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Título del libro: Cogsci 2017 - Proceedings Of The 39th Annual Meeting Of The Cognitive Science Society: Computational Foundations Of Cognition
Título del capítulo: Computational Exploration of Lexical Development in Down Syndrome

Autores UNAM:
ANGEL EUGENIO TOVAR Y ROMO;
Autores externos:

Idioma:

Año de publicación:
2017
Palabras clave:

Computation theory; Associative learning; Atypicals; Comprehension/production asymmetry; Computational exploration; Down's syndrome; Language production; Lexical development; Long term depression; Long-term potentiations; Neurocomputational models; Neural network models


Resumen:

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. © CogSci 2017.


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