A central pattern generator for controlling sequential activation in a neural architecture for sentence processing

Abstract

The neural architecture for sentence processing is a model of a neural ‘blackboard’ capable of temporarily storing both semantic and syntactic information. Retrieving information from the neural blackboard requires a sequence of activations that is controlled by a central pattern generator. We implement a central pattern generator that controls the sequence of activation. To ground the implementation in a biological context, the implementation is based on a model of the escape swim network of Tritonia diomedea, a marine mollusk. A central pattern generator is developed to meet the specifications required to successfully control the sequence of actions and activations needed to retrieve information from the neural blackboard in response to a question. The model is an existence proof for a biologically plausible implementation of a neural blackboard central pattern generator. The role of the central pattern generator in this neural architecture of sentence processing illustrates the potential relation between controlling movement processing and cognitive processing.