Computational neurolinguistics (CN) is an approach to computational linguistics which includes neurally-motivated constraints in the design of models of natural language processing. Furthermore, the knowledge representations included in such models must be supported with documented behaviorial ev~ce, normal and pathological. This paper will discuss the contribution of CN models to ~the understanding of linguistic "competence" within recent research efforts to adapt HOPE (Gigley 1981; 1982a; 1982b; 1982c; 1983a), an implemented CN model for "understanding" English to I'ESPERANCE, one which "understands" French.