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EEG/MEG Source Reconstruction

EEG/MEG Source Reconstruction PDF Author: Thomas R. Knösche
Publisher: Springer Nature
ISBN: 3030749185
Category : Medical
Languages : en
Pages : 429

Book Description
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.

EEG/MEG Source Reconstruction

EEG/MEG Source Reconstruction PDF Author: Thomas R. Knösche
Publisher: Springer Nature
ISBN: 3030749185
Category : Medical
Languages : en
Pages : 429

Book Description
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.

Brain and Human Body Modeling 2020

Brain and Human Body Modeling 2020 PDF Author: Sergey N. Makarov
Publisher: Springer Nature
ISBN: 3030456234
Category : Biomedical engineering
Languages : en
Pages : 395

Book Description
The 41st Annual International Conference of the IEEE EMBS, took place between July 23 and 27, 2019, in Berlin, Germany. The focus was on "Biomedical engineering ranging from wellness to intensive care." This conference provided an opportunity for researchers from academia and industry to discuss a variety of topics relevant to EMBS and hosted the 4th Annual Invited Session on Computational Human Models. At this session, a bevy of research related to the development of human phantoms was presented, together with a substantial variety of practical applications explored through simulation.

Magnetoencephalography

Magnetoencephalography PDF Author: Selma Supek
Publisher: Springer
ISBN: 3642330452
Category : Technology & Engineering
Languages : en
Pages : 999

Book Description
Magnetoencephalography (MEG) is an invaluable functional brain imaging technique that provides direct, real-time monitoring of neuronal activity necessary for gaining insight into dynamic cortical networks. Our intentions with this book are to cover the richness and transdisciplinary nature of the MEG field, make it more accessible to newcomers and experienced researchers and to stimulate growth in the MEG area. The book presents a comprehensive overview of MEG basics and the latest developments in methodological, empirical and clinical research, directed toward master and doctoral students, as well as researchers. There are three levels of contributions: 1) tutorials on instrumentation, measurements, modeling, and experimental design; 2) topical reviews providing extensive coverage of relevant research topics; and 3) short contributions on open, challenging issues, future developments and novel applications. The topics range from neuromagnetic measurements, signal processing and source localization techniques to dynamic functional networks underlying perception and cognition in both health and disease. Topical reviews cover, among others: development on SQUID-based and novel sensors, multi-modal integration (low field MRI and MEG; EEG and fMRI), Bayesian approaches to multi-modal integration, direct neuronal imaging, novel noise reduction methods, source-space functional analysis, decoding of brain states, dynamic brain connectivity, sensory-motor integration, MEG studies on perception and cognition, thalamocortical oscillations, fetal and neonatal MEG, pediatric MEG studies, cognitive development, clinical applications of MEG in epilepsy, pre-surgical mapping, stroke, schizophrenia, stuttering, traumatic brain injury, post-traumatic stress disorder, depression, autism, aging and neurodegeneration, MEG applications in cognitive neuropharmacology and an overview of the major open-source analysis tools.

Handbook of Neural Activity Measurement

Handbook of Neural Activity Measurement PDF Author: Romain Brette
Publisher: Cambridge University Press
ISBN: 0521516226
Category : Mathematics
Languages : en
Pages : 493

Book Description
Underlying principles of the various techniques are explained, enabling neuroscientists to extract meaningful information from their measurements.

Niedermeyer's Electroencephalography

Niedermeyer's Electroencephalography PDF Author: Donald L. Schomer
Publisher: Lippincott Williams & Wilkins
ISBN: 1451153155
Category : Medical
Languages : en
Pages : 1308

Book Description
The leading reference on electroencephalography since 1982, Niedermeyer's Electroencephalography is now in its thoroughly updated Sixth Edition. An international group of experts provides comprehensive coverage of the neurophysiologic and technical aspects of EEG, evoked potentials, and magnetoencephalography, as well as the clinical applications of these studies in neonates, infants, children, adults, and older adults. This edition's new lead editor, Donald Schomer, MD, has updated the technical information and added a major new chapter on artifacts. Other highlights include complete coverage of EEG in the intensive care unit and new chapters on integrating other recording devices with EEG; transcranial electrical and magnetic stimulation; EEG/TMS in evaluation of cognitive and mood disorders; and sleep in premature infants, children and adolescents, and the elderly. A companion website includes fully searchable text and image bank.

Electromagnetic Brain Imaging

Electromagnetic Brain Imaging PDF Author: Kensuke Sekihara
Publisher: Springer
ISBN: 3319149474
Category : Medical
Languages : en
Pages : 277

Book Description
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 ready to pursue research in either the engineering or the neuroscientific aspects of electromagnetic brain imaging. This textbook will not only appeal to graduate students but all scientists and engineers engaged in research on electromagnetic brain imaging.

MEG-EEG Primer

MEG-EEG Primer PDF Author: Riitta Hari
Publisher: Oxford University Press
ISBN: 0197542182
Category : Medical
Languages : en
Pages : 481

Book Description
"Neuronal communication in the brain is associated with minute electrical currents that give rise to both electrical potentials on the scalp (measurable by means of electroencephalography [EEG]) and magnetic fields outside the head (measurable by means of magnetoencephalography [MEG]). Both MEG and EEG are noninvasive neurophysiological methods used to study brain dynamics, temporal changes in the activation patterns, and sequences. Their differences between MEG and EEG mainly reflect differences in the spread of electric potentials and magnetic fields generated by the same electric currents in the human brain. In this chapter, we give an overall description of the main principles of MEG and EEG, going deeper into details in the following chapters"--

From raw MEG/EEG to publication: How to perform MEG/EEG group analysis with free academic software

From raw MEG/EEG to publication: How to perform MEG/EEG group analysis with free academic software PDF Author: Vladimir Litvak
Publisher: Frontiers Media SA
ISBN: 2832525644
Category : Science
Languages : en
Pages : 411

Book Description


Encyclopedia of Computational Neuroscience

Encyclopedia of Computational Neuroscience PDF Author: Dieter Jaeger
Publisher:
ISBN: 9781461473206
Category : Computational neuroscience
Languages : en
Pages :

Book Description


Brain Informatics

Brain Informatics PDF Author: Mufti Mahmud
Publisher: Springer Nature
ISBN: 3031150376
Category : Computers
Languages : en
Pages : 390

Book Description
This book constitutes the refereed proceedings of the 15th International Conference on Brain Informatics, BI 2022, held as hybrid event in Padua, Italy (in person) and Queensland, Australia (online) in July 2022. The 29 papers were selected from 65 submissions and the main theme of BI 2022 is Brain Science meets Artificial Intelligence with respect to the five tracks: Cognitive and computational foundations of brain science; human information processing systems; brain big data analytics, curation and management; informatics paradigms for brain and mental health research; and brain-machine intelligence and brain inspired computing.