Memory, Attention, and Decision-Making : A Unifying Computational Neuroscience Approach

Memory, attention, and decision-making are three major areas of cognitive neuroscience. They are however frequently studied in isolation, using a range of models to understand them. This book brings a unified approach to understanding these three processes, showing how these fundamental functions can be understood in a common and unifying framework.

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 for cognitive 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 brain implement 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.