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Updated: Jun 28, 2026

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
Published on: June 25, 2019
Two semantic systems in the brain for rapid and slow differentiation of abstract and concrete words
I R Il'yuchenok1, O V Sysoeva, A M Ivanitskii
1Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Moscow, Russia. inrosil@mail.ru
Abstract:
Most studies of semantic processing address changes in the late (300-800 msec) components of evoked potentials. However, recent years have seen the appearance of data showing that humans can perceive the sense of stimuli presented to them in significantly shorter periods of time. We report here studies of the mechanism of semantic analysis of written abstract and concrete words in four series of experiments: 1) reading of words on a monitor screen; 2) simple classification of all presented words into the categories "abstract" and "concrete;" 3) complex, i.e., selective classification of words written only in a specified color with a prompt as to which color would be used for the word; 4) complex classification of words of only a specified color without a prior prompt. Early (40-100 msec) differences in evoked brain potentials were seen on comparison of responses to abstract and concrete words, predominantly in the frontal areas in the case of simple reading of words and in the more dorsal areas in the case of tasks with simple classification. All cases of explicit classification of words were characterized by differences in late (450-700 msec) components in the left frontal zone. The results indicate the existence of two semantic systems: a rapid, implicit system associated with activation of the right frontal area, and a slow, explicit system of word classification which is predominantly associated with activity in the left frontal area. The relationship between the two systems is to a certain extent reciprocal: the rapid system can by inhibited by introduction of a word classification task.
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