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A Historical Introduction

This introduction to neuroscience is unique in its emphasis on how we know what we know about the structure and function of the nervous system. What are the observations and experiments that have taught us about the brain and spinal cord?

From Laboratory to Theory

Vision is one of the most active areas in biomedical research, and visual psychophysical techniques are a foundational methodology for this research enterprise. Visual psychophysics, which studies the relationship between the physical world and human behavior, is a classical field of study that has widespread applications in modern vision science. Bridging the gap between theory and practice, this textbook provides a comprehensive treatment of visual psychophysics, teaching not only basic techniques but also sophisticated data analysis methodologies and theoretical approaches.

How We Perceive the World

In this accessible and engaging introduction to modern vision science, James Stone uses visual illusions to explore how the brain sees the world. Understanding vision, Stone argues, is not simply a question of knowing which neurons respond to particular visual features, but also requires a computational theory of vision.

An Introduction with Readings
Edited by Martha J. Farah

Neuroscience increasingly allows us to explain, predict, and even control aspects of human behavior. The ethical issues that arise from these developments extend beyond the boundaries of conventional bioethics into philosophy of mind, psychology, theology, public policy, and the law. This broader set of concerns is the subject matter of neuroethics.

The Computational Approach to Biological Vision

Seeing has puzzled scientists and philosophers for centuries and continues to do so. This new edition of a classic text offers an accessible but rigorous introduction to the computational approach to understanding biological visual systems.

This essential resource on neuroimaging provides an accessible and user-friendly introduction to the field written by leading researchers. The book describes theoretical and methodological developments in the use of functional neuroimaging techniques to study the neural basis of cognition, from early scientific efforts to link brain and behavior to the latest applications of fMRI and PET methods. The core of the book covers fMRI and PET studies in specific domains: attention, skill learning, semantic memory, language, episodic memory, working memory, and executive functions.

The event-related potential (ERP) technique in cognitive neuroscience allows scientists to observe human brain activity that reflects specific cognitive processes. In An Introduction to the Event-Related Potential Technique, Steve Luck offers the first comprehensive guide to the practicalities of conducting ERP experiments in cognitive neuroscience and related fields, including affective neuroscience and experimental psychopathology.

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.

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.

This introductory text offers a clear exposition of the algorithmic principles driving advances in bioinformatics. Accessible to students in both biology and computer science, it strikes a unique balance between rigorous mathematics and practical techniques, emphasizing the ideas underlying algorithms rather than offering a collection of apparently unrelated problems.

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