Individual differences in decisiveness: ERP correlates of response inhibition and error monitoring

Does the stop-signal P3 reflect inhibitory control?

The ability to stop already-initiated actions is paramount to adaptive behavior. In psychology and neuroscience alike, action-stopping is a popular model behavior to probe inhibitory control - the underlying cognitive control process that is purportedly vital to regulating thoughts and actions. Starting with seminal work in the 1990s, the frontocentral stop-signal P3 - an event-related potential derived from scalp EEG - has been proposed as a neurophysiological index of inhibitory control during action-stopping. However, this association has been challenged repeatedly over recent years. Here, we perform a critical review of both the evidence in support of the association between this P3 index and inhibitory control, as well as its documented criticisms. We first comprehensively review literature from the past three decades that suggested a link between stop-signal P3 and inhibitory control. Second, we then replicate the key empirical patterns reported in that body of literature in a uniquely large stop-signal task EEG dataset (N = 255). Third, we then examine the criticisms raised against the view of P3 as an index of inhibitory control and evaluate the evidence supporting these arguments. Finally, we present an updated view of the process(es) reflected in the stop-signal P3. Specifically, we propose that the stop-signal P3 indexes a specific, selective inhibitory control process that critically contributes to action-stopping. This view is motivated by recent two-stage models of inhibitory control and emerging empirical data. Together, we hope to clarify the process(es) reflected in the stop-signal P3 and resolve the ongoing debates regarding its utility as an index of inhibitory control during action-stopping.

A network analysis of affective and motivational individual differences and error monitoring in a non-clinical sample

Error monitoring, which plays a crucial role in shaping adaptive behavior, is influenced by a complex interplay of affective and motivational factors. Understanding these associations often proves challenging due to the intricate nature of these variables. With the aim of addressing previous inconsistencies and methodological gaps, in this study, we utilized network analysis to investigate the relationship between affective and motivational individual differences and error monitoring. We employed six Gaussian Graphical Models on a non-clinical population ($N$ = 236) to examine the conditional dependence between the amplitude of response-related potentials (error-related negativity; correct-related negativity) and 29 self-report measures related to anxiety, depression, obsessive thoughts, compulsive behavior, and motivation while adjusting for covariates: age, handedness, and latency of error-related negativity and correct-related negativity. We then validated our results on an independent sample of 107 participants. Our findings revealed unique associations between error-related negativity amplitudes and specific traits. Notably, more pronounced error-related negativity amplitudes were associated with increased rumination and obsessing, and decreased reward sensitivity. Importantly, in our non-clinical sample, error-related negativity was not directly associated with trait anxiety. These results underscore the nuanced effects of affective and motivational traits on error processing in healthy population.

A high-density EEG investigation into the neurocognitive mechanisms underlying differences between personality profiles in social information processing

This study investigated whether differences between personality styles in the processing of social stimuli reflect variability in underlying general-purpose or social-specific neurocognitive mechanisms. Sixty-five individuals classified previously into two distinct personality profiles underwent high-density electroencephalography whilst performing tasks that tap into both aspects of cognitive processing - namely, two distinct facets of general-purpose response inhibition (interference resolution and action withholding) during social information processing. To determine the stage of processing at which personality differences manifest, we assessed event-related components associated with the early visual discrimination of social stimuli (N170, N190) and later more general conflict-related processes (N2, P3). Although a performance index of interference resolution was comparable between the personality profiles, differences were detected in action withholding. Specifically, individuals expressing a wider repertoire of personality styles and more adaptive emotion regulation performed significantly better at withholding inappropriate actions to neutral faces presented in emotional contexts compared with those exhibiting stronger preferences for fewer and less adaptive personality styles and more ruminative affective tendencies. At the neurophysiological level, however, difference between the profiles was observed in brain responses elicited to the same stimuli within the N170. These results indicate that neural processes related to early visual discrimination might contribute to differences in the suppression of inappropriate responses towards social stimuli in populations with different personality dispositions.

