Signal Processing for Neuroscientists - 1st Edition - ISBN: 9780123708670, 9780080467757

Signal Processing for Neuroscientists

1st Edition

An Introduction to the Analysis of Physiological Signals

Editors: Wim Drongelen
Authors: Wim Drongelen
eBook ISBN: 9780080467757
Hardcover ISBN: 9780123708670
Imprint: Academic Press
Published Date: 13th December 2006
Page Count: 320
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Description

Signal Processing for Neuroscientists introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest background in mathematics, physics, and computer programming. The focus of this text is on what can be considered the ‘golden trio’ in the signal processing field: averaging, Fourier analysis, and filtering. Techniques such as convolution, correlation, coherence, and wavelet analysis are considered in the context of time and frequency domain analysis. The whole spectrum of signal analysis is covered, ranging from data acquisition to data processing; and from the mathematical background of the analysis to the practical application of processing algorithms. Overall, the approach to the mathematics is informal with a focus on basic understanding of the methods and their interrelationships rather than detailed proofs or derivations. One of the principle goals is to provide the reader with the background required to understand the principles of commercially available analyses software, and to allow him/her to construct his/her own analysis tools in an environment such as MATLAB®.

Key Features

  • Multiple color illustrations are integrated in the text
  • Includes an introduction to biomedical signals, noise characteristics, and recording techniques
  • Basics and background for more advanced topics can be found in extensive notes and appendices
  • A Companion Website hosts the MATLAB scripts and several data files:  http://www.elsevierdirect.com/companion.jsp?ISBN=9780123708670

Readership

Neuroscientists and biomedical engineering students.

