Neuroscience is an interdisciplinary field that strives to understand the functioning of neural systems at levels ranging from biomolecules and cells to behaviour and higher brain functions (perception, memory, cognition). Neurophysics has flourished over the past three decades, becoming an indelible part of neuroscience, and has arguably entered its maturity. It encompasses a vast array of approaches stemming from theoretical physics, computer science, and applied mathematics. This book p...

Why are we conscious? Why do we experience the taste of almonds or the colour red? What is the experience of choosing between beer and wine, and how do we do it? Why do we think that only organisms with brains can do this, although our brains are based on the same sort of physics as everything else in the universe? The conventional consciousness studies of the last twenty years, wedded to a nineteenth century view of physics and biology, has failed to produce anything of explanatory value....

This book introduces stochastic dynamical systems theory in order to synthesize our current knowledge of climate variability. Nonlinear processes, such as advection, radiation and turbulent mixing, play a central role in climate variability. These processes can give rise to transition phenomena, associated with tipping or bifurcation points, once external conditions are changed. The theory of dynamical systems provides a systematic way to study these transition phenomena. Its stochastic ex...

Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains describes a comprehensive framework for the identification and analysis of nonlinear dynamic systems in the time, frequency, and spatio-temporal domains. This book is written with an emphasis on making the algorithms accessible so that they can be applied and used in practice.Includes coverage of:The NARMAX (nonlinear autoregressive moving aver...

An extensive update to a classic textStochastic geometry and spatial statistics play a fundamental role in many modern branches of physics, materials sciences, engineering, biology and environmental sciences. They offer successful models for the description of random two- and three-dimensional micro and macro structures and statistical methods for their analysis.The previous edition of this book has served as the key reference in its field ...

The author is a space scientist of international reputation with a close and active relation with music (he studied organ with the late maestros Héctor Zeoli in Buenos Aires and Hans Jendis in Göttingen), who organized and directed the international workshops on the Neuropsychological Foundations of Music at the Carinthian Music Festivals in Ossiach, Austria. These workshops, held regularly between 1973 and 1985, have been credited as being the originators of the interdisciplinary approach...

This handbook and ready reference presents a combination of statistical, information-theoretic, and data analysis methods to meet the challenge of designing empirical models involving molecular descriptors within bioinformatics. The topics range from investigating information processing in chemical and biological networks to studying statistical and information-theoretic techniques for analyzing chemical structures to employing data analysis and machine learning techniques for QSAR/QSPR.

Presents the latest advances in complex-valued neural networks by demonstrating the theory in a wide range of applicationsComplex-valued neural networks is a rapidly developing neural network framework that utilizes complex arithmetic, exhibiting specific characteristics in its learning, self-organizing, and processing dynamics. They are highly suitable for processing complex amplitude, composed of amplitude and phase, which is one of the core concepts in physical ...

Protein NMR Spectroscopy, Second Edition combines a comprehensive theoretical treatment of NMR spectroscopy with an extensive exposition of the experimental techniques applicable to proteins and other biological macromolecules in solution. Beginning with simple theoretical models and experimental techniques, the book develops the complete repertoire of theoretical principles and experimental techniques necessary for understanding and implementing the most sophisticated NMR experiments. Imp...

MATLAB for Neuroscientists: An Introduction to Scientific Computing in MATLAB is the first comprehensive teaching resource and textbook for the teaching of MATLAB in the Neurosciences and in Psychology. MATLAB is unique in that it can be used to learn the entire empirical and experimental process, including stimulus generation, experimental control, data collection, data analysis and modeling. Thus a wide variety of computational problems can be addressed in a single programming environmen...

Dictionary of Scientific Principles presents a unique and timeless collection of (almost) all known rules or laws commonly called principles, identified throughout the history of scientific development, their definition, and use. Exploring a broad range of disciplines, the book first lists more than 2,000 principles organized in a standard alphabetical order, then provides a list of subject headings for which related principles are identified. A staple addition to every library, t...

Leading authorities in the field review current experimental and theoretical knowledge oncriticality and brain function.The book begins by summarizing experimental evidence for criticality and self-organizedcriticality in the brain. Subsequently, important breakthroughs in modeling of critical neuronal circuits and how to establish self-organized criticality in the brain are described.A milestone publication, defining upcoming directions of research in this ne...