This book examines theoretical and applied aspects of wavelet analysis
in neurophysics, describing in detail different practical applications
of the wavelet theory in the areas of neurodynamics and neurophysiology
and providing a review of fundamental work that has been carried out in
these fields over the last decade.
Chapters 1 and 2 introduce and review the relevant foundations of
neurophysics and wavelet theory, respectively, pointing on one hand to
the various current challenges in neuroscience and introducing on the
other the mathematical techniques of the wavelet transform in its two
variants (discrete and continuous) as a powerful and versatile tool for
investigating the relevant neuronal dynamics.
Chapter 3 then analyzes results from examining individual neuron
dynamics and intracellular processes. The principles for recognizing
neuronal spikes from extracellular recordings and the advantages of
using wavelets to address these issues are described and combined with
approaches based on wavelet neural networks (chapter 4). The features of
time-frequency organization of EEG signals are then extensively
discussed, from theory to practical applications (chapters 5 and 6).
Lastly, the technical details of automatic diagnostics and processing of
EEG signals using wavelets are examined (chapter 7).
The book will be a useful resource for neurophysiologists and physicists
familiar with nonlinear dynamical systems and data processing, as well
as for graduate students specializing in the corresponding areas.
