Memory, attention, and decision-making are three major areas of psychology. They are frequently studied in isolation, and using a range of models to understand them. This book brings a unified approach to understanding these three processes. It shows how these fundamental functions forcognitive neuroscience can be understood in a common and unifying computational neuroscience framework. This framework links empirical research on brain function from neurophysiology, functional neuroimaging, and the effects of brain damage, to a description of how neural networks in the brainimplement these functions using a set of common principles. The book describes the principles of operation of these networks, and how they could implement such important functions as memory, attention, and decision-making.The topics covered includeThe hippocampus and memoryReward and punishment related learning: emotion and motivationVisual object recognition learningShort term memoryAttention, short term memory, and biased competitionProbabilistic decision-makingAction selectionDecision-makingAlso included are tutorial appendices onNeural networks in the brainNeural encoding in the brain'Memory, Attention and Decision-Making' will be valuable for those in the fields of neuroscience, psychology, and cognitive neuroscience from advanced undergraduate level upwards. It will also be of interest to those interested in neuroeconomics, animal behaviour, zoology, evolutionary biology,psychiatry, medicine, and philosophy. The book has been written with modular chapters and sections, making it possible to select particular Chapters for course work.

This volume discusses a variety of preclinical MRI methods and protocols to help technicians and researchers conduct studies in their respective fields. This book is organized into 7 parts: Part 1 covers the basics of MRI physics, relaxation, image contrast, and main acquisition sequences; Part 2 describes methodologies for diffusion, perfusion, and functional imaging; Part 3 looks at in vivo spectroscopy; Part 4 explores special MRI techniques that are less known in the field; Parts 5 and 6 discuss MRIs and MRSs in animal models of disease and the applications used to study them, and Part 7 looks at anesthesia and advanced contrast agents. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Comprehensive and thorough, Preclinical MRI: Methods and Protocols is a valuable resource for researchers interested in expanding their knowledge in this developing field.

What produces emotions? Why do we have emotions? How do we have emotions? Why do emotional states feel like something? What is the relation between emotion, and reward value, and subjective feelings of pleasure? These are just some of the question considered in this book, written by a leading neuroscientist in this field.

The activity of neurons in the brain is noisy in that the neuronal firing times are random for a given mean rate. The Noisy Brain shows that this is fundamental to understanding many aspects of brain function, including probabilistic decision-making, perception, memory recall, short-term memory, attention, and even creativity. There are many applications too of this understanding, to for example memory and attentional disorders, aging, schizophrenia, and obsessive-compulsive disorder.

This book describes the types of computation that can be performed by biologically plausible neural networks and shows how they may be implemented in different systems of the brain. It is structured in three sections, each of which addresses a different need. The first introduces and analyzes the operation of several fundamental types of neural networks. The second discusses real neural networks in several brain systems, and shows how it is becoming possible to construct theories about the way different parts of the brain work. This section also analyzes the various neuroscience and neurocomputation techniques that need to be combined to ensure further progress in understanding the mechanism of brain processes. The third section, a collection of appendices. introduces the formal quantitative approaches to many of the networks described. Neural Networks and Brain Function is an accessible, clear introduction for researchers and students in neuroscience and artificial intelligence to the fascinating problems of how the brain works and how behavior is determined.

This cutting-edge book offers a theoretical account of the evolution of multiple memory systems of the brain. The authors conceptualize these memory systems from both behavioral and neurobiological perspectives, guided by three related principles. First, that our understanding of a wide range of memory phenomena can be advanced by breaking down memory into multiple forms with different operating characteristics. Second, that different forms of memory representation are supported by distinct brain pathways with circuitry and neural coding properties. Third, that the contributions of different brain systems can be compared and contrasted by distinguishing between dedicated (or specific) and elaborate (or general) memory systems. A primary goal of this work is to relate the neurobiological properties of dedicated and elaborate systems to their neuropsychological counterparts, and in so doing, account for the phenomenology of memory, from conditioning to conscious recollection.