The brain is the most complex computational machine known to science, even though its components (neurons) are slow and unreliable compared to a laptop computer.
In this richly illustrated book, Shannon's mathematical theory of information is used to explore the metabolic efficiency of neurons, with special reference to visual perception.
Evidence from a diverse range of research papers is used to show how information theory defines absolute limits on neural efficiency; limits which ultimately determine the neuroanatomical microstructure of the eye and brain.
Written in an informal style, with a comprehensive glossary, tutorial appendices, explainer boxes, and a list of annotated Further Readings, this book is an ideal introduction to cutting-edge research in neural information theory.
Tutorial Introductions Principles of neural information theory: computational neuroscience and metabolic efficiency, hardcover/james v. stone
