Expectancy modulates a late positive ERP in an artificial grammar task.

A wide range of studies have found late positive ERP components in response to anomalies during processing of structured sequences. In language studies, this component is named Syntactic Positive Shift (SPS) or P600. It is characterized by an increase in potential peaking around 600 ms after the appearance of the syntactic anomaly and has a centroparietal topography. Similar late positive components were found more recently in non-linguistic contexts. These results have led to the hypothesis that these components index the detection of anomalies in rule-governed sequences, or the access to abstract rule representations, regardless of the nature of the stimuli. Additionally, there is evidence showing that the SPS/P600 is sensitive to probability manipulations, which affect the subjects' expectancy of the stimuli. Our aim in the present work was to address the hypothesis that the late positive component is modulated by the subject's expectancy of the stimuli. To do so, we employed an artificial grammar learning task, and controlled the frequency of presentation to different kind of sequences during training. Results showed that certain sequence types elicited a late positive component which was modulated by different factors in two distinct time windows. In an earlier window, the component was higher for sequences which had a low or null probability of occurrence during training, while in a later window, the component was higher for incorrect than correct sequences. Furthermore, this late window effect was absent in those subjects whose performance was not significantly above chance. Two possible explanations for this effect are suggested.