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Ever since the 19th century, the standard model for spoken language processing has assumed two pathways for repetition—a phonological pathway and a semantic pathway—and this idea has gained further support in the last decade. First, recent  in vivo  tractography studies have demonstrated both the “dorsal” (via arcuate fasciculus) and “ventral” (via extreme capsule and uncinate fasciculus) pathways connecting from the primary auditory area to the speech-motor area, the latter of which passes through a brain area associated with semantic processing (anterior temporal lobe). Secondly, neuropsychological evidence for the role of semantics in repetition is  conduite d'approche , a successive phonological improvement (sometimes non-improvement) in aphasic patients' response by repeating several times in succession. Crucially, conduite d'approche is observed in patients with neurological damage in/around the arcuate fasciculus. Successful conduite d'approche is especially clear for semantically-intact patients and it occurs for real words rather than for non-words. These features have led researchers to hypothesize that the patients' disrupted phonological output is “cleaned-up” by intact lexical-semantic information before the next repetition. We tested this hypothesis using the neuroanatomically-constrained dual dorsal-ventral pathway computational model. The results showed that (a) damage to the dorsal pathway impaired repetition; (b) in the context of recovery, the model learned to compute a correct repetition response following the model's own noisy speech output (i.e., successful conduite d'approche); (c) this behavior was more evident for real words than non-words; and (d) activation from the ventral pathway contributed to the increased rate of successful conduite d'approche for real words. These results suggest that lexical-semantic “clean-up” is key to this self-correcting mechanism, supporting the classic proposal of two pathways for repetition.

The roles of the “ventral” semantic and “dorsal” pathways in conduite d'approche: a neuroanatomically-constrained computational modeling investigation