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Neurowissenschaftler suchen nach Antworten auf die Fragen, wie wir lernen und Information speichern, welche Prozesse im Gehirn verantwortlich sind und in welchem Zeitrahmen diese ablaufen. Die Konzepte, die aus der Physik kommen und weiterentwickelt werden, können in Medizin und Soziologie, aber auch in Robotik und Bildanalyse Anwendung finden. Zentrales Thema dieses Buches sind die sogenannten kritischen Phänomene im Gehirn. Diese werden mithilfe mathematischer und physikalischer Modelle beschrieben, mit denen man auch Erdbeben, Waldbrände oder die Ausbreitung von Epidemien modellieren kann. Neuere Erkenntnisse haben ergeben, dass diese selbstgeordneten Instabilitäten auch im Nervensystem auftreten. Dieses Referenzwerk stellt theoretische und experimentelle Befunde internationaler Gehirnforschung vor zeichnet die Perspektiven dieses neuen Forschungsfeldes auf.
Neuronal Networks in Brain Function, CNS Disorders, and Therapeutics, edited by two leaders in the field, offers a current and complete review of what we know about neural networks. How the brain accomplishes many of its more complex tasks can only be understood via study of neuronal network control and network interactions. Large networks can undergo major functional changes, resulting in substantially different brain function and affecting everything from learning to the potential for epilepsy. With chapters authored by experts in each topic, this book advances the understanding of: - How the brain carries out important tasks via networks - How these networks interact in normal brain function - Major mechanisms that control network function - The interaction of the normal networks to produce more complex behaviors - How brain disorders can result from abnormal interactions - How therapy of disorders can be advanced through this network approach This book will benefit neuroscience researchers and graduate students with an interest in networks, as well as clinicians in neuroscience, pharmacology, and psychiatry dealing with neurobiological disorders. - Utilizes perspectives and tools from various neuroscience subdisciplines (cellular, systems, physiologic), making the volume broadly relevant - Chapters explore normal network function and control mechanisms, with an eye to improving therapies for brain disorders - Reflects predominant disciplinary shift from an anatomical to a functional perspective of the brain - Edited work with chapters authored by leaders in the field around the globe – the broadest, most expert coverage available
Affective brain circuits underpin our moods and emotions. Appetitive and aversive stimuli from our exteroceptive and interoceptive worlds play a key role in the activity of these circuits, but we still do not know precisely how to characterize these so-called reward-related and aversion-related systems. Moreover, we do we yet understand how they interact anatomically or functionally. The aim of the current project was to gather some translational evidence to help clarify the role of such circuits. A multi-dimensional problem in its own right, the book contains 14 works from authors exploring these questions at many levels, from the cellular to the cognitive-behavioural, and from both experimental and conceptual viewpoints. The editorial which introduces the book provides brief summaries of each perspective (Hayes, Northoff, Greenshaw, 2015). While questions of how to accurately define affect- and emotion-related concepts at the psychological level are far from answered, here we have attempted to provide some insight into the brain-based underpinnings of such processes. The near future will undoubtedly involve making new inroads and will require the joint efforts of behavioural, brain-based, and philosophical perspectives to do so.
As an introductory account of the theory of phase transitions and critical phenomena, this book reflects lectures given by the authors to graduate students at their departments and is thus classroom-tested to help beginners enter the field. Most parts are written as self-contained units and every new concept or calculation is explained in detail without assuming prior knowledge of the subject. The book significantly enhances and revises a Japanese version which is a bestseller in the Japanese market and is considered a standard textbook in the field. It contains new pedagogical presentations of field theory methods, including a chapter on conformal field theory, and various modern developments hard to find in a single textbook on phase transitions. Exercises are presented as the topics develop, with solutions found at the end of the book, making the text useful for self-teaching, as well as for classroom learning.
This book introduces a variety of neural network methods for solving differential equations arising in science and engineering. The emphasis is placed on a deep understanding of the neural network techniques, which has been presented in a mostly heuristic and intuitive manner. This approach will enable the reader to understand the working, efficiency and shortcomings of each neural network technique for solving differential equations. The objective of this book is to provide the reader with a sound understanding of the foundations of neural networks and a comprehensive introduction to neural network methods for solving differential equations together with recent developments in the techniques and their applications. The book comprises four major sections. Section I consists of a brief overview of differential equations and the relevant physical problems arising in science and engineering. Section II illustrates the history of neural networks starting from their beginnings in the 1940s through to the renewed interest of the 1980s. A general introduction to neural networks and learning technologies is presented in Section III. This section also includes the description of the multilayer perceptron and its learning methods. In Section IV, the different neural network methods for solving differential equations are introduced, including discussion of the most recent developments in the field. Advanced students and researchers in mathematics, computer science and various disciplines in science and engineering will find this book a valuable reference source.