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Neurons in the feature areas are implemented as Wilson-Cowan oscillators, to allow segmentation of different simultaneous objects via gamma-band synchronization. Excitatory synapses among neurons in the feature and lexical areas are learned, during a training phase, via a Hebbian rule. In this work, we first assume that some words in the first language (L1) and the corresponding object representations are initially learned during a preliminary training phase. Subsequently, second-language (L2) words are learned by simultaneously presenting the new word together with the L1 one. A competitive mechanism between the two words is also implemented by the use of inhibitory interneurons. Simulations show that, after a weak training, the L2 word allows retrieval of the object properties but requires engagement of the first language. Conversely, after a prolonged training, the L2 word becomes able to retrieve object per se. In this case, a conflict between words can occur, requiring a higher-level decision mechanism.<\/jats:p>","DOI":"10.1155\/2010\/350269","type":"journal-article","created":{"date-parts":[[2010,3,1]],"date-time":"2010-03-01T15:29:00Z","timestamp":1267457340000},"page":"1-10","source":"Crossref","is-referenced-by-count":2,"title":["A Semantic Model to Study Neural Organization of Language in Bilingualism"],"prefix":"10.1155","volume":"2010","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0911-0308","authenticated-orcid":true,"given":"M.","family":"Ursino","sequence":"first","affiliation":[{"name":"Department of Electronics, Computer Science and Systems, University of Bologna, Viale Risorgimento 2, I40136 Bologna, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"C.","family":"Cuppini","sequence":"additional","affiliation":[{"name":"Department of Electronics, Computer Science and Systems, University of Bologna, Viale Risorgimento 2, I40136 Bologna, 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