Computational Neurolinguistics - What Is It All About?

Abstract

Computational Neurolinguisties (CN) integrates artificial intelligence (AI) methods with concepts of neurally motivated processing to develop cognitive models of language processing. HOPE is one example of a model developed to address issues in CN. The model is parallel, and exemplifies language as the result of time synchronized processes which are asynchronous in nature. Furthermore, the model is substantially validated to include normal behavioral evidence in its design. In addition, it attends to aspects of language breakdown which are well documented in the literature of neurolinguistics or aphasia. This paper discusses assumptions which underlie the CN approach to model development. It will describe the neurally motivated or natural computational processes which produce the model's observable and verifiable behavioral results. The differences in the CN approach to other models of parallel memory process and behavior will be presented. Finally, the contribution of the CN research approach as a tool for investigating the breakdown of language performance and its potential contribution to understanding brain function will be discussed.