Preserved artificial grammar learning in Parkinson's disease

Parkinson's disease (PD) patients and matched control subjects were compared in an artificial grammar learning task. The test strings were constructed in such a way that grammaticality judgments could not be based on some superficial features of the learning strings: the grammatical and nongrammatical test strings did not differ according to different measures of chunk strength (based on the frequency with which their bigrams and trigrams appear in the learning strings). Results show that PD patients and controls performed at the same level during the first presentation of the test strings series, which suggests that the striatum is not (crucially) implicated in the ability to abstract rules implicitly from exemplars generated by a finite-state grammar. However, and contrary to control subjects, the classification performance of PD patients was at chance during the second presentation of the test strings. We argue that this latter result could be the consequence of the attentional deficit of PD patients.