A Fluid Self-Concept: How the Brain Maintains Coherence and Positivity across an Interconnected Self-Concept While Incorporating Social Feedback.

People experience instances of social feedback as interdependent with potential implications for their entire self-concept. How do people maintain positivity and coherence across the self-concept while updating self-views from feedback? We present a network model describing how the brain represents the semantic dependency relations among traits and uses this information to avoid an overall loss of positivity and coherence. Both male and female human participants received social feedback during a self-evaluation task while undergoing functional magnetic resonance imaging. We modeled self-belief updating by incorporating a reinforcement learning model within the network structure. Participants learned more rapidly from positive than negative feedback and were less likely to change self-views for traits with more dependencies in the network. Further, participants back propagated feedback across network relations while retrieving prior feedback on the basis of network similarity to inform ongoing self-views. Activation in ventromedial prefrontal cortex (vmPFC) reflected the constrained updating process such that positive feedback led to higher activation and negative feedback to less activation for traits with more dependencies. Additionally, vmPFC was associated with the novelty of a trait relative to previously self-evaluated traits in the network, and angular gyrus was associated with greater certainty for self-beliefs given the relevance of prior feedback. We propose that neural computations that selectively enhance or attenuate social feedback and retrieve past relevant experiences to guide ongoing self-evaluations may support an overall positive and coherent self-concept.SIGNIFICANCE STATEMENT We humans experience social feedback throughout our lives, but we do not dispassionately incorporate feedback into our self-concept. The implications of feedback for our entire self-concept plays a role in how we either change or retain our prior self-beliefs. In a neuroimaging study, we find that people are less likely to change their beliefs from feedback when the feedback has broader implications for the self-concept. This resistance to change is reflected in processing in the ventromedial prefrontal cortex, a region that is central to self-referential and social cognition. These results are broadly applicable given the role that maintaining a positive and coherent self-concept plays in promoting mental health and development throughout the lifespan.

Stereotypes disrupt probabilistic category learning.

Racial stereotypes exert pernicious effects on decision-making and behavior, yet little is known about how stereotypes disrupt people's ability to learn new associations. The current research interrogates a fundamental question about the boundary conditions of probabilistic learning by examining whether and how learning is influenced by preexisting associations. Across three experiments, participants learned the probabilistic outcomes of different card combinations based on feedback in either a social (e.g., forecasting crime) or nonsocial (e.g., forecasting weather) learning context. During learning, participants were presented with either task-irrelevant social (i.e., Black or White faces) or nonsocial (i.e., darker or lighter clouds) stimuli that were stereotypically congruent or incongruent with the learning context. Participants exhibited learning disruptions in the social compared to nonsocial learning context, despite repeated instructions that the stimuli were unrelated to the outcome (Studies 1 and 2). We also found no differences in learning disruptions when participants learned in the presence of negatively (Black and criminal) or positively valenced stereotypes (Black and athletic; Study 3). Finally, we tested whether learning decrements were due to "first-order" stereotype application or inhibition at the trial level, or due to "second-order" cognitive load disruptions that accumulate across trials due to fears of appearing prejudiced (aggregated analysis). We found no evidence of first-order disruptions and instead found evidence for second-order disruptions: participants who were more internally motivated to respond without prejudice, and thus more likely to self-monitor their responses, learned less accurately over time. We discuss the implications of the influence of stereotypes on learning and memory. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Uncertain threat is associated with greater impulsive actions and neural dissimilarity to Black versus White faces.

Race is a social construct that contributes to group membership and heightens emotional arousal in intergroup contexts. Little is known about how emotional arousal, specifically uncertain threat, influences behavior and brain processes in response to race information. We investigated the effects of experimentally manipulated uncertain threat on impulsive actions to Black versus White faces in a community sample (n = 106) of Black and White adults. While undergoing fMRI, participants performed an emotional go/no-go task under three conditions of uncertainty: 1) anticipation of an uncertain threat (i.e., unpredictable loud aversive sound); 2) anticipation of an uncertain reward (i.e., unpredictable receipt of money); and 3) no anticipation of an uncertain event. Representational similarity analysis was used to examine the neural representations of race information across functional brain networks between conditions of uncertainty. Participants-regardless of their own race-showed greater impulsivity and neural dissimilarity in response to Black versus White faces across all functional brain networks in conditions of uncertain threat relative to other conditions. This pattern of greater neural dissimilarity under threat was enhanced in individuals with high implicit racial bias. Our results illustrate the distinct and important influence of uncertain threat on global differentiation in how race information is represented in the brain, which may contribute to racially biased behavior.

Computational underpinnings of partisan information processing biases and associations with depth of cognitive reasoning.

