography (MEG) and electroencephalography (EEG), describing what kind of information is available in the neuroelectromagnetic field and how the measured MEG and EEG signals can be analyzed. Unlike most previous works on these topics, which have been collections of writings by different authors using different conventions, this book presents the material in a unified manner, providing the reader with a thorough understanding of basic principles and a firm basis for analyzing data generated by MEG and EEG. The book first provides a brief introduction to brain states and the early history of EEG and MEG, describes the generation of electromagnetic fields by neuronal activity, and discusses the electromagnetic forward problem. The authors then turn to EEG and MEG analysis, offering a review of linear and matrix algebra and basic statistics needed for analysis of the data, and presenting several analysis methods: dipole fitting; the minimum norm estimate (MNE); beamforming; the multiple signal classification algorithm (MUSIC), including RAP-MUSIC with the RAP dilemma and TRAP-MUSIC, which removes the RAP dilemma; independent component analysis (ICA); and blind source separation (BSS) with joint diagonalization., A unified treatment of the generation and analysis of brain-generated electromagnetic fields. In Brain Signals , Risto Ilmoniemi and Jukka Sarvas present the basic physical and mathematical principles of magnetoencephalography (MEG) and electroencephalography (EEG), describing what kind of information is available in the neuroelectromagnetic field and how the measured MEG and EEG signals can be analyzed. Unlike most previous works on these topics, which have been collections of writings by different authors using different conventions, this book presents the material in a unified manner, providing the reader with a thorough understanding of basic principles and a firm basis for analyzing data generated by MEG and EEG. The book first provides a brief introduction to brain states and the early history of EEG and MEG, describes the generation of electromagnetic fields by neuronal activity, and discusses the electromagnetic forward problem. The authors then turn to EEG and MEG analysis, offering a review of linear and matrix algebra and basic statistics needed for analysis of the data, and presenting several analysis methods- dipole fitting; the minimum norm estimate (MNE); beamforming; the multiple signal classification algorithm (MUSIC), including RAP-MUSIC with the RAP dilemma and TRAP-MUSIC, which removes the RAP dilemma; independent component analysis (ICA); and blind source separation (BSS) with joint diagonalization.
LC Classification Number
RC386.6.M36I46 2019

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