Magnetoencephalography: From Signals to Dynamic Cortical Networks

ISBN-13: 9783030000868 / Angielski / Twarda / 2019 / 1430 str.

Selma Supek; Cheryl J. Aine

Opis

This book surveys MEG basics and covers the latest methodological, empirical and clinical research. Includes tutorials on instrumentation, measurement, modeling and experimental design, discussion of open issues, future developments and new applications.

Spis treści

MEG as an Enabling Tool in Neuroscience - Transcending Boundaries with New Analysis Methods and Devices

Instrumentation for Measuring MEG Signals

Novel Noise Reduction Methods

Electric and Magnetic Fields of the Brain

Forward Modeling and Tissue Conductivities

EEG/MEG Source Estimation and Spatial Filtering: The Linear Toolkit

Designing MEG Experiments

Magnetoencephalographic Imaging

MEG and Multimodal Integration

Simultaneous recordings of MEG and intracerebral EEG

Fusing Concurrent EEG and fMRI Intrinsic Networks

Nonparametric Statistical Analysis of Map Topographies on the Epoch Level

Dual Signal Subspace Projection (DSSP): A Powerful Algorithm for Interference Removal and Selective Detection of Deep Sources

MNE: Software for Acquiring, Processing,and Visualizing MEG/EEG Data

MRIVIEW: A Software Package for the Analysis and Visualization of Brain Imaging Data

MEG/EEG Data Analysis Using EEGLAB

MEG-SIM Web Portal: A Database of Realistic Simulated and Empirical MEG Data for Testing Algorithms

An Introduction to MEG Connectivity Measurements

Human Brain Oscillations: From Physiological Mechanisms to Analysis and Cognition

Studying Dynamic Neural Interactions with MEG

Unified Principles of Thalamocortical Network Dynamics: A Framework for Typical/Atypical Functional Connectivity

Temporal and Spectral Signatures of the Default Mode Network

Methods to Estimate Functional and Effective Brain Connectivity from MEG Data Robust to Artifacts of Volume Conduction

Recent Developments in MEG Network Analysis

Analyzing MEG Data with Granger Causality: Promises and Pitfalls

Fetal Magnetoencephalography (fMEG)

Current Status and Future Prospects of Perinatal MEG

Whole-Head Child MEG Systems and Their Applications

Brain Dynamics in Pediatric MEG

MEG Studies on the Connectivity of Brain Networks in Children

Technological Challenges of Pediatric MEG and Potential Solutions: The Aston Experience

Application of MEG in Understanding the Development of Executive and Social Cognitive Functions

Language Processing in Atypical Development: Looking Below the Surface with MEG

Towards the Understanding of Healthy and Pathological Aging Through MEG

Timing the Brain to Time the Mind: Critical Contributions of Time-resolved Neuroimaging for Temporal Cognition

MEG Auditory Research

MEG Studies on Music

Sensorimotor Integration: The Somatosensory System and Voluntary Movement

Pain- and Itch-Related Magnetic Fields

Selection of Stimulus Parameters for Visual MEG Studies of Sensation and Cognition

MEG in Epilepsy and Pre-surgical Functional Mapping

Toward Brain Connectivity in Epilepsy Using MEG

Presurgical MEG to Forecast Pediatric Cortical Epilepsies

Presurgical Localization of Language Regions and Their Networks

Cognitive Decline Associated with Aging, Alzheimer’s Disease, and Cerebrovascular Risk: Advantages of Dynamic Imaging with MEG

Review of Schizophrenia Research Using MEG

MEG Imaged Pathways of Stuttering

Neuropsychopharmacology: Recent MEG Investigations

Developments in Clinical MEG and Its Combination with Navigated TMS

Neural Decoding and Brain Machine Interfaces Based on Electromagnetic Oscillatory Activities: A Challenge for MEG

Organizational Cognitive Neuroscience: A New Frontier for Magnetoencephalography

Food Meets Brain

Zero Helium Boiloff MEG Technology

Ultra-Low-Field MRI and Its Combination with MEG

Neuronal Current Imaging with Ultralow-Field NMR Techniques

Optically Pumped Magnetometers for MEG

On-Scalp MEG

Spin Electronics-Based Magnetic Sensors for Biomagnetic Measurements

Magnetic Relaxometry: A Comparison to Magnetoencephalography

O autorze

Dr. Selma Supek obtained her degrees in physics. She entered the field of functional brain imaging using MEG during her doctoral research in the Biophysics Group, Los Alamos National Laboratory – LANL (1988–1993). After returning to Zagreb, Croatia, she continued collaborations with MEG/EEG laboratories at LANL and Mind Research Network and established new ones at ITAB in Chieti, HUCH BioMag Laboratory, Aalto University, University of Heidelberg, TU Ilmenau, and University of Jena. Research interests of Selma Supek include retinotopic organization of the visual cortex, spatiotemporal resolution of MEG, face processing, cognitive neurodynamics, auditory processing, and translational and educational neuroscience. She introduced functional brain imaging methods, in particular MEG, in Croatia both in research and education programs at diploma and doctoral levels. Selma Supek founded a series of intensive international graduate courses MIND AND BRAIN (www.brain.com.hr) within the academic program of the Inter-University Centre Dubrovnik, and cofounded and codirected the first interdisciplinary international postgraduate program “Language Communication and Cognitive Neuroscience” of the University of Zagreb. She organized and chaired Biomag 2010 (www.biomag2010.org) and serves as a permanent member of the International Advisory Board for Biomag conferences which she chaired in 2010–2012.

Dr. Cheryl Aine has more than 30 years of research experience in the neuroimaging field (e.g., ERPs, MEG, fMRI, DTI, PET, Xenon-133 for imaging rCBF). She is most noted for her work using MEG and has served in several leadership positions (e.g., Deputy Group Leader in the Physics Division at Los Alamos National Laboratory and Director of the MEG groups at the Veterans Affairs, the MIND Institute (currently the Mind Research Network), and the University of New Mexico Department of Radiology in Albuquerque, New Mexico). Her research interests have ranged from basic vision (e.g., retinotopic organization of human visual cortex and visual selective attention), use of simulated data to validate analysis methods, and studies of cognitive decline in clinical populations (e.g., normal aging, mild cognitive impairment/Alzheimer’s disease, schizophrenia).