Wavelets in Neuroscience (Hardcover, 2nd ed. 2021)

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 of Visual Sensory Processing in the Brain and BCI for Human Attention Control; * 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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Springer Series in Synergetics
Release date:	June 2021
First published:	2021
Authors:	Alexander E. Hramov • Alexey A. Koronovskii • Valeri A. Makarov • Vladimir A. Maksimenko • Alexey N. Pavlov • Evgenia Sitnikova
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	384
Edition:	2nd ed. 2021
ISBN-13:	978-3-03-075991-9
Categories:	Books > Science & Mathematics > Mathematics > Combinatorics & graph theory Books > Reference & Interdisciplinary > Communication studies > Information theory > Cybernetics & systems theory Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematical modelling Books > Science & Mathematics > Physics > Applied physics & special topics > Biophysics Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > Neurosciences Promotions
LSN:	3-03-075991-1
Barcode:	9783030759919

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