Computational Exploration of Lexical Development in Down Syndrome

Research on lexical development in Down syndrome (DS) has emphasized a dissociation between language comprehension and production abilities, with production of words being relatively more impaired than comprehension. Current theories stress the role of associative learning on lexical development. However, there have been no attempts to explain the atypical lexical development in DS based on atypical associative learning. The long-term potentiation (LTP) and long-term depression (LTD) of synapses, underlying associative learning, are altered in DS. Here we present a neural network model that instantiates notions from neurophysiological studies to account for the disparities between lexical comprehension and production in DS. Our simulations show that an atypical LTP/LTD balance affects comprehension and production differently in an associative model of lexical development.