Expectancy modulates a late positive ERP in an artificial grammar task

Area of Science:

• Cognitive Neuroscience
• Psycholinguistics
• Event-Related Potentials (ERPs)

Background:

• Late positive ERP components, including the Syntactic Positive Shift (SPS) or P600, are observed in response to anomalies in structured sequences.
• These components are hypothesized to index anomaly detection or abstract rule access, irrespective of stimulus type.
• Evidence suggests sensitivity to probability manipulations, influencing stimulus expectancy.

Purpose of the Study:

• To investigate whether late positive ERP components are modulated by stimulus expectancy.
• To test the hypothesis that expectancy influences the neural processing of anomalies in rule-governed sequences.

Main Methods:

• An artificial grammar learning task was utilized.
• Sequence presentation frequency was controlled during training to manipulate expectancy.
• Event-related potentials (ERPs) were recorded and analyzed.

Main Results:

• A late positive component showed modulation in two distinct time windows based on sequence type and probability.
• An earlier window revealed higher component amplitude for low/null probability sequences.
• A later window showed higher amplitude for incorrect versus correct sequences, but only in participants with above-chance performance.

Conclusions:

• Late positive ERP components are sensitive to both stimulus probability and accuracy, reflecting expectancy and rule violation.
• The observed effects suggest distinct neural processes related to expectancy and error detection.
• Performance accuracy is crucial for the later component's sensitivity to rule violations.