A03Construction and evaluation of neurocomputational models of natural language
Natural language processing (a branch of artificial intelligence) and the neurobiology of language (a branch of brain science) have been traditionally divorced. In natural language processing, on the one hand, computational bases of language have been developed under the shadow of deep learning techniques, but the question of how those computational bases are biologically realized in the human brain was not sufficiently addressed. In the neurobiology of language, on the other, neural bases of language have been revealed thanks to neuroimaging techniques, but the perspective on how those neural bases are algorithmically implemented with neural computations was largely neglected. However, despite being proposed relatively independently, those computational and neural bases show striking resemblance in that both constitute complex networks of various modules, so that the happy marriage of the two fields is highly desirable. For this purpose, in this research project, we will investigate computational and neural bases of language by constructing neurocomputational models based on symbolic automata and neural networks and evaluating them with neurophysiological measurements of human magnetoencephalography (MEG) and electrocorticography (ECoG).