PRESERVED ARTIFICIAL GRAMMAR LEARNING IN PARKINSONS-DISEASE

Parkinson's disease (PD) patients and matched control subjects were co mpared in an artificial grammar learning task. The test strings were c onstructed in such a way that grammaticality judgments could not be ba sed on some superficial features of the learning strings: the grammati cal and nongrammatical test strings did not differ according to differ ent measures of chunk strength (based on the frequency with which thei r bigrams and trigrams appear in the learning strings). Results show t hat PD patients and controls performed at the same level during the fi rst presentation of the test strings series, which suggests that the s triatum is not (crucially) implicated in the ability to abstract rules implicitly from exemplars generated by a finite-state grammar. Howeve r, 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.