Corticostriatal response selection in sentence production: Insights from neural network simulation with reservoir computing.

Abstract

Language production requires selection of the appropriate sentence structure to accommodate the communication goal of the speaker - the transmission of a particular meaning. Here we consider event meanings, in terms of predicates and thematic roles, and we address the problem that a given event can be described from multiple perspectives, which poses a problem of response selection. We present a model of response selection in sentence production that is inspired by the primate corticostriatal system. The model is implemented in the context of reservoir computing where the reservoir - a recurrent neural network with fixed connections - corresponds to cortex, and the readout corresponds to the striatum. We demonstrate robust learning, and generalization properties of the model, and demonstrate its cross linguistic capabilities in English and Japanese. The results contribute to the argument that the corticostriatal system plays a role in response selection in language production, and to the stance that reservoir computing is a valid potential model of corticostriatal processing.

DOI: 10.1016/j.bandl.2015.08.002

Cite this paper

@article{Hinaut2015CorticostriatalRS, title={Corticostriatal response selection in sentence production: Insights from neural network simulation with reservoir computing.}, author={Xavier Hinaut and Florian Lance and Colas Droin and Maxime Petit and Gr{\'e}goire Pointeau and Peter Ford Dominey}, journal={Brain and language}, year={2015}, volume={150}, pages={54-68} }