Despite unprecedented access to information, partisans increasingly disagree about basic facts that are backed by data, posing a serious threat to a democracy that relies on finding common ground based on objective truths. We examine the underpinnings of this phenomenon using drift diffusion modeling (DDM). Partisans (N = 148) completed a sequential sampling task where they evaluated the honesty of Democrat or Republican politicians during a debate based on fact-check scores. We found that partisans required less and weaker evidence to correctly categorize the ingroup as more honest, and were more accurate on trials when the ingroup candidate was more honest, compared to the outgroup. DDM revealed that such tendencies arise from both a prior preference for categorizing the ingroup as more honest (i.e., biased starting point) and more precise accumulation of information favoring the ingroup candidate compared to the outgroup (i.e., biased drift rate). Moreover, individual differences in cognitive reasoning moderated task performance for the most devoted partisans and maintained divergent associations with the DDM parameters. This suggests that partisans may reach biased conclusions via different pathways depending on their depth of cognitive reasoning. These findings provide key insights into the mechanisms driving partisan divides in polarized environments, and can inform interventions that reduce impasse and conflict.

Partisan-motivated sampling: Re-examining politically motivated reasoning across the information processing stream.

The United States is increasingly politically polarized, fueling intergroup conflict and intensifying partisan biases in cognition and behavior. To date, research on intergroup bias has separately examined biases in how people search for information and how they interpret information. Here, we integrate these two perspectives to elucidate how partisan biases manifest across the information processing stream, beginning with (a) a biased selection of information, leading to (b) skewed samples of information that interact with (c) motivated interpretations to produce evaluative biases. Across three experiments and four internal meta-analyses, participants (N = 2,431) freely sampled information about ingroup and outgroup members or ingroup and outgroup political candidates until they felt confident to evaluate them. Across experiments, we reliably find that most participants begin sampling information from the ingroup, which was associated with individual differences in group-based motives, and that participants sampled overall more information from the ingroup. This sampling behavior, in turn, generates more variability in ingroup (relative to outgroup) experiences. We find that more variability in ingroup experiences predicted when participants decided to stop sampling and was associated with more biased evaluations. We further demonstrate that participants employ different sampling strategies over time when the ingroup is de facto worse-obfuscating Real Group Differences-and that participants selectively integrate their experiences into evaluations based on congeniality. The proposed framework extends classic findings in psychology by demonstrating how biases in sampling behavior interact with motivated interpretations to produce downstream evaluative biases and has implications for intergroup bias interventions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Learning About the Self: Motives for Coherence and Positivity Constrain Learning From Self-Relevant Social Feedback.

People learn about themselves from social feedback, but desires for coherence and positivity constrain how feedback is incorporated into the self-concept. We developed a network-based model of the self-concept and embedded it in a reinforcement-learning framework to provide a computational account of how motivations shape self-learning from feedback. Participants (N = 46 adult university students) received feedback while evaluating themselves on traits drawn from a causal network of trait semantics. Network-defined communities were assigned different likelihoods of positive feedback. Participants learned from positive feedback but dismissed negative feedback, as reflected by asymmetries in computational parameters that represent the incorporation of positive versus negative outcomes. Furthermore, participants were constrained in how they incorporated feedback: Self-evaluations changed less for traits that have more implications and are thus more important to the coherence of the network. We provide a computational explanation of how motives for coherence and positivity jointly constrain learning about the self from feedback, an explanation that makes testable predictions for future clinical research.

Causal Inference Gates Corticostriatal Learning.

Attributing outcomes to your own actions or to external causes is essential for appropriately learning which actions lead to reward and which actions do not. Our previous work showed that this type of credit assignment is best explained by a Bayesian reinforcement learning model which posits that beliefs about the causal structure of the environment modulate reward prediction errors (RPEs) during action value updating. In this study, we investigated the brain networks underlying reinforcement learning that are influenced by causal beliefs using functional magnetic resonance imaging while human participants (n = 31; 13 males, 18 females) completed a behavioral task that manipulated beliefs about causal structure. We found evidence that RPEs modulated by causal beliefs are represented in dorsal striatum, while standard (unmodulated) RPEs are represented in ventral striatum. Further analyses revealed that beliefs about causal structure are represented in anterior insula and inferior frontal gyrus. Finally, structural equation modeling revealed effective connectivity from anterior insula to dorsal striatum. Together, these results are consistent with a possible neural architecture in which causal beliefs in anterior insula are integrated with prediction error signals in dorsal striatum to update action values.SIGNIFICANCE STATEMENT Learning which actions lead to reward-a process known as reinforcement learning-is essential for survival. Inferring the causes of observed outcomes-a process known as causal inference-is crucial for appropriately assigning credit to one's own actions and restricting learning to effective action-outcome contingencies. Previous studies have linked reinforcement learning to the striatum, and causal inference to prefrontal regions, yet how these neural processes interact to guide adaptive behavior remains poorly understood. Here, we found evidence that causal beliefs represented in the prefrontal cortex modulate action value updating in posterior striatum, separately from the unmodulated action value update in ventral striatum posited by standard reinforcement learning models.

