Adaptive Spatial Filters for Electromagnetic Brain Imaging

  • Kensuke Sekihara
  • Srikatan S. Nagarajan

Part of the Series in Biomedical Engineering book series (BIOMENG)

Table of contents

  1. Front Matter
    Pages I-XI
  2. Kensuke Sekihara, Srikatan S. Nagarajan
    Pages 1-7
  3. Kensuke Sekihara, Srikatan S. Nagarajan
    Pages 9-25
  4. Kensuke Sekihara, Srikatan S. Nagarajan
    Pages 27-36
  5. Kensuke Sekihara, Srikatan S. Nagarajan
    Pages 37-63
  6. Kensuke Sekihara, Srikatan S. Nagarajan
    Pages 65-82
  7. Kensuke Sekihara, Srikatan S. Nagarajan
    Pages 83-107
  8. Kensuke Sekihara, Srikatan S. Nagarajan
    Pages 109-123
  9. Kensuke Sekihara, Srikatan S. Nagarajan
    Pages 125-143
  10. Kensuke Sekihara, Srikatan S. Nagarajan
    Pages 145-161
  11. Kensuke Sekihara, Srikatan S. Nagarajan
    Pages 163-178
  12. Kensuke Sekihara, Srikatan S. Nagarajan
    Pages 179-191
  13. Kensuke Sekihara, Srikatan S. Nagarajan
    Pages 193-204
  14. Kensuke Sekihara, Srikatan S. Nagarajan
    Pages 205-232
  15. Back Matter
    Pages 233-245

About this book

Introduction

Neural activity in the human brain generates coherent synaptic and intracellular currents in cortical columns that create electromagnetic signals which can be measured outside the head using magnetoencephalography (MEG) and electroencephalography (EEG). Electromagnetic brain imaging refers to techniques that reconstruct neural activity from MEG and EEG signals. Electromagnetic brain imaging is unique among functional imaging techniques for its ability to provide spatio-temporal brain activation profiles that reflect not only where the activity occurs in the brain but also when this activity occurs in relation to external and internal cognitive events, as well as to activity in other brain regions. Adaptive spatial filters are powerful algorithms for electromagnetic brain imaging that enable high-fidelity reconstruction of neuronal activity. This book describes the technical advances of adaptive spatial filters for electromagnetic brain imaging by integrating and synthesizing available information and describes various factors that affect its performance. The intended audience include graduate students and researchers interested in the methodological aspects of electromagnetic brain imaging.

Keywords

Adaptive beamformers Electroencephalography EEG Elektroenzephalografie IFMBE Imaging methods Magnetoencephalography MEG Signal Processing brain imaging electromagnetic brain imaging imaging techniques

Authors and affiliations

  • Kensuke Sekihara
    • 1
  • Srikatan S. Nagarajan
    • 2
  1. 1.Dept. of Systems Design & EngineeringTokyo Metropolitan UniversityHinoJapan
  2. 2.Department of RadiologyUniversity of California Biomagnetic Imaging LaboratorySan FranciscoUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-79370-0
  • Copyright Information Springer-Verlag Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-79369-4
  • Online ISBN 978-3-540-79370-0
  • Series Print ISSN 1864-5763
  • About this book