Neural and behavioral effects of regulating emotional responses to errors during an implicit racial bias task

Psychiatric and affective predictors of negative racial attitudes

Negative Racial Attitudes (NRA) have been identified as major contributors to discrimination and inequalities. Previous studies of predictors of NRA have focused largely on socioeconomic, socialization, social attitudes, and personality characteristics. Yet, the potential links of psychiatric and affective indicators to NRA have received little scientific inquiry. Three-hundred-and-two participants completed measures of explicit, covert, and implicit NRA, along with indices of psychotic-like experiences (PLEs), mood symptoms, affective processing, social attitudes, and personality characteristics. Explicit and covert NRA were significantly correlated with difficulty identifying and describing feelings, use of suppression to regulate emotion, and the PLEs domains of perceptual abnormalities, bizarre experiences, and persecutory ideation, along with social attitudes and personality characteristics. Implicit NRA was not associated with any indicators. Next, employing hierarchical multiple linear regression analyses, the affective and psychiatric indicators accounted 5.2% and 10.4% of the explicit and covert NRA variance, respectively, controlling for previously identified predictors including demographics, social attitudes, and personality characteristics. Our results point to newly identified predictors of NRA including difficulties identifying and describing emotions, use of suppression to regulate emotions, as well as PLEs, specifically perceptual abnormalities. We discuss the implications of the findings to the development and adaptation of anti-racism interventions.

Aversiveness of errors and the error-related negativity (ERN): A systematic review on the affective states' manipulations findings

Error-related negativity (ERN) has been used to investigate neural mechanisms underlying error processing and conflict monitoring. Recent evidence highlights that affective and motivational states modulate the ERN and that aversiveness of errors plays a vital role in error monitoring. Therefore, our primary objective was to systematically evaluate and describe the influence of affect state-related manipulations on the ERN. A total of 51 publications identified from PsyInfo, PubMed, and PsyArticles databases were included following the Prisma procedures for systematic reviews. Papers were analyzed using sample attributes, psychological paradigms, and states manipulations. The present study shows that the ERN component has recurrently appeared to be sensitive to manipulations of affective states in the reviewed literature. However, conclusive findings concerning the affect state-dependent properties of the ERN remain elusive. Results are discussed considering heterogeneity in paradigms, variables, and the state-trait interactions. Furthermore, recommendations for future high-quality studies are provided along with the necessity of upcoming high-power replication attempts and more studies with positive affect manipulations.

Brain-Computer Interfaces, Open-Source, and Democratizing the Future of Augmented Consciousness

Accessibility, adaptability, and transparency of Brain-Computer Interface (BCI) tools and the data they collect will likely impact how we collectively navigate a new digital age. This discussion reviews some of the diverse and transdisciplinary applications of BCI technology and draws speculative inferences about the ways in which BCI tools, combined with machine learning (ML) algorithms may shape the future. BCIs come with substantial ethical and risk considerations, and it is argued that open source principles may help us navigate complex dilemmas by encouraging experimentation and making developments public as we build safeguards into this new paradigm. Bringing open-source principles of adaptability and transparency to BCI tools can help democratize the technology, permitting more voices to contribute to the conversation of what a BCI-driven future should look like. Open-source BCI tools and access to raw data, in contrast to black-box algorithms and limited access to summary data, are critical facets enabling artists, DIYers, researchers and other domain experts to participate in the conversation about how to study and augment human consciousness. Looking forward to a future in which augmented and virtual reality become integral parts of daily life, BCIs will likely play an increasingly important role in creating closed-loop feedback for generative content. Brain-computer interfaces are uniquely situated to provide artificial intelligence (AI) algorithms the necessary data for determining the decoding and timing of content delivery. The extent to which these algorithms are open-source may be critical to examine them for integrity, implicit bias, and conflicts of interest.

TEAMwork: Testing Emotional Attunement and Mutuality During Parent-Adolescent fMRI

The parent-child relationship and family context influence the development of emotion regulation (ER) brain circuitry and related skills in children and adolescents. Although both parents' and children's ER neurocircuitry simultaneously affect how they interact with one another, neuroimaging studies of parent-child relationships typically include only one member of the dyad in brain imaging procedures. The current study examined brain activation related to parenting and ER in parent-adolescent dyads during concurrent fMRI scanning with a novel task - the Testing Emotional Attunement and Mutuality (TEAM) task. The TEAM task includes feedback trials indicating the other dyad member made an error, resulting in a monetary loss for both participants. Results indicate that positive parenting practices as reported by the adolescent were positively correlated with parents' hemodynamic activation of the ventromedial prefrontal cortex, a region related to empathy, during these error trials. Additionally, during feedback conditions both parents and adolescents exhibited fMRI activation in ER-related regions, including the dorsolateral prefrontal cortex, anterior insula, fusiform gyrus, thalamus, caudate, precuneus, and superior parietal lobule. Adolescents had higher left amygdala activation than parents during the feedback condition. These findings demonstrate the utility of dyadic fMRI scanning for investigating relational processes, particularly in the parent-child relationship.

Temporal dynamics of error-related corrugator supercilii and zygomaticus major activity: Evidence for implicit emotion regulation following errors

According to feedback control models, errors are monitored and inform subsequent control adaptations. Despite these cognitive consequences, errors also have affective consequences. It has been suggested that errors elicit negative affect which might be functional for control adaptations. The present research is concerned with the temporal dynamics of error-related affect. Therefore, we ask how affective responses to errors change over time. Two experiments assessed performance in a Stroop-like task in combination with online measures of facial electromyography that index affective responses specific for muscles that are associated with the expression of negative (corrugator supercilii) and positive affect (zygomaticus major). After errors, corrugator activity first increased relative to correct trials but then decreased (below correct trials) for later time bins. Zygomaticus activity showed a concomitant inverse pattern following errors, such that an initial decrease was followed by a later increase relative to correct trials. Together, this biphasic response in both facial muscles suggests that early negative responses to errors turn into increasingly more positive ones over time. Error-triggered electromyography did marginally predict behavioral adjustments following errors at the inter-individual, but not at the intra-individual level, providing only limited evidence for a functional role of error-related affect for immediate changes in behavior. However, the dynamics of error-related electromyography points to the role of implicit emotion regulation during task performance. We propose that this process helps to maintain homeostasis of positive and negative affect which in the long term could facilitate adaptive behavior.