語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
EEG/MEG Source Reconstruction = Textbook for Electro-and Magnetoencephalography /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
EEG/MEG Source Reconstruction/ by Thomas R. Knösche, Jens Haueisen.
其他題名:
Textbook for Electro-and Magnetoencephalography /
作者:
Knösche, Thomas R.
其他作者:
Haueisen, Jens.
面頁冊數:
XIX, 415 p. 174 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Biological Imaging. -
電子資源:
https://doi.org/10.1007/978-3-030-74918-7
ISBN:
9783030749187
EEG/MEG Source Reconstruction = Textbook for Electro-and Magnetoencephalography /
Knösche, Thomas R.
EEG/MEG Source Reconstruction
Textbook for Electro-and Magnetoencephalography /[electronic resource] :by Thomas R. Knösche, Jens Haueisen. - 1st ed. 2022. - XIX, 415 p. 174 illus. in color.online resource.
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
Standard No.: 10.1007/978-3-030-74918-7doiSubjects--Topical Terms:
1388121
Biological Imaging.
LC Class. No.: RC321-580
Dewey Class. No.: 612.8
EEG/MEG Source Reconstruction = Textbook for Electro-and Magnetoencephalography /
LDR
:03807nam a22003855i 4500
001
1083806
003
DE-He213
005
20221001012053.0
007
cr nn 008mamaa
008
221228s2022 sz | s |||| 0|eng d
020
$a
9783030749187
$9
978-3-030-74918-7
024
7
$a
10.1007/978-3-030-74918-7
$2
doi
035
$a
978-3-030-74918-7
050
4
$a
RC321-580
072
7
$a
PSAN
$2
bicssc
072
7
$a
MED057000
$2
bisacsh
072
7
$a
PSAN
$2
thema
082
0 4
$a
612.8
$2
23
100
1
$a
Knösche, Thomas R.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1389925
245
1 0
$a
EEG/MEG Source Reconstruction
$h
[electronic resource] :
$b
Textbook for Electro-and Magnetoencephalography /
$c
by Thomas R. Knösche, Jens Haueisen.
250
$a
1st ed. 2022.
264
1
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2022.
300
$a
XIX, 415 p. 174 illus. in color.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
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
2 4
$a
Biological Imaging.
$3
1388121
650
2 4
$a
Imaging Techniques.
$3
1387817
650
2 4
$a
Biomedical Engineering and Bioengineering.
$3
1211019
650
1 4
$a
Neuroscience.
$3
569964
650
0
$a
Imaging systems in biology.
$3
640661
650
0
$a
Imaging systems.
$3
639186
650
0
$a
Materials—Analysis.
$3
1366463
650
0
$a
Biomedical engineering.
$3
588770
650
0
$a
Neurosciences.
$3
593561
700
1
$a
Haueisen, Jens.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1389926
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9783030749163
776
0 8
$i
Printed edition:
$z
9783030749170
856
4 0
$u
https://doi.org/10.1007/978-3-030-74918-7
912
$a
ZDB-2-SBL
912
$a
ZDB-2-SXB
950
$a
Biomedical and Life Sciences (SpringerNature-11642)
950
$a
Biomedical and Life Sciences (R0) (SpringerNature-43708)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入