Synopses & Reviews
Neuroscience research has exploded, with more than fifty thousand neuroscientists applying increasingly advanced methods. A mountain of new facts and mechanisms has emerged. And yet a principled framework to organize this knowledge has been missing. In this book, Peter Sterling and Simon Laughlin, two leading neuroscientists, strive to fill this gap, outlining a set of organizing principles to explain the whys of neural design that allow the brain to compute so efficiently.
Setting out to "reverse engineer" the brain -- disassembling it to understand it -- Sterling and Laughlin first consider why an animal should need a brain, tracing computational abilities from bacterium to protozoan to worm. They examine bigger brains and the advantages of "anticipatory regulation"; identify constraints on neural design and the need to "nanofy"; and demonstrate the routes to efficiency in an integrated molecular system, phototransduction. They show that the principles of neural design at finer scales and lower levels apply at larger scales and higher levels; describe neural wiring efficiency; and discuss learning as a principle of biological design that includes "save only what is needed."
Sterling and Laughlin avoid speculation about how the brain might work and endeavor to make sense of what is already known. Their distinctive contribution is to gather a coherent set of basic rules and exemplify them across spatial and functional scales.
Review
Time, space, energy, and information: these are the key themes of this fascinating book, which takes the spirit of the Feynman Lectures on Physics and applies it to explain how the brain has been designed, by evolution, to process information efficiently. Unique insights, recounted in the authors' characteristically appealing style, are to be found on every page. The MIT Press
Review
This is not your typical neuroscience textbook. Rather than catalogue processes and structures of the central nervous system, Sterling and Laughlin take a unique approach to interpreting the brain. They consider the general principles that have shaped brain design through natural selection, principles that make the human brain 10^5 times more efficient than the most powerful computers. Chapters examine efficient encoding of information, layout of brain circuits, and strategies for learning and memory. This overview of brain function is refreshing and insightful. David Attwell, Jodrell Professor of Physiology, University College London
Review
Drawing on their areas of expertise, Sterling and Laughlin have written a beautiful book addressing some simple questions about how the brain works, enriching the reader with many 'aha' moments. This transformative book brings us closer to understanding the logic that nature could be using in its design of neural circuits. And, in fact, perhaps the biggest impression from reading the book is a renewed awe for the incredible work that nature has done with nervous systems, which must be the crowning achievement of evolution. I cannot wait to use it as textbook in my course on neural circuits. Eric A. Newman, Distinguished McKnight University Professor of Neuroscience, University of Minnesota
Synopsis
Two distinguished neuroscientists distil general principles from more than a century of scientific study, "reverse engineering" the brain to understand its design.
Neuroscience research has exploded, with more than fifty thousand neuroscientists applying increasingly advanced methods. A mountain of new facts and mechanisms has emerged. And yet a principled framework to organize this knowledge has been missing. In this book, Peter Sterling and Simon Laughlin, two leading neuroscientists, strive to fill this gap, outlining a set of organizing principles to explain the whys of neural design that allow the brain to compute so efficiently.
Setting out to "reverse engineer" the brain -- disassembling it to understand it -- Sterling and Laughlin first consider why an animal should need a brain, tracing computational abilities from bacterium to protozoan to worm. They examine bigger brains and the advantages of "anticipatory regulation"; identify constraints on neural design and the need to "nanofy"; and demonstrate the routes to efficiency in an integrated molecular system, phototransduction. They show that the principles of neural design at finer scales and lower levels apply at larger scales and higher levels; describe neural wiring efficiency; and discuss learning as a principle of biological design that includes "save only what is needed."
Sterling and Laughlin avoid speculation about how the brain might work and endeavor to make sense of what is already known. Their distinctive contribution is to gather a coherent set of basic rules and exemplify them across spatial and functional scales.
About the Author
Peter Sterling is Professor of Neuroscience at the University of Pennsylvania School of Medicine. Simon Laughlin is Professor of Neurobiology in the Department of Zoology at the University of Cambridge and a Fellow of the Royal Society.