Multivariate morphological brain signatures enable individualized prediction of dispositional need for closure

Need for closure (NFC) reflects stable individual differences in the desire for a quick, definite, and stable answer to a question. A large body of research has documented the association between NFC and various cognitive, emotional and social processes. Despite considerable interest in psychology, little effort has been made to uncover the neural substrates of individual variations in NFC. Herein, we took a data-driven approach to predict NFC trait combining machine learning framework and the whole-brain grey matter volume (GMV) features, which represent a reliable brain imaging measure and have been commonly employed to explore neural basis underlying individual differences of cognition and behaviors. Brain regions contributing to the prediction were then subjected to functional connectivity and decoding analyses for a quantitative inference on their psychophysiological functions. Our results indicated that multivariate patterns of GMV derived from multiple regions across distributed brain systems predicted NFC at individual level. The contributing regions are distributed across the emotional processing network (e.g., striatum), cognitive control network (e.g., lateral prefrontal cortex), social cognition network (e.g., temporoparietal junction) and perceptual processing network (e.g., occipital cortex). The current study provided the first evidence that dispositional NFC is embodied in multiple large-scale brain networks, helping to delineate a more complete picture about the neuropsychological processes that support individual differences in NFC. Beyond these findings, the current interdisciplinary approach to constructing and interpreting neuroimaging-based prediction model of personality traits would be informative to a wide range of future studies on personality.

Temporal Fluctuation of Mood in Gaming Task Modulates Feedback Negativity: EEG Study With Virtual Reality

Feedback outcomes are generally classified into positive and negative feedback. People often predict a feedback outcome with information that is based on both objective facts and uncertain subjective information, such as a mood. For example, if an action leads to good results consecutively, people performing the action overestimate the behavioral result of the next action. In electroencephalogram measurements, negative feedback evokes negative potential, called feedback negativity, and positive feedback evokes positive potential, called reward positivity. The present study investigated the relationship between the degree of the mood caused by the feedback outcome and the error-related brain potentials. We measured the electroencephalogram activity while the participants played a virtual reality shooting game. The experimental task was to shoot down a cannonball flying toward the player using a handgun. The task difficulty was determined from the size and curve of the flying cannonball. These gaming parameters affected the outcome probability of shooting the target in the game. We also implemented configurations in the game, such as the player’s life points and play times. These configurations affected the outcome magnitude of shooting the target in the game. Moreover, we used the temporal accuracy of shooting in the game as the parameter of the mood. We investigated the relationship between these experimental features and the event-related potentials using the single-trial-based linear mixed-effects model analysis. The feedback negativity was observed at an error trial, and its amplitude was modulated with the outcome probability and the mood. Conversely, reward positivity was observed at hit trials, but its amplitude was modulated with the outcome probability and outcome magnitude. This result suggests that feedback negativity is enhanced according to not only the feedback probability but also the mood that was changed depending on the temporal gaming outcome.

Abnormal performance monitoring but intact response inhibition in sensation seeking

The sensation-seeking trait is a potential endophenotype for various addictive behaviors. Using a nonclinical sample, the current ERP study examined the effects of sensation seeking on performance monitoring and response inhibition. Twenty high sensation seekers and 21 low sensation seekers were selected from a large sample based on their sensation-seeking score and performed a stop-signal task while their EEG was recorded. High relative to low sensation seekers displayed similar response inhibition in terms of performance measure and stop-P3 amplitudes. Compared to low sensation seekers, however, high sensation seekers exhibited a reduced stop-N2 for unsuccessful, but not successful, inhibition. Moreover, an enhanced go-N2 in response to go signals was observed for high versus low sensation seekers, irrespective of whether the go signals were followed by a stop signal or not. Together, our findings suggest that sensation seeking in nonclinical populations is related to individual variability in performance monitoring rather than response inhibition, which provides important implications for the prevention and intervention of addictive behaviors that are driven by trait sensation seeking.

Religious fundamentalism is associated with hyperactive performance monitoring: ERP evidence from correct and erroneous responses

The aim of the current study was to examine whether action monitoring is associated with religious fundamentalism. Participants performed a stop-signal task that required response inhibition to a simple auditory tone. The level of their religious fundamentalism was measured on a scale. Analysis with mixed-effects linear models revealed significantly larger error-related negativity, correct-related negativity, and post-error positivity components in individuals scoring higher on religious fundamentalism, pointing to their increased engagement in response monitoring. However, it was not accompanied by improved behavioral performance. The electrophysiological results of our study suggest that individuals high in religious fundamentalism engage more in monitoring for conflict between outcomes of their actions and standards of correct behavior. Our findings also point to a possible association between a fundamentalist mindset and higher levels of negative affect, uncertainty, anxiety, and distress, as measured by response-related brain activity.