Neuroimaging measures of error-processing: Extracting reliable signals from event-related potentials and functional magnetic resonance imaging

Abstract

Error-related brain activity has become an increasingly important focus of cognitive neuroscience research utilizing both event-related potentials (ERPs) and functional magnetic resonance imaging (fMRI). Given the significant time and resources required to collect these data, it is important for researchers to plan their experiments such that stable estimates of error-related processes can be achieved efficiently. Reliability of error-related brain measures will vary as a function of the number of error trials and the number of participants included in the averages. Unfortunately, systematic investigations of the number of events and participants required to achieve stability in error-related processing are sparse, and none have addressed variability in sample size. Our goal here is to provide data compiled from a large sample of healthy participants (n = 180) performing a Go/NoGo task, resampled iteratively to demonstrate the relative stability of measures of error-related brain activity given a range of sample sizes and event numbers included in the averages. We examine ERP measures of error-related negativity (ERN/Ne) and error positivity (Pe), as well as event-related fMRI measures locked to false alarms. We find that achieving stable estimates of ERP measures required four to six error trials and approximately 30 participants; fMRI measures required six to eight trials and approximately 40 participants. Fewer trials and participants were required for measures where additional data reduction techniques (i.e., principal component analysis and independent component analysis) were implemented. Ranges of reliability statistics for various sample sizes and numbers of trials are provided. We intend this to be a useful resource for those planning or evaluating ERP or fMRI investigations with tasks designed to measure error-processing.

Development of the error-monitoring system from ages 9–35: Unique insight provided by MRI-constrained source localization of EEG

“…Following interpolation, data were referenced to the average of all electrodes. All participants included in the ERP and current source analyses had a minimum of 10 artifact-free incongruent-error trials ( M = 29.05, SD = 11.52), which has been shown to elicit a reliable measurement of the ERN in both children and adults (Pontifex et al, 2010; Steele et al, 2016). Further, the number of artifact-free error trials did not correlate with age (r = .216, p = .164).…”

Effects of reward context on feedback processing as indexed by time‐frequency analysis

“…While an important benefit of resampling techniques in general are the improved estimates of population parameters, the primary purpose of implementing these techniques was to remove any bias associated with uneven trail counts by equating the number of trails in each subject‐electrode‐condition average. Indeed, previous research has shown that the number of trails used in each average affects the reliability of the measures extracted from ERPs (J. Cohen & Polich, ; Olvet & Hajcak, ; Pontifex et al, ; Steele et al, ). Thus, in the current study, resampling and bootstrapping methods used in previous research (Watts et al, ) were employed.…”

Adolescent neural response to reward is related to participant sex and task motivation

“…Only the feedback phase (combining wins across all types of trials) was analyzed in the present study, because it offers the most power for statistical analysis (i.e. number of trials is not limited by participant selections) (Jones, Cservenka, & Nagel, 2016; Steele et al, 2016). During this phase, the screen indicated whether the participant won or did not win money during that trial, as well as the cumulative dollar amount won up to that point.…”