Computational Neurolinguistics - What Is It All About?

Computational Neurolinguisties (CN) integrates a r t i f i c i a l intel l igence (AI) methods with concepts of neurally motivated processing to develop cognitive models of natural language processing. HOPE is one example of a model developed to address issues in CN. The model is pa ra l l e l , and exemplifies language as the result of time synchronized processes which are asynchronous in nature. Furthermore, the model is substantial ly validated to include normal behavioral evidence in i t s design. In addit ion, it attends to aspects of language breakdown which are well documented in the l i te ra ture of neurolinguistics or aphasia. This paper discusses assumptions which under l ie the CN approach to model development. It w i l l describe the neurally motivated or "natural computational" processes which produce the model's observable and ver i f iab le behavioral results. The differences in the CN approach to other models of paral le l memory process and behavior w i l l be presented. F ina l ly , the contribution of the CN research approach as a tool for investigating the breakdown of language performance and i t s potent i a l contr ibution to understanding brain function w i l l be discussed.