Processing of Task-Irrelevant Race Information is Associated with Diminished Cognitive Control in Black and White Individuals.

The race of an individual is a salient physical feature that is rapidly processed by the brain and can bias our perceptions of others. How the race of others explicitly impacts our actions toward them during intergroup contexts is not well understood. In the current study, we examined how task-irrelevant race information influences cognitive control in a go/no-go task in a community sample of Black (n = 54) and White (n = 51) participants. We examined the neural correlates of behavioral effects using functional magnetic resonance imaging and explored the influence of implicit racial attitudes on brain-behavior associations. Both Black and White participants showed more cognitive control failures, as indexed by dprime, to Black versus White faces, despite the irrelevance of race to the task demands. This behavioral pattern was paralleled by greater activity to Black faces in the fusiform face area, implicated in processing face and in-group information, and lateral orbitofrontal cortex, associated with resolving stimulus-response conflict. Exploratory brain-behavior associations suggest different patterns in Black and White individuals. Black participants exhibited a negative association between fusiform activity and response time during impulsive errors to Black faces, whereas White participants showed a positive association between lateral OFC activity and cognitive control performance to Black faces when accounting for implicit racial associations. Together our findings propose that attention to race information is associated with diminished cognitive control that may be driven by different mechanisms for Black and White individuals.

Self-choice preference: The propensity to under-delegate irrespective of sense of control.

People are more likely to make choices themselves than delegate to an agent, even when it may not be the most optimal decision based on a cost-benefit analysis. Previous studies have demonstrated that retaining authority and controllability might be the primary reason for preferring self-choice. The current study asks whether impairment of controllability associated with self-choice can increase the rate of delegation and whether there are self-other discrepancies in self-choice preference. In three studies, we directly manipulated participants' controllability associated with choice through literal instructions (experiment 1) and visual presentation (experiments 2 and 3). We found that participants showed a robust propensity to under-delegate even when they were aware of their impaired controllability associated with self-choice. Moreover, only 40% impairment of controllability (but not 20%) can decrease the propensity to under-delegate. This trend differed between decision-for-self and decision-for-other. These findings suggest that pursuing a sense of control cannot fully explain self-choice preference and appears to occur equally in decisions for oneself as well as for others.

Neural adaptation to faces reveals racial outgroup homogeneity effects in early perception.

A hallmark of intergroup biases is the tendency to individuate members of one's own group but process members of other groups categorically. While the consequences of these biases for stereotyping and discrimination are well-documented, their early perceptual underpinnings remain less understood. Here, we investigated the neural mechanisms of this effect by testing whether high-level visual cortex is differentially tuned in its sensitivity to variation in own-race versus other-race faces. Using a functional MRI adaptation paradigm, we measured White participants' habituation to blocks of White and Black faces that parametrically varied in their groupwise similarity. Participants showed a greater tendency to individuate own-race faces in perception, showing both greater release from adaptation to unique identities and increased sensitivity in the adaptation response to physical difference among faces. These group differences emerge in the tuning of early face-selective cortex and mirror behavioral differences in the memory and perception of own- versus other-race faces. Our results suggest that biases for other-race faces emerge at some of the earliest stages of sensory perception.

Neurocomputational mechanisms underlying motivated seeing.

People tend to believe that their perceptions are veridical representations of the world, but also commonly report perceiving what they want to see or hear. It remains unclear whether this reflects an actual change in what people perceive or merely a bias in their responding. Here we manipulated the percept that participants wanted to see as they performed a visual categorization task. Even though the reward-maximizing strategy was to perform the task accurately, the manipulation biased participants' perceptual judgements. Motivation increased neural activity selective for the motivationally relevant category, indicating a bias in participants' neural representation of the presented image. Using a drift diffusion model, we decomposed motivated seeing into response and perceptual components. Response bias was associated with anticipatory activity in the nucleus accumbens, whereas perceptual bias tracked category-selective neural activity. Our results provide a computational description of how the drive for reward leads to inaccurate representations of the world.

Causal Inference About Good and Bad Outcomes.

