Intact Artificial Grammar Learning in Amnesia: Dissociation of Classification Learning and Explicit Memory for Specific Instances

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Abstract
The present study investigates whether the ability to classify on the basis of rules can be learned independently of memory for the specific instances used to leach the rules. Thirteen amnesic patients and 14 control subjects studied letter strings generated by an artificial grammar. Subjects were then shown new letter strings and were instructed to classify them as grammatical or nongrammatical. Amnesic patients performed as well as normal subjects. However, amnesic patients performed more poorly than control subjects on a recognition test of the exemplars that had been presented. Amnesic patients also performed more poorly than control subjects when the instructions were to base the classification on explicit comparison with the original exemplars. The results show that classification learning based on exemplars of an artificial grammar can develop normally despite impaired memory for the exemplars themselves. Whereas exemplar memory depends on interactions between neocortex and the limbic system, classification learning may depend on interaction between neocortex and the neostriatum.