We provide a threefold taxonomy of models in neurolinguistics: faculty models, which embrace the work of classical connectionists and holists and of such modern workers as Geschwind; process models, which are exemplified by the work of Luria, and which fractionate psycholinguistic tasks and ascribe the components to particular brain regions; and representational models, which use specific linguistic representations to build a psycholinguistic analysis of aphasic performance. We argue that further progress requires that neurolinguistics become more computational, using techniques from Artificial Intelligence to model the cooperative computation underlying language processing at a level of detail consonant with linguistic representations. Finally, we note that current neurolinguistics makes virtually no contact with the synapse-cell-circuit level of analysis characteristic of twentieth-century neuroscience. We suggest that the cooperative computation models we envisage provide the necessary intermediary between current neurolinguistic analysis and the utilization of the fruits of modern neuroanatomy, neurochemistry, and neurophysiology.