Abstract
To clarify the functional significance of Go event-related potential (ERP) components, this study aimed to explore stimulus- and response-locked ERP averaging effects on the series of ERP components elicited during an auditory Go/NoGo task. Go stimulus- and response-locked ERP data from 126 healthy young adults (Mage = 20.3, SD = 2.8 years, 83 female) were decomposed using temporal principal components analysis (PCA). The extracted components were then identified as stimulus- specific, response-specific, or common to both stimulus- and response-locked data. MANOVAs were then used to test for stimulus- versus response-locked averaging effects on common component amplitudes to determine their primary functional significance (i.e., stimulus- or response-related). Go stimulus- and response-related component amplitudes were then entered into stepwise linear regressions predicting the reaction time (RT), RT variability, and omission errors. Nine ERP components were extracted from the stimulus- and response-locked data, including N1-1, processing negativity (PN), P2, response-related N2 (RN2), motor potential (MP), P3b, P420, and two slow wave components; SW1 and SW2. N1-1, PN, and P2 were stimulus-specific, whereas, RN2, MP, and P420 were response-specific; P3b, SW1, and SW2 were common to both data sets. P3b, SW1, and SW2 were significantly larger in the response-locked data, indicating that they were primarily response-related. RT, RT variability, and omission errors were predicted by various stimulus- and response-related components, providing further insight into ERP markers of auditory information processing and cognitive control. Further, the results of this study indicate the utility of quantifying some common components (i.e., Go P3b, SW1, and SW2) using the response-locked ERP.
Original language | English |
---|---|
Article number | e13538 |
Number of pages | 11 |
Journal | Psychophysiology |
Volume | 57 |
Issue number | 5 |
DOIs | |
Publication status | Published - 2020 |
Keywords
- cognition
- enterprise resource planning
- human information processing