Peter Sterling – författare

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.

An argument that health is optimal responsiveness and is often best treated at the system level.

Medical education centers on the venerable “no-fault” concept of homeostasis, whereby local mechanisms impose constancy by correcting errors, and the brain serves mainly for emergencies. Yet, it turns out that most parameters are not constant; moreover, despite the importance of local mechanisms, the brain is definitely in charge. In this book, the eminent neuroscientist Peter Sterling describes a broader concept: allostasis (coined by Sterling and Joseph Eyer in the 1980s), whereby the brain anticipates needs and efficiently mobilizes supplies to prevent errors.

Allostasis evolved early, Sterling explains, to optimize energy efficiency, relying heavily on brain circuits that deliver a brief reward for each positive surprise. Modern life so reduces the opportunities for surprise that we are driven to seek it in consumption: bigger burgers, more opioids, and innumerable activities that involve higher carbon emissions. The consequences include addiction, obesity, type 2 diabetes, and climate change. Sterling concludes that solutions must go beyond the merely technical to restore possibilities for daily small rewards and revivify the capacities for egalitarianism that were hard-wired into our nature.

Sterling explains that allostasis offers what is not found in any medical textbook: principled definitions of health and disease: health as the capacity for adaptive variation and disease as shrinkage of that capacity. Sterling argues that since health is optimal responsiveness, many significant conditions are best treated at the system level.

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.