title: Dyslexic and category-specific aphasic impairments in a self-organizing feature map model of the lexicon.
abstract: DISLEX is an artificial neural network model of the mental lexicon. It was built to test computationally whether the lexicon could consist of separate feature maps for the different lexical modalities and the lexical semantics, connected with ordered pathways. In the model, the orthographic, phonological, and semantic feature maps and the associations between them are formed in an unsupervised process, based on cooccurrence of the lexical symbol and its meaning. After the model is organized, various damage to the lexical system can be simulated, resulting in dyslexic and category-specific aphasic impairments similar to those observed in human patients.
authors.affiliation: Department of Computer Sciences, University off Texas at Austin 78712, USA. risto@cs.utexas.edu
authors.forename: R
authors.initials: R
authors.lastname: Mikkulainen
mesh_terms: D001037:Aphasia / Q000503:physiopathology*; D001921:Brain / Q000503:physiopathology*; D004410:Dyslexia / Q000503:physiopathology*; D006801:Humans; D009415:Nerve Net / Q000503:physiopathology*; D009434:Neural Pathways / Q000503:physiopathology; D012660:Semantics; D014825:Vocabulary