Simulating brain damage.

In 1944 a young soldier suÝered a bullet wound to the head. He survived the war with a strange disability: although he could read and comprehend some words with ease, many others gave him trouble. He read the word antique as ÒvaseÓ and uncle as Ònephew.Ó The injury was devastating to the patient, G.R., but it provided invaluable information to researchers investigating the mechanisms by which the brain comprehends written language. A properly functioning system for converting letters on a page to spoken sounds reveals little of its inner structure, but when that system is disrupted, the peculiar pattern of the resulting dysfunction may oÝer essential clues to the original, undamaged architecture. During the past few years, computer simulations of brain function have advanced to the point where they can be used to model information-processing pathways. We have found that deliberate damage to artiÞcial systems can mimic the symptoms displayed by people who have sustained brain injury. Indeed, building a model that makes the same errors as brain-injured people do gives us conÞdence that we are on the right track in trying to understand how the brain works. We have yet to make computer models that exhibit even a tiny fraction of the capabilities of the human brain. Nevertheless, our results so far have produced unexpected insights into the way the brain transforms a string of letter shapes into the meaning of a word. When John C. Marshall and Freda Newcombe of the University of Oxford analyzed G.R.Õs residual problems in 1966, they found a highly idiosyncratic pattern of reading deÞcits. In addition to his many semantic errors, G.R. made visual ones, reading stock as ÒshockÓ and crowd as Òcrown.Ó Many of his misreadings resembled the correct word in both form and meaning; for example, he saw wise and said Òwisdom.Ó Detailed testing showed that G.R. could read concrete words, such as table, much more easily than abstract words, such as truth. He was fair at reading nouns (46 percent correct), worse at adjectives (16 percent), still worse at verbs (6 percent) and worst of all at