Table of Contents

Dedication

Preface

Chapter 1: Introduction

1.1 OVERVIEW

1.2 BIOMEDICAL SIGNALS

1.3 BIOPOTENTIALS

1.4 EXAMPLES OF BIOMEDICAL SIGNALS

1.5 ANALOG-TO-DIGITAL CONVERSION

1.6 MOVING SIGNALS INTO THE MATLAB ANALYSIS ENVIRONMENT

APPENDIX 1.1

Chapter 2: Data Acquisition

2.1 RATIONALE

2.2 THE MEASUREMENT CHAIN

2.3 SAMPLING AND NYQUIST FREQUENCY IN THE FREQUENCY DOMAIN

2.4 THE MOVE TO THE DIGITAL DOMAIN

Appendix 2.1

Chapter 3: Noise

3.1 INTRODUCTION

3.2 NOISE STATISTICS

3.3 SIGNAL-TO-NOISE RATIO

3.4 NOISE SOURCES

APPENDIX 3.1

APPENDIX 3.2

APPENDIX 3.3

APPENDIX 3.4

Chapter 4: Signal Averaging

4.1 INTRODUCTION

4.2 TIME LOCKED SIGNALS

4.3 SIGNAL AVERAGING AND RANDOM NOISE

4.4 NOISE ESTIMATES AND THE ± AVERAGE

4.5 SIGNAL AVERAGING AND NONRANDOM NOISE

4.6 NOISE AS A FRIEND OF THE SIGNAL AVERAGER

4.7 EVOKED POTENTIALS

4.8 OVERVIEW OF COMMONLY APPLIED TIME DOMAIN ANALYSIS TECHNIQUES

Chapter 5: Real and Complex Fourier Series

5.1 INTRODUCTION

5.2 THE FOURIER SERIES

5.3 THE COMPLEX FOURIER SERIES

5.4 EXAMPLES

APPENDIX 5.1

APPENDIX 5.2

Chapter 6: Continuous, Discrete, and Fast Fourier Transform

6.1 INTRODUCTION

6.2 THE FOURIER TRANSFORM

6.3 DISCRETE FOURIER TRANSFORM AND THE FFT ALGORITHM

6.4 UNEVENLY SAMPLED DATA

Chapter 7: Fourier Transform Applications

7.1 SPECTRAL ANALYSIS

7.2 TOMOGRAPHY

APPENDIX 7.1

Chapter 8: LTI Systems, Convolution, Correlation, and Coherence

8.1 INTRODUCTION

8.2 LINEAR TIME INVARIANT (LTI) SYSTEM

8.3 CONVOLUTION

8.4 AUTOCORRELATION AND CROSS-CORRELATION

8.5 COHERENCE

APPENDIX 8.1

Chapter 9: Laplace and z-Transform

9.1 INTRODUCTION

9.2 THE USE OF TRANSFORMS TO SOLVE ODEs

9.3 THE LAPLACE TRANSFORM

9.4 EXAMPLES OF THE LAPLACE TRANSFORM

9.5 THE Z-TRANSFORM

9.6 THE Z-TRANSFORM AND ITS INVERSE

9.7 EXAMPLE OF THE z-TRANSFORM

APPENDIX 9.1

APPENDIX 9.2

APPENDIX 9.3

Chapter 10: Introduction to Filters: The RC Circuit

10.1 INTRODUCTION

10.2 FILTER TYPES AND THEIR FREQUENCY DOMAIN CHARACTERISTICS

10.3 RECIPE FOR AN EXPERIMENT WITH AN RC CIRCUIT

Chapter 11: Filters: Analysis

11.1 INTRODUCTION

11.2 THE RC CIRCUIT

11.3 THE EXPERIMENTAL DATA

APPENDIX 11.1

APPENDIX 11.2

APPENDIX 11.3

Chapter 12: Filters: Specification, Bode Plot, and Nyquist Plot

12.1 INTRODUCTION: FILTERS AS LINEAR TIME INVARIANT (LTI) SYSTEMS

12.2 TIME DOMAIN RESPONSE

12.3 THE FREQUENCY CHARACTERISTIC

12.4 NOISE AND THE FILTER FREQUENCY RESPONSE

Chapter 13: Filters: Digital Filters

13.1 INTRODUCTION

13.2 IIR AND FIR DIGITAL FILTERS

13.3 AR, MA, AND ARMA FILTERS

13.4 FREQUENCY CHARACTERISTIC OF DIGITAL FILTERS

13.5 MATLAB IMPLEMENTATION

13.6 FILTER TYPES

13.7 FILTER BANK

13.8 FILTERS IN THE SPATIAL DOMAIN

APPENDIX 13.1

Chapter 14: Spike Train Analysis

14.1 INTRODUCTION

14.2 POISSON PROCESSES AND POISSON DISTRIBUTIONS

14.3 ENTROPY AND INFORMATION

14.4 THE AUTOCORRELATION FUNCTION

14.5 CROSS-CORRELATION

APPENDIX 14.1

APPENDIX 14.2

Chapter 15: Wavelet Analysis: Time Domain Properties

15.1 INTRODUCTION

15.2 WAVELET TRANSFORM

15.3 OTHER WAVELET FUNCTIONS

15.4 TWO-DIMENSIONAL APPLICATION

APPENDIX 15.1

Chapter 16: Wavelet Analysis: Frequency Domain Properties

16.1 INTRODUCTION

16.2 THE CONTINUOUS WAVELET TRANSFORM (CWT)

16.3 TIME FREQUENCY RESOLUTION

16.4 MATLAB WAVELET EXAMPLES

Chapter 17: Nonlinear Techniques

17.1 INTRODUCTION

17.2 NONLINEAR DETERMINISTIC PROCESSES

17.3 LINEAR TECHNIQUES FAIL TO DESCRIBE NONLINEAR DYNAMICS

17.4 EMBEDDING

17.5 METRICS FOR CHARACTERIZING NONLINEAR PROCESSES

17.6 APPLICATION TO BRAIN ELECTRICAL ACTIVITY

References

Index

Details

No. of pages:
320
Language:
English
Copyright:
© Academic Press 2006
Published:
Imprint:
Academic Press
eBook ISBN:
9780080467757
Hardcover ISBN:
9780123708670

About the Editor

Wim Drongelen

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/

Affiliations and Expertise

University of Chicago, Department of Pediatrics, Chicago, IL, USA

About the Author

Wim Drongelen

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/

Affiliations and Expertise

University of Chicago, Department of Pediatrics, Chicago, IL, USA