The structure of mental representations: text extraction from memory, neural network and artificial intelligence

The paper explicates the problem of human mental lexicon organization in the aspect of the connectionist approach. It is substantiated that knowledge representation in human brain is based on a specific neural network and a particular brain structure. Present viewpoints on the structure and nature of knowledge “units” are analysed and a conception of their functioning is thus set forth. In this regard, the problem of extraction of text as a whole psycho-linguistic organization is discussed and the model of the text extraction from long-term memory is described. The paper also hypothesizes that the associative-semantic network principle plays a key role in the formation of human mental space. Based upon the data available, the author develops a methodology of modeling structures of knowledge representation in the systems of artificial intelligence.