A model-driven analysis of severity, response characteristics, and partial recovery in aphasics' picture naming.

Dell, Schwartz, Martin, Saffran, and Gagnon (DSMSG; 1997) presented a computational analysis of aphasic naming that, among other things, purports to explain why some error types correlate with naming severity while others do not. It does so in terms of chance response opportunities, which differ among error types and which come into play particularly when activation levels are small. The present study looks at error frequencies in relation to severity at two points in time: at study entry and after a period of partial recovery. Results support the model's distinction between severity-sensitive errors (nonwords. formal paraphasias, and unrelated errors) and those that are severity insensitive (semantic; mixed). Additionally, we show that the degree of target overlap in nonwords is sensitive to severity but various measures of monitoring and error correction are not. While these results generally support DSMSG, effects at the level of individual patients underscore the difficulties that their model encounters in explaining some pure error dissociations.