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.

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This textbook is an introduction to systems and computational neuroscience with a special focus on cognition. It consists of three parts: Part I covers basic concepts and mathematical models of computational neuroscience, as well as cutting-edge topics. Part II is dedicated to building blocks of cognition: working memory (how our brain maintains and manipulates information “online” in the absence of any external input), decision making (how a choice is selected among multiple options under uncertainty and risk) and behavioral flexibility (how we direct our attention and control our actions). In Part III, frontier research is discussed: models of large-scale multi-regional brain systems, computational psychiatry, interface with artificial intelligence. The author emphasizes the viewpoint of neural circuits as dynamical systems, and cross-level (from genes and cell types to collective neural populations to behavior) mechanistic understanding of the brain and the mind. Taken together, a reader is offered the opportunity to become well versed in this highly cross-disciplinary 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