Description
Springer Introduction to Brain Topography 1st Editon 2012 Softbound by Peter K.H. Wong
It had been difficult to find appropriate teaching material for students and newcomers to this field of brain electromagnetic topography. In part, this is due to the many disciplines involved, requiring some knowledge of the physical sciences, mathematics, neurophysiology and anatomy. It is my hope that this book will be found suitable for introducing interested workers to this exciting field. Advanced topics will not be covered, as there are many excellent texts available. Peter K.H. Wong vii ACKNOWLEDGEMENT My co-authors, Hal Weinberg and Roberto Bencivenga, for their support; Richard Hamer, for all his early advice; Ernst Rodin and Gene Ramsay, for their encouragement; Wendy Cummings for her assistance; Technologists from the Department of Diagnostic Neurophysiology for collecting such excellent data; Bio-Logic Systems Corp. for permission to use some data as illustration; and all my friends and colleagues. My wife Elke, for putting up with me throughout this presumptuous endeavour. The manuscript was delivered in camera-ready form to the Publisher. Illustrations were created using Harvard Graphics and CorelDraw software. ix CONTENTS Part 1: Fundamentals. 1 1.1 Introduction . . . 1 1.2 Data Aquisition. . 3 Map Construction. 8 Interpolation . . . 12 1.3 Spatial Sampling . . 16 1.4 Reference and Reference-Dependence 20 1.5 Map Display Methods ..... . 27 Scaling and Floating Voltage Scales. 37 Summary Maps .......... . 37 1.6 Identification of Topographic Features 41 1.7 Spike Mapping .. . 51 1.8 Post-Processing 61 Analog Front-end. 62 Digital Filtering . 63 Reference Manipulation .. 65 Statistical Mapping . 1: Fundamentals.- 1.1 Introduction.- 1.2 Data Aquisition.- 1.3 Spatial Sampling.- 1.4 Reference and Reference-Dependence.- 1.5 Map Display Methods.- 1.6 Identification of Topographic Features.- 1.7 Spike Mapping.- 1.8 Post-Processing.- 1.9 Frequency Analysis.- 2: Source Modelling and Analysis.- 2.1 Concepts of a Source.- 2.2 Physical Model.- 2.3 Inverse Solution.- 2.4 Stability of Dipole Solutions.- 2.5 Data Characterization.- 3: Magnetoencephalography.- 3.1 Instrumentation.- 3.2 Meg Measurements and Generators.- 3.3 Spontaneous MEG Rhythms.- 3.4 Review of MEG Studies.- 3.5 Concerns and Outlook.- 4: Statistical Approaches.- 4.1 Introduction.- 4.2 Assumptions and Difficulties.- 4.3 Normative Data.- 4.4 Statistical Comparisons.- 4.5 Classification.- 4.6 Exploratory vs. Confirmatory Analysis.- 5: Selected Normative Data.- Flash VEP.- Pattern Reversal VEP.- P300 AEP.- Resting EEG.- References.