This book deals with information theory, a new and expanding area of neuroscience which provides a framework for understanding neuronal processing.

Arousal is fundamental to all cognition. It is intuitively obvious, absolutely necessary, but what exactly is it? In Brain Arousal and Information Theory, Donald Pfaff presents a daring perspective on this long-standing puzzle. Pfaff argues that, beneath our mental functions and emotional dispositions, a primitive neuronal system governs arousal. Employing the simple but powerful framework of information theory, Pfaff revolutionizes our understanding of arousal systems in the brain. Starting with a review of the neuroanatomical, neurophysiological, and neurochemical components of arousal, Pfaff asks us to look at the gene networks and neural pathways underlying the brain's arousal systems much as a design engineer would contemplate information systems. This allows Pfaff to postulate that there is a bilaterally symmetric, bipolar system universal among mammals that readies the animal or the human being to respond to stimuli, initiate voluntary locomotion, and react to emotional challenges. Applying his hypothesis to heightened states of arousal--sex and fear--Pfaff shows us how his theory opens new scientific approaches to understanding the structure of brain arousal. A major synthesis of disparate data by a preeminent neuroscientist, Brain Arousal and Information Theory challenges current thinking about cognition and behavior. Whether you subscribe to Pfaff's theory or not, this book will stimulate debate about the nature of arousal itself.

Hardbound. The present collection of papers focuses on the subject of vision. The papers bring together new insights and facts from various branches of experimental and theoretical neuroscience. The experimental facts presented in the volume stem from disparate fields, such as neuroanatomy, electrophysiology, optical imaging and psychophysics. The theoretical models in part are unsophisticated, yet still inspiring, while others skilfully apply advanced mathematical reasoning to results of experimental measurements. The book is the fifth in a series of volumes intending to define a theory of the brain by bringing together formal reasoning and experimental facts. The reader is thus being introduced to a new kind of brain science, where facts and theory are beginning to blend together.

In this richly illustrated book, it is shown how Shannon's mathematical theory of information defines absolute limits on neural efficiency; limits which ultimately determine the neuroanatomical microstructure of the eye and brain. Written in an informal style this is an ideal introduction to cutting-edge research in neural information theory.

The human brain is made up of 85 billion neurons, which are connected by over 100 trillion synapses. For more than a century, a diverse array of researchers searched for a language that could be used to capture the essence of what these neurons do and how they communicate – and how those communications create thoughts, perceptions and actions. The language they were looking for was mathematics, and we would not be able to understand the brain as we do today without it. In Models of the Mind, author and computational neuroscientist Grace Lindsay explains how mathematical models have allowed scientists to understand and describe many of the brain's processes, including decision-making, sensory processing, quantifying memory, and more. She introduces readers to the most important concepts in modern neuroscience, and highlights the tensions that arise when the abstract world of mathematical modelling collides with the messy details of biology. Each chapter of Models of the Mind focuses on mathematical tools that have been applied in a particular area of neuroscience, progressing from the simplest building block of the brain – the individual neuron – through to circuits of interacting neurons, whole brain areas and even the behaviours that brains command. In addition, Grace examines the history of the field, starting with experiments done on frog legs in the late eighteenth century and building to the large models of artificial neural networks that form the basis of modern artificial intelligence. Throughout, she reveals the value of using the elegant language of mathematics to describe the machinery of neuroscience.

A coherent and comprehensive theory of visual pattern classification with quantitative models, verifiable predictions and extensive empirical evidence.

Originally developed by Claude Shannon in the 1940s, information theory laid the foundations for the digital revolution, and is now an essential tool in telecommunications, genetics, linguistics, brain sciences, and deep space communication. In this richly illustrated book, accessible examples are used to introduce information theory in terms of everyday games like ‘20 questions’ before more advanced topics are explored. Online MatLab and Python computer programs provide hands-on experience of information theory in action, and PowerPoint slides give support for teaching. Written in an informal style, with a comprehensive glossary and tutorial appendices, this text is an ideal primer for novices who wish to learn the essential principles and applications of information theory.

Scientific knowledge grows at a phenomenal pace--but few books have had as lasting an impact or played as important a role in our modern world as The Mathematical Theory of Communication, published originally as a paper on communication theory more than fifty years ago. Republished in book form shortly thereafter, it has since gone through four hardcover and sixteen paperback printings. It is a revolutionary work, astounding in its foresight and contemporaneity. The University of Illinois Press is pleased and honored to issue this commemorative reprinting of a classic.

The book was written as an attempt to find the solution to one of the most complex and unsolved issues of the human anatomy: the understanding of the human brain and the principles according to which it operates. Currently, it is important to look at the challenge in an alternatively non-standard, yet still systemic way, paying less attention to details and outlining the ways out of this crisis of neuroscience. The purpose of this monograph is to describe the author's theory about the brain's architecture and operation to the medical and scientific community. Accompanied with extensive clinical, research and training experience, the author's theoretical concepts of the brain synthesized with scientific evidence brought about the conclusion that low efficiency in neurologic therapy and mental diseases; the inability to work out mathematical models and simulations that could compete with the human brain; an academic dead end in the development of artificial intelligence; as well as high energy consumption of the computing innovations were conditioned by the inaccurate methodology and outdated anatomical and physiological views of the neurologists and neuroscientists on information processing in the brain, registration of memories and basic functions of the key morphological structures of the brain. The morphological structure and physiological functions of all known anatomical formations of the brain were defined in the late nineteenth century. Since then, these functions have been accepted as dogmatic. The book shows that present day multi-level neuroresearch relies on the foundation of systemic, morphofunctional and neuroanatomic knowledge about the brain structure. It looks for correlations between genome and post-genome data of molecular research in the brain tissue, as well as with neuropsychological and cognitive data; that is, the book intends to integrate the non-integrable into unified information space. The systemic approach in neuroresearch has become outdated by now and interferes with scientific development. The information approach in the author's research of the genome, transcriptome, proteome in health and in disease permitted the analysis of the inductivity and magnetization of the nervous tissue. It also provided the explanation for targeted movement of the data in the module of the nervous tissue. The author came to the conclusion that gene, protein and neural networks "confused and chained" the pathways of scientific thought. Neural networks are only logistic constructions to provide data transfer in the brain between different modules of the nervous tissue. The author presumes that the funds invested in the development of brain simulations and artificial intelligence will hardly result in the expected advantages. If we are unable to step over the stereotypes of the systemic, morphofunctional research of the previous century, no progress shall come about. The author's theoretical survey resulted in the unique information-commutation theory of the brain and formulation of the key principles of brain operation. As a clinician and professor of neurology, the author underpins his theory with clinical examples. This book presents the framework of the ideas that require experimental research and proof.

Philosophy has long puzzled over the relation between mind and brain. This volume presents some of the state-of-the-art reflections on philosophical efforts to 'make sense' of neuroscience, as regards issue including neuroaesthetics, brain science and the law, neurofeminism, embodiment, race, memory and pain.