People learn differently from good and bad outcomes. We argue that valence-dependent learning asymmetries are partly driven by beliefs about the causal structure of the environment. If hidden causes can intervene to generate bad (or good) outcomes, then a rational observer will assign blame (or credit) to these hidden causes, rather than to the stable outcome distribution. Thus, a rational observer should learn less from bad outcomes when they are likely to have been generated by a hidden cause, and this pattern should reverse when hidden causes are likely to generate good outcomes. To test this hypothesis, we conducted two experiments ( N = 80, N = 255) in which we explicitly manipulated the behavior of hidden agents. This gave rise to both kinds of learning asymmetries in the same paradigm, as predicted by a novel Bayesian model. These results provide a mechanistic framework for understanding how causal attributions contribute to biased learning.

Social Rewards: From Basic Social Building Blocks to Complex Social Behavior.

Humans are social creatures, engaging almost constantly in social behaviors that serve ultimate social goals, such as forming strong bonds with one another. However, most social behaviors provide only incremental progress toward an ultimate goal. Instead, the drive to engage in any individual social act may derive from its proximal value rather than its ultimate goal. Thus, this proximal value forms the foundation on which the complexities of human sociality are built. We describe two complementary approaches for using proximal social rewards to understand social behaviors and their ultimate goals: (a) decontextualizing social rewards-paring down complex social interactions can help identify which basic building blocks remain valuable even in minimalistic contexts-and (b) recontextualizing social rewards-reintroducing motivational and contextual factors into the study of social experience can help identify how proximal rewards serve their ultimate function. We discuss how this dual-approach framework can inform future research by bridging basic social building blocks and real-world social goals.

Perceiving groups: The people perception of diversity and hierarchy.

The visual perception of individuals has received considerable attention (visual person perception), but little social psychological work has examined the processes underlying the visual perception of groups of people (visual people perception). Ensemble-coding is a visual mechanism that automatically extracts summary statistics (e.g., average size) of lower-level sets of stimuli (e.g., geometric figures), and also extends to the visual perception of groups of faces. Here, we consider whether ensemble-coding supports people perception, allowing individuals to form rapid, accurate impressions about groups of people. Across nine studies, we demonstrate that people visually extract high-level properties (e.g., diversity, hierarchy) that are unique to social groups, as opposed to individual persons. Observers rapidly and accurately perceived group diversity and hierarchy, or variance across race, gender, and dominance (Studies 1-3). Further, results persist when observers are given very short display times, backward pattern masks, color- and contrast-controlled stimuli, and absolute versus relative response options (Studies 4a-7b), suggesting robust effects supported specifically by ensemble-coding mechanisms. Together, we show that humans can rapidly and accurately perceive not only individual persons, but also emergent social information unique to groups of people. These people perception findings demonstrate the importance of visual processes for enabling people to perceive social groups and behave effectively in group-based social interactions. (PsycINFO Database Record

Trusting outgroup, but not ingroup members, requires control: neural and behavioral evidence.

Trust and cooperation often break down across group boundaries, contributing to pernicious consequences, from polarized political structures to intractable conflict. As such, addressing such conflicts require first understanding why trust is reduced in intergroup settings. Here, we clarify the structure of intergroup trust using neuroscientific and behavioral methods. We found that trusting ingroup members produced activity in brain areas associated with reward, whereas trusting outgroup members produced activity in areas associated with top-down control. Behaviorally, time pressure-which reduces people's ability to exert control-reduced individuals' trust in outgroup, but not ingroup members. These data suggest that the exertion of control can help recover trust in intergroup settings, offering potential avenues for reducing intergroup failures in trust and the consequences of these failures.

Motivation alters impression formation and related neural systems.

Observers frequently form impressions of other people based on complex or conflicting information. Rather than being objective, these impressions are often biased by observers' motives. For instance, observers often downplay negative information they learn about ingroup members. Here, we characterize the neural systems associated with biased impression formation. Participants learned positive and negative information about ingroup and outgroup social targets. Following this information, participants worsened their impressions of outgroup, but not ingroup, targets. This tendency was associated with a failure to engage neural structures including lateral prefrontal cortex, dorsal anterior cingulate cortex, temporoparietal junction, Insula and Precuneus when processing negative information about ingroup (but not outgroup) targets. To the extent that participants engaged these regions while learning negative information about ingroup members, they exhibited less ingroup bias in their impressions. These data are consistent with a model of 'effortless bias', under which perceivers fail to process goal-inconsistent information in order to maintain desired conclusions.

Power Heightens Sensitivity to Unfairness Against the Self.

Power is accompanied by a sense of entitlement, which shapes reactions to self-relevant injustices. We propose that powerful people more strongly expect to be treated fairly and are faster to perceive unjust treatment that violates these expectations. After preliminary data demonstrated that power leads people to expect fair outcomes for themselves, we conducted four experiments. Participants primed with high (vs. low) power were faster to identify violations of distributive justice in which they were victims (Study 1). This