國立高雄大學圖資館 |

Language: English

Back

EEG/MEG source reconstructiontextbook for electro-and magnetoencephalography /

Record Type:	Electronic resources : Monograph/item
Title/Author:	EEG/MEG source reconstructionby Thomas R. Knosche, Jens Haueisen.
Reminder of title:	textbook for electro-and magnetoencephalography /
Author:	Knosche, Thomas R.
other author:	Haueisen, Jens.
Published:	Cham :Springer International Publishing :2022.
Description:	xix, 415 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Electroencephalography.
Online resource:	https://doi.org/10.1007/978-3-030-74918-7
ISBN:	9783030749187$q(electronic bk.)

EEG/MEG source reconstructiontextbook for electro-and magnetoencephalography /
Knosche, Thomas R.

EEG/MEG source reconstructiontextbook for electro-and magnetoencephalography /[electronic resource] :by Thomas R. Knosche, Jens Haueisen. - Cham :Springer International Publishing :2022. - xix, 415 p. :ill., digital ;24 cm.

Chapter 1: Introduction -- Chapter 2: Neural Tissue and its Signals -- Chapter 3: Measurements -- Chapter 4: Source Models -- Chapter 5: Forward Models -- Chapter 6: Inverse Methods -- Chapter 7: Assessment -- Chapter 8: Applications.

This textbook provides a comprehensive and didactic introduction from the basics to the current state of the art in the field of EEG/MEG source reconstruction. Reconstructing the generators or sources of electroencephalographic and magnetoencephalographic (EEG/MEG) signals is an important problem in basic neuroscience as well as clinical research and practice. Over the past few decades, an entire theory, together with a whole collection of algorithms and techniques, has developed. In this textbook, the authors provide a unified perspective on a broad range of EEG/MEG source reconstruction methods, with particular emphasis on their respective assumptions about sources, data, head tissues, and sensor properties. An introductory chapter highlights the concept of brain imaging and the particular importance of the neuroelectromagnetic inverse problem. This is followed by an in-depth discussion of neural information processing and brain signal generation and an introduction to the practice of data acquisition. Next, the relevant mathematical models for the sources of EEG and MEG are discussed in detail, followed by the neuroelectromagnetic forward problem, that is, the prediction of EEG or MEG signals from those source models, using biophysical descriptions of the head tissues and the sensors. The main part of this textbook is dedicated to the source reconstruction methods. The authors present a theoretical framework of the neuroelectromagnetic inverse problem, centered on Bayes' theorem, which then serves as the basis for a detailed description of a large variety of techniques, including dipole fit methods, distributed source reconstruction, spatial filters, and dynamic source reconstruction methods. The final two chapters address the important topic of assessment, including verification and validation of source reconstruction methods, and their actual application to real-world scientific and clinical questions. This book is intended as basic reading for anybody who is engaged with EEG/MEG source reconstruction, be it as a method developer or as a user, including advanced undergraduate students, PhD students, and postdocs in neuroscience, biomedical engineering, and related fields.

ISBN: 9783030749187$q(electronic bk.)

Standard No.: 10.1007/978-3-030-74918-7doiSubjects--Topical Terms:

194456
Electroencephalography.

LC Class. No.: RC386.6.E43 / K5 2022

Dewey Class. No.: 616.8047547

EEG/MEG source reconstructiontextbook for electro-and magnetoencephalography /
LDR:03489nmm a2200325 a 4500 001 630190
003 DE-He213
005 20221001012053.0
006 m d
007 cr nn 008maaau
008 230329s2022 sz s 0 eng d
020 $a 9783030749187$q(electronic bk.)
020 $a 9783030749163$q(paper)
024 7 $a 10.1007/978-3-030-74918-7 $2 doi
035 $a 978-3-030-74918-7
040 $a GP $c GP
041 0 $a eng
050 4 $a RC386.6.E43 $b K5 2022
072 7 $a PSAN $2 bicssc
072 7 $a MED057000 $2 bisacsh
072 7 $a PSAN $2 thema
082 0 4 $a 616.8047547 $2 23
090 $a RC386.6.E43 $b K72 2022
100 1 $a Knosche, Thomas R. $3 935306
245 1 0 $a EEG/MEG source reconstruction $h [electronic resource] : $b textbook for electro-and magnetoencephalography / $c by Thomas R. Knosche, Jens Haueisen.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a xix, 415 p. : $b ill., digital ; $c 24 cm.
505 0 $a Chapter 1: Introduction -- Chapter 2: Neural Tissue and its Signals -- Chapter 3: Measurements -- Chapter 4: Source Models -- Chapter 5: Forward Models -- Chapter 6: Inverse Methods -- Chapter 7: Assessment -- Chapter 8: Applications.
520 $a This textbook provides a comprehensive and didactic introduction from the basics to the current state of the art in the field of EEG/MEG source reconstruction. Reconstructing the generators or sources of electroencephalographic and magnetoencephalographic (EEG/MEG) signals is an important problem in basic neuroscience as well as clinical research and practice. Over the past few decades, an entire theory, together with a whole collection of algorithms and techniques, has developed. In this textbook, the authors provide a unified perspective on a broad range of EEG/MEG source reconstruction methods, with particular emphasis on their respective assumptions about sources, data, head tissues, and sensor properties. An introductory chapter highlights the concept of brain imaging and the particular importance of the neuroelectromagnetic inverse problem. This is followed by an in-depth discussion of neural information processing and brain signal generation and an introduction to the practice of data acquisition. Next, the relevant mathematical models for the sources of EEG and MEG are discussed in detail, followed by the neuroelectromagnetic forward problem, that is, the prediction of EEG or MEG signals from those source models, using biophysical descriptions of the head tissues and the sensors. The main part of this textbook is dedicated to the source reconstruction methods. The authors present a theoretical framework of the neuroelectromagnetic inverse problem, centered on Bayes' theorem, which then serves as the basis for a detailed description of a large variety of techniques, including dipole fit methods, distributed source reconstruction, spatial filters, and dynamic source reconstruction methods. The final two chapters address the important topic of assessment, including verification and validation of source reconstruction methods, and their actual application to real-world scientific and clinical questions. This book is intended as basic reading for anybody who is engaged with EEG/MEG source reconstruction, be it as a method developer or as a user, including advanced undergraduate students, PhD students, and postdocs in neuroscience, biomedical engineering, and related fields.
650 0 $a Electroencephalography. $3 194456
650 0 $a Magnetoencephalography. $3 243690
650 1 4 $a Neuroscience. $3 297547
650 2 4 $a Biomedical Engineering and Bioengineering. $3 826326
650 2 4 $a Imaging Techniques. $3 921145
650 2 4 $a Biological Imaging. $3 933220
700 1 $a Haueisen, Jens. $3 935307
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-030-74918-7
950 $a Biomedical and Life Sciences (SpringerNature-11642)