Signal Processing for Neuroscientists

Signal Processing for Neuroscientists

An Introduction to the Analysis of Physiological Signals

2nd Edition - April 20, 2018

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  • Author: Wim van Drongelen
  • eBook ISBN: 9780128104835
  • Hardcover ISBN: 9780128104828

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Signal Processing for Neuroscientists, Second Edition provides an introduction to signal processing and modeling for those with a modest understanding of algebra, trigonometry and calculus. With a robust modeling component, this book describes modeling from the fundamental level of differential equations all the way up to practical applications in neuronal modeling. It features nine new chapters and an exercise section developed by the author. Since the modeling of systems and signal analysis are closely related, integrated presentation of these topics using identical or similar mathematics presents a didactic advantage and a significant resource for neuroscientists with quantitative interest. Although each of the topics introduced could fill several volumes, this book provides a fundamental and uncluttered background for the non-specialist scientist or engineer to not only get applications started, but also evaluate more advanced literature on signal processing and modeling.

Key Features

  • Includes an introduction to biomedical signals, noise characteristics, recording techniques, and the more advanced topics of linear, nonlinear and multi-channel systems analysis
  • Features new chapters on the fundamentals of modeling, application to neuronal modeling, Kalman filter, multi-taper power spectrum estimation, and practice exercises
  • Contains the basics and background for more advanced topics in extensive notes and appendices
  • Includes practical examples of algorithm development and implementation in MATLAB
  • Features a companion website with MATLAB scripts, data files, figures and video lectures


Graduate and advanced undergraduate students in biological and biomedical sciences, neuroscientists, neurologists, biomedical engineers, post-doctoral fellows, researchers. Potential users include neuroscientists, clinicians, engineers, mathematicians

Table of Contents

  • 1. Introduction
    2. Data Acquisition
    3. Noise
    4. Signal Averaging
    5. Real and Complex Fourier Series
    6. Continuous, Discrete, and Fast Fourier Transform
    7. 1D and 2D Fourier Transform Applications
    8. Lomb’s Algorithm and Multi-Taper Power Spectrum Estimation
    9. Differential Equations: Introduction
    10. Differential Equations: Phase Space and Numerical Solutions
    11. Modeling
    12. Laplace and z-Transform
    13. LTI Systems, Convolution, Correlation, Coherence, and the Hilbert Transform
    14. Causality
    15. Introduction to Filters: The RC-Circuit
    16. Filters: Analysis
    17. Filters: Specification, Bode Plot, and Nyquist Plot
    18. Filters: Digital Filters
    19. Kalman Filter
    20. Spike Train Analyses
    21. Wavelet Analysis: Time Domain Properties
    22. Wavelet Analysis: Frequency Domain Properties
    23. Low Dimensional Nonlinear Dynamics: Fixed Points, Limit Cycles and Bifurcations
    24. Volterra Series
    25. Wiener Series
    26. Poisson-Wiener Series
    27. Nonlinear Techniques
    28. Decomposition of Multi-Channel Data
    29. Modeling Neural Systems: Cellular Models
    30. Modeling Neural Systems: Network Models

Product details

  • No. of pages: 740
  • Language: English
  • Copyright: © Academic Press 2018
  • Published: April 20, 2018
  • Imprint: Academic Press
  • eBook ISBN: 9780128104835
  • Hardcover ISBN: 9780128104828

About the Author

Wim van Drongelen

Wim van 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

Affiliations and Expertise

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

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