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.

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

Autorentext
Alexander N. Pisarchik is Distinguished Researcher at the Center for Biomedical Technologies of the Universidad Politécnica de Madrid, Spain, and Senior Researcher at the Innopolis University, Russia. His research interests include nonlinear and stochastic dynamics, chaos, synchronization, complex networks, chaotic cryptography, cognitive neuroscience and brain-computer interfaces. Alexander E. Hramov is Head of the Laboratory of Neuroscience and Cognitive Technologies and Full Professor at the Innopolis University, Russia, Leading Researcher at the Center for Neurotechnology and Machine Learning of the Immanuel Kant Baltic Federal University, Saratov State Medical University and Lobachevsky University of Niznij Novgorod. Scientific activity of Prof. Hramov is devoted to nonlinear dynamics, theory of complex systems, artificial intelligence and its application to the analysis and modeling of neuronal brain activity.

Inhalt

Mathematical Methods of Signal Processing in Neuroscience.- Brief Tour of Wavelet Theory.- Analysis of Single Neuron Recordings.- Classification of Neuronal Spikes from Extracellular Recordings.- Analysis of Gamma-Waves in Multielectrode LFP Recordings.- Wavelet Approach to the Study of Rhythmic Neuronal Activity.- Wavelet-based Approach to Epilepsy.- Analysis of Visual Sensory Processing in the Brain and Brain-Computer Interfaces for Human Attention Control.- Analysis and Real-Time Classication of Motor-related EEG and MEG Patterns.- Conclusion.