Overview
- Illustrates how the wavelet transform provides new insights into the complex behavior of neural systems
- Includes the latest topics relevant for a broad audience working in experimental and computational neuroscience
- Features a self-contained introduction and review of an emerging topic
- Suitable as graduate-level text for non-specialists and students
Part of the book series: Springer Series in Synergetics (SSSYN)
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Table of contents (10 chapters)
Keywords
About this book
This book illustrates how modern mathematical wavelet transform techniques offer fresh insights into the complex behavior of neural systems at different levels: from the microscopic dynamics of individual cells to the macroscopic behavior of large neural networks. It also demonstrates how and where wavelet-based mathematical tools can provide an advantage over classical approaches used in neuroscience. The authors well describe single neuron and populational neural recordings.
This 2nd edition discusses novel areas and significant advances resulting from experimental techniques and computational approaches developed since 2015, and includes three new topics:
• Detection of fEPSPs in multielectrode LFPs recordings.
• Analysis and Real-time Classification of Motor-related EEG Patterns;
The book is a valuable resource for neurophysiologists and physicists familiar with nonlinear dynamical systems and data processing, as well as for graduate students specializing in these and related areas.
Authors and Affiliations
About the authors
Bibliographic Information
Book Title: Wavelets in Neuroscience
Authors: Alexander E. Hramov, Alexey A. Koronovskii, Valeri A. Makarov, Vladimir A. Maksimenko, Alexey N. Pavlov, Evgenia Sitnikova
Series Title: Springer Series in Synergetics
DOI: https://doi.org/10.1007/978-3-030-75992-6
Publisher: Springer Cham
eBook Packages: Physics and Astronomy, Physics and Astronomy (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-75991-9Published: 17 June 2021
Softcover ISBN: 978-3-030-75994-0Published: 18 June 2022
eBook ISBN: 978-3-030-75992-6Published: 16 June 2021
Series ISSN: 0172-7389
Series E-ISSN: 2198-333X
Edition Number: 2
Number of Pages: XVI, 384
Number of Illustrations: 105 b/w illustrations, 69 illustrations in colour
Topics: Biological and Medical Physics, Biophysics, Mathematical Models of Cognitive Processes and Neural Networks, Neurosciences, Complexity, Graph Theory