A Biologically Plausible SOM Representation of the Orthographic Form of 50,000 French Words

Abstract

Abstract. Recently, an important aspect of human visual word recognition has been characterized. The letter position is encoded in our brain using an explicit representation of order based on letter pairs: the openbigram coding [15]. We hypothesize that spelling has evolved in order to minimize reading errors. Therefore, word recognition using bigramsinstead of letters -should be more efficient. First, we study the influence of the size of the neighborhood, which defines the number of bigrams per word, on the performance of the matching between bigrams and word. Our tests are conducted against one of the best recognition solutions used today by the industry, which matches letters to words. Secondly, we build a cortical map representation of the words in the bigram space -which implies numerous experiments in order to achieve a satisfactory projection. Third, we develop an ultra-fast version of the self-organizing map in order to achieve learning in minutes instead of months.

The Theory of Neural Cognition Applied to Robotics

“…Its neural organization has been modelled by Dehaene (in 2005 [18]) and others [19–20]. The model (Figure 4) involves six cortical maps, starting with the oriented edges of the primary visual cortex and moving up to letters, bigrams (i.e., pairs of letters [21]) and words. Reading is acquired at age five, and the reader's expertise depends on the regularity of the language.…”