The Brain's Sense of Movement.

TLDR: Alain Berthoz takes the reader on a whirlwind tour of cognitive neuroscience topics: perception, coherence, memory, prediction, and adaptation, and builds a persuasive case supporting his thesis that the brain is an anticipation machine.

Abstract: The Brain's Sense of Movement. By Alain Berthoz (Translated by Giselle Weiss). Cambridge, Massachusetts: Harvard University Press; 2000, 352 pp. $22.80. Ever wonder how certain people catch or bat a baseball hurled at blurring speeds? If you have, find yourself in a group whose intended or accidental success maybe a machine that pitches and throws like a ballplayer. Once this group of researchers articulates an accurate set of principles behind movement, deft engineering, persistence, and luck may converge to emulate nature. Although Berthoz's The Brain's Sense ofMovement, does not offer a science-fiction glimpse of agile androids that populate Asimov's novels, it provides an organized and fascinating way of thinking about movement. Berthoz takes the reader on a whirlwind tour of cognitive neuroscience topics: perception, coherence, memory, prediction, and adaptation. By examining these topics and using choice examples, Berthoz builds a persuasive case supporting his thesis that the brain is an anticipation machine. Even before delving into the intricacies of each of these topics, Berthoz's claim seems reasonable in light of evolution. In fact, Berthoz explains how evolution and improved neural systems that guide movement influence and drive each other: \"The species that passed the test of natural selection are those that figured out how to save a few milliseconds in capturing prey and anticipating the actions of predators, those whose brains were able to simulate the elements of the environment and choose the best way home, those able to memorize great quantities of information from past experience and use them in the heat of action.\" This cat and mouse games has honed the brain to take advantage of its parallel architecture, bypassing computing each trajectory in a Newtonian sense, and arriving at a solution by using heuristics developed over evolution. Heuristics play an important role in examples where a target exceeds physical limits of detection. For example, a baseball may move too quickly for the fovea to focus, however, the brain, and skeletal-muscular system use computational shortcuts to simulate, predict, adapt, and control the body in response to a changing environment. The first choice example that Berthoz highlights as a key computational shortcut is the derivative. Signals from receptors enable anticipation of future position of the head owing to their sensitivity to derivatives such as jerk, acceleration, and velocity. Another mathematical concept that Berthoz explores as a predictive tool is tensors. From what I learned, a tensor is a group of mathematical operators called matrices that carry out transformations among vectors. Between derivatives and vectors, Berthoz devotes several chapters to explaining how otoliths and semicircular canals use derivatives for linear and angular accelerations to predict while tensors receive perfunctory treatment. A balance between these two topics may better satisfy some readers. Certainly, derivatives and tensors alone cannot account for movement. Just as a calculator or computer derives its usefulness in a network, mathematical shortcuts for movement need to occur in the context of a circuit. Reading Berthoz's