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 book is divided into three parts. Part I discusses the relationship between sensory stimuli and neural responses, focusing on the representation of information by the spiking activity of neurons. Part II discusses the modeling of neurons and neural circuits on the basis of cellular and synaptic biophysics. Part III analyzes the role of plasticity in development and learning. An appendix covers the mathematical methods used, and exercises are available on the book's Web site.
About the Authors
Peter Dayan is Professor and Director of the Gatsby Computational Neuroscience Unit at University College London.
Larry Abbott is Professor of Neuroscience and Co-Director of the Center for Theoretical Neuroscience at Columbia University.
"It will not be surprising if this book becomes the standard text for students and researchers entering theoretical neuroscience for years to come."—M. Brandon Westover, Philosophical Psychology
"Not only does the book set a high standard for theoretical neuroscience, it defines the field."—Dmitri Chklovskii, Neuron