Signal Processing for Neuroscientists, A Companion Volume (eBook)

Advanced Topics, Nonlinear Techniques and Multi-Channel Analysis

Wim van Drongelen (Autor)

eBook Download: PDF

2010 | 1. Auflage
186 Seiten
Elsevier Science (Verlag)
978-0-12-384916-8 (ISBN)

Infos

The popularity of signal processing in neuroscience is increasing, and with the current availability and development of computer hardware and software, it is anticipated that the current growth will continue. Because electrode fabrication has improved and measurement equipment is getting less expensive, electrophysiological measurements with large numbers of channels are now very common. In addition, neuroscience has entered the age of light, and fluorescence measurements are fully integrated into the researcher's toolkit. Because each image in a movie contains multiple pixels, these measurements are multi-channel by nature. Furthermore, the availability of both generic and specialized software packages for data analysis has altered the neuroscientist's attitude toward some of the more complex analysis techniques.

This book is a companion to the previously published Signal Processing for Neuroscientists: An Introduction to the Analysis of Physiological Signals, which introduced readers to the basic concepts. It discusses several advanced techniques, rediscovers methods to describe nonlinear systems, and examines the analysis of multi-channel recordings.

• Covers the more advanced topics of linear and nonlinear systems analysis and multi-channel analysis
• Includes practical examples implemented in MATLAB
• Provides multiple references to the basics to help the student

Wim van Drongelen studied Biophysics at the University Leiden, The Netherlands. After a period in the Laboratoire d'Electrophysiologie, Université Claude Bernard, Lyon, France, he received the Doctoral degree cum laude. In 1980 he received the Ph.D. degree.
He worked for the Netherlands Organization for the Advancement of Pure Research (ZWO) in the Department of Animal Physiology, Wageningen, The Netherlands. He lectured and founded a Medical Technology Department at the HBO Institute Twente, The Netherlands. In 1986 he joined the Benelux office of Nicolet Biomedical as an Application Specialist and in 1993 he relocated to Madison, WI, USA where he was involved in research and development of equipment for clinical neurophysiology and neuromonitoring.
In 2001 he joined the Epilepsy Center at The University of Chicago, Chicago, IL, USA. Currently he is Professor of Pediatrics, Neurology, and Computational Neuroscience. In addition to his faculty position he serves as Technical and Research Director of the Pediatric Epilepsy Center and he is Senior Fellow with the Computation Institute. Since 2003 he teaches applied mathematics courses for the Committee on Computational Neuroscience. His ongoing research interests include the application of signal processing and modeling techniques to help resolve problems in neurophysiology and neuropathology.
For details of recent work see http://epilepsylab.uchicago.edu/

Inhalt

Front Cover 1
Signal Processing for Neuroscientists, A Companion Volume 4
Copyright Page 5
Contents 6
Preface 8
Chapter 1 Lomb's Algorithm and the Hilbert Transform 10
1.1 Introduction 10
1.2 Unevenly Sampled Data 10
1.3 The Hilbert Transform 17
Appendix 1.1 26
Appendix 1.2 27
Appendix 1.3 28
Chapter 2 Modeling 30
2.1 Introduction 30
2.2 Different Types of Models 30
2.3 Examples of Parametric and Nonparametric Models 32
2.4 Polynomials 35
2.5 Nonlinear Systems with Memory 41
Appendix 2.1 45
Chapter 3 Volterra Series 48
3.1 Introduction 48
3.2 Volterra Series 51
3.3 A Second-Order Volterra System 54
3.4 General Second-Order System 60
3.5 System Tests for Internal Structure 62
3.6 Sinusoidal Signals 66
Chapter 4 Wiener Series 70
4.1 Introduction 70
4.2 Wiener Kernels 71
4.3 Determination of the Zero-, First-, and Second-Order Wiener Kernels 78
4.4 Implementation of the Cross-Correlation Method 82
4.5 Relation between Wiener and Volterra Kernels 86
4.6 Analyzing Spiking Neurons Stimulated with Noise 88
4.7 Nonwhite Gaussian Input 93
4.8 Summary 95
Appendix 4.1 96
Appendix 4.2 98
Chapter 5 Poisson–Wiener Series 100
5.1 Introduction 100
5.2 Systems with Impulse Train Input 100
5.3 Determination of the Zero-, First-, and Second-Order Poisson–Wiener Kernels 112
5.4 Implementation of the Cross-Correlation Method 118
5.5 Spiking Output 120
5.6 Summary 121
Appendix 5.1 122
Appendix 5.2 126
Chapter 6 Decomposition of Multichannel Data 128
6.1 Introduction 128
6.2 Mixing and Unmixing of Signals 129
6.3 Principal Component Analysis 132
6.4 Independent Component Analysis 143
Appendix 6.1 164
Chapter 7 Causality 168
7.1 Introduction 168
7.2 Granger Causality 169
7.3 Directed Transfer Function 169
7.4 Combination of Multichannel Methods 184
References 186

Produkt-Details

• Erscheint lt. Verlag: 26.8.2010
• Sprache: englisch
• Themenwelt: Medizin / Pharmazie ► Medizinische Fachgebiete ► Neurologie
• Themenwelt: Medizin / Pharmazie ► Physiotherapie / Ergotherapie ► Orthopädie
• Themenwelt: Studium ► 1. Studienabschnitt (Vorklinik) ► Physiologie
• Themenwelt: Naturwissenschaften ► Biologie ► Biochemie
• Themenwelt: Naturwissenschaften ► Biologie ► Humanbiologie
• Themenwelt: Naturwissenschaften ► Biologie ► Zoologie
• Themenwelt: Naturwissenschaften ► Physik / Astronomie ► Angewandte Physik
• Themenwelt: Technik ► Bauwesen
• ISBN-10: 0-12-384916-0 / 0123849160
• ISBN-13: 978-0-12-384916-8 / 9780123849168