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Neuroscience

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Studies in Neurophilosophy

Progress in the neurosciences is profoundly changing our conception of ourselves. Contrary to time-honored intuition, the mind turns out to be a complex of brain functions. And contrary to the wishful thinking of some philosophers, there is no stemming the revolutionary impact that brain research will have on our understanding of how the mind works.

Computation, Representation, and Dynamics in Neurobiological Systems

For years, researchers have used the theoretical tools of engineering to understand neural systems, but much of this work has been conducted in relative isolation. In Neural Engineering, Chris Eliasmith and Charles Anderson provide a synthesis of the disparate approaches current in computational neuroscience, incorporating ideas from neural coding, neural computation, physiology, communications theory, control theory, dynamics, and probability theory. This synthesis, they argue, enables novel theoretical and practical insights into the functioning of neural systems.

Selected Readings in the Philosophy of Perception

The philosophy of perception is a microcosm of the metaphysics of mind. Its central problems—What is perception? What is the nature of perceptual consciousness? How can one fit an account of perceptual experience into a broader account of the nature of the mind and the world?—are at the heart of metaphysics. Rather than try to cover all of the many strands in the philosophy of perception, this book focuses on a particular orthodoxy about the nature of visual perception.

This popular behavioral endocrinology text provides detailed information on what hormones are, how they affect cells, and how such effects can alter the behavior of animals, including humans. Presenting a broad continuum of levels of analysis, from molecular to evolutionary, the book discusses how genes work, the structure of cells, the interactions of endocrine organs, the behavior of individuals, the structure of social hierarchies, and the evolution of mating systems.

Computational and Mathematical Modeling of Neural Systems

Theoretical neuroscience provides a quantitative basis for describing what nervous systems do, determining how they function, and uncovering the general principles by which they operate. This text introduces the basic mathematical and computational methods of theoretical neuroscience and presents applications in a variety of areas including vision, sensory-motor integration, development, learning, and memory.

The Machine Learning Approach

An unprecedented wealth of data is being generated by genome sequencing projects and other experimental efforts to determine the structure and function of biological molecules. The demands and opportunities for interpreting these data are expanding rapidly. Bioinformatics is the development and application of computer methods for management, analysis, interpretation, and prediction, as well as for the design of experiments.

An Introduction to Neural Network Modeling of the Hippocampus and Learning

This book is for students and researchers who have a specific interest in learning and memory and want to understand how computational models can be integrated into experimental research on the hippocampus and learning. It emphasizes the function of brain structures as they give rise to behavior, rather than the molecular or neuronal details. It also emphasizes the process of modeling, rather than the mathematical details of the models themselves.

Understanding the Mind by Simulating the Brain

The goal of computational cognitive neuroscience is to understand how the brain embodies the mind by using biologically based computational models comprising networks of neuronlike units. This text, based on a course taught by Randall O'Reilly and Yuko Munakata over the past several years, provides an in-depth introduction to the main ideas in the field. The neural units in the simulations use equations based directly on the ion channels that govern the behavior of real neurons, and the neural networks incorporate anatomical and physiological properties of the neocortex.

An Algorithmic Approach

In one of the first major texts in the emerging field of computational molecular biology, Pavel Pevzner covers a broad range of algorithmic and combinatorial topics and shows how they are connected to molecular biology and to biotechnology. The book has a substantial "computational biology without formulas" component that presents the biological and computational ideas in a relatively simple manner. This makes the material accessible to computer scientists without biological training, as well as to biologists with limited background in computer science.

The Philosophy and Biology of Cognitive Ethology

The authors of this book, a philosopher and a cognitive ethologist, approach their work from the perspective that many animals have minds and rich cognitive lives. They also believe that arguments about evolutionary continuity are as applicable to the study of animal minds and brains as they are to comparative studies of kidneys, stomachs, and hearts. Cognitive ethologists study the comparative, evolutionary, and ecological aspects of the mental phenomena of animals.

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