A neural blackboard architecture of sentence structure

We present a neural architecture for sentence representation. Sentences are represented in terms of word representations as constituents. A word representation consists of a neural assembly distributed over the brain. Sentence representation does not result from associations between neural word assemblies. Instead, word assemblies are embedded in a neural architecture, in which the structural (thematic) relations between words can be represented. Arbitrary thematic relations between arguments and verbs can be represented. Arguments can consist of nouns and phrases, as in sentences with relative clauses. A number of sentences can be stored simultaneously in this architecture. We simulate how probe questions about thematic relations can be answered. We discuss how differences in sentence complexity, such as the difference between subject-extracted versus object-extracted relative clauses and the difference between right-branching versus center-embedded structures, can be related to the underlying neural dynamics of the model. Finally, we illustrate how memory capacity for sentence representation can be related to the nature of reverberating neural activity, which is used to store information temporarily in this architecture. 2 Introduction To understand how the brain enables the mind, processes at the neural level have to be related with processes at the cognitive level. This entails an implementation of cognitive processes in terms of neural computations. Successful implementations of this kind have been produced for processes in visual perception (e. implementations of language processes have been hard to come by. It is not difficult to see why. On the one hand, linguistic expressions are highly structured and language processes depend on complex and often recursive forms of information processing (e.g., Jackendoff, 1999). On the other hand, a direct animal model of language processing is lacking, which precludes a systematic analysis of language processes at the neural level. Yet, the overall structure of the cortex is highly uniform (e.g., Calvin, 1995; Mountcastle, 1998), which suggests that forms of neural representation and processing found in perception or attention could play an important role in other cognitive processes as well. This notion can be combined with the detailed knowledge about language representation and processing obtained by linguistics and psycholinguistics over the last decades. Thus, knowledge about language representation and processing can be used as a guiding principle in an implementation of (aspects of) language processing in terms of established forms of neural representation and processing. In this article, we will explore the possibility of a neural implementation of language processing. In …