Signal Processing for Neuroscientists

Wim van Drongelen9780123849151, 0123849152

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 towards some of the more complex analysis techniques.
This book is a companion to the previously published book,’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 mulit-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

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Table of contents :
cover……Page 1
Preface……Page 2
1. Introduction……Page 4
2. Data Acquisition……Page 17
3. Noise……Page 36
4. Signal Averaging……Page 55
5. Real and Complex Fourier Series……Page 71
6. Continuous, Discrete, and Fast Fourier Transform……Page 91
7. Fourier Transform Applications……Page 106
8. LTI Systems, Convolution, Correlation, and Coherence……Page 126
9. Laplace and z-Transform……Page 149
10.Introduction to Filters: The RC Circuit……Page 167
11.Filters: Analysis……Page 174
12.Filters: Specification, Bode Plot, and Nyquist Plot……Page 186
13.Filters: Digital Filters……Page 201
14.Spike Train Analysis……Page 214
15.Wavelet Analysis: Time Domain Properties……Page 239
16.Wavelet Analysis: Frequency Domain Properties……Page 258
17.Nonlinear Techniques……Page 271
References……Page 288
Index……Page 292
Eagle Hill……Page 299