Contrasting time and frequency domains: ERN and induced theta oscillations differentially predict post-error behavior

Area of Science:

• Cognitive Neuroscience
• Electrophysiology
• Action Monitoring

Background:

• Error processing is crucial for adaptive behavior and involves distinct neural signals.
• Previous research often examined evoked and induced neural activity separately, limiting a comprehensive understanding of error monitoring.

Purpose of the Study:

• To investigate the single-trial neural dynamics of error processing in both time and frequency domains.
• To differentiate the predictive roles of evoked (error-related negativity, ERN) and induced (frontal midline theta) neural activity on post-error behavioral adjustments.

Main Methods:

• Utilized electroencephalography (EEG) to analyze evoked and induced signal components at the single-trial level.
• Employed mediation models to assess the relationships between neural signals and post-error slowing (PES) and post-error accuracy (PEA).

Main Results:

• Frontal midline theta power predicted both PES and PEA across trial types.
• The error-related negativity (ERN) only predicted PES on incongruent trials.
• Mediation analysis revealed that PES mediated the relationship between theta power and PEA, but not between ERN and PEA.

Conclusions:

• Frontal midline theta and ERN reflect distinct, though related, cognitive processes in error monitoring.
• Induced theta activity offers a more comprehensive neural index for adaptive post-error adjustments than evoked ERN.
• Findings support the adaptive theory of post-error slowing and advocate for time-frequency analysis in studying medial frontal cortex function.