Theoretical Neuroscience

This textbook synthesizes neuroscience and cognitive science. Cognition and intelligence arise from neural circuits endowed with many feedback loops, which is difficult to understand by intuition alone. The book covers basic computational neuroscience required for discussions of brain mechanisms and computational principles of cognition. This textbook is an introduction to Systems and Theoretical/Computational Neuroscience, with a particular emphasis on cognition. It consists of three parts: Part I covers fundamental concepts and mathematical models in computational neuroscience, along with cutting-edge topics. Part II explores the building blocks of cognition, including working memory (how the brain maintains and manipulates information "online" without external input), decision making (how choices are made among multiple options under conditions of uncertainty and risk) and behavioral flexibility (how we direct attention and control actions). Part III is dedicated to frontier research, covering models of large-scale multi-regional brain systems, Computational Psychiatry and the interface with Artificial Intelligence. The author highlights the perspective of neural circuits as dynamical systems, and emphasizes a cross-level mechanistic understanding of the brain and mind, from genes and cell types to collective neural populations and behavior. Overall, this textbook provides an opportunity for readers to become well versed in this highly interdisciplinary field of the twenty-first century. Key Features Rooted in the most recent advances in experimental studies of basic cognitive functions Introduces neurobiological and mathematical concepts so that the book is self-contained Heavily illustrated with high-quality figures that help to illuminate neurobiological concepts, present experimental findings and explain mathematical models Concludes with a list of core cognitive behavior tasks, ten take-home messages and three open questions for future research Computer model codes are available via GitHub for hands-on practice ()