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 include The hippocampus and memory Reward and punishment related learning: emotion and motivation Visual object recognition learning Short term memory Attention, short term memory, and biased competition Probabilistic decision-making Action selection Decision-making Also included are tutorial appendices on Neural networks in the brain Neural 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.

Reviews the most intriguing applications of fractal analysis in neuroscience with a focus on current and future potential, limits, advantages, and disadvantages. Will bring an understanding of fractals to clinicians and researchers also if they do not have a mathematical background, and will serve as a good tool for teaching the translational applications of computational models to students and scholars of different disciplines. This comprehensive collection is organized in four parts:
(1) Basics of fractal analysis;
(2) Applications of fractals to the basic neurosciences;
(3) Applications of fractals to the clinical neurosciences;
(4) Analysis software, modeling and methodology.
Series: Springer Series in Computational Neuroscience

"Simulation," writes Gary Flake in his preface, "becomes a form of experimentation in a universe of theories. The primary purpose of this book is to celebrate this fact."In this book, Gary William Flake develops in depth the simple idea that recurrent rules can produce rich and complicated behaviors. Distinguishing "agents" (e.g., molecules, cells, animals, and species) from their interactions (e.g., chemical reactions, immune system responses, sexual reproduction, and evolution), Flake argues that it is the computational properties of interactions that account for much of what we think of as "beautiful" and "interesting." From this basic thesis, Flake explores what he considers to be today's four most interesting computational topics: fractals, chaos, complex systems, and adaptation.Each of the book's parts can be read independently, enabling even the casual reader to understand and work with the basic equations and programs. Yet the parts are bound together by the theme of the computer as a laboratory and a metaphor for understanding the universe. The inspired reader will experiment further with the ideas presented to create fractal landscapes, chaotic systems, artificial life forms, genetic algorithms, and artificial neural networks.

美国能源部计算生物学项目数学科学研究委员会、美国国家学术院国家研究委员会编著的《数学与21世纪生物学》是美国数学和生物学界各领域科学家联合开展研究的重要成果。书中全面总结了近年来数学生物学的研究现状和研究动态，前瞻性地提出了数学与生物学的交叉学科前沿的发展趋势与未来研究方向。本书对于我国数学生物学领域的科研人员、高校师生、科技管理者、政府科研投资决策者洞悉数学生物学科学发展规律、了解数学生物学前沿领域和重点方向及开展科技创新等有重要的参考价值。