How variable are the classic ERP effects during sentence processing? A systematic resampling analysis of the N400 and P600 effects

• Published in: Cortex Vol. 177; pp. 130 - 149
• Main Authors: Kim, Albert E., McKnight, Shannon M., Miyake, Akira
• Format: Journal Article
• Language: English
• Published: Italy Elsevier Ltd 01.08.2024
• Subjects: Adolescent; Adult; Bootstrapping; Brain - physiology; Comprehension - physiology; Electroencephalography - methods; Evoked Potentials - physiology; Female; Humans; Language; Male; N400; P600; Reading; Resampling analysis; Semantics; Statistical power; Young Adult; Bootstrapping; N400; P600; Statistical power; Resampling analysis
• ISSN: 0010-9452; 1973-8102; 1973-8102
• DOI: 10.1016/j.cortex.2024.05.007

Although event-related potential (ERP) research on language processing has capitalized on key, theoretically influential components such as the N400 and P600, their measurement properties—especially the variability in their temporal and spatial parameters—have rarely been examined. The current study examined the measurement properties of the N400 and P600 effects elicited by semantic and syntactic anomalies, respectively, during sentence processing. We used a bootstrap resampling procedure to randomly draw many thousands of resamples varying in sample size and stimulus count from a larger sample of 187 participants and 40 stimulus sentences of each type per condition. Our resampling investigation focused on three issues: (a) statistical power; (b) variability in the magnitudes of the effects; and (c) variability in the temporal and spatial profiles of the effects. At the level of grand averages, the N400 and P600 effects were both robust and substantial. However, across resamples, there was a high degree of variability in effect magnitudes, onset times, and scalp distributions, which may be greater than is currently appreciated in the literature, especially for the P600 effects. These results provide a useful basis for designing future studies using these two well-established ERP components. At the same time, the results also highlight challenges that need to be addressed in future research (e.g., how best to analyze the ERP data without engaging in such questionable research practices as p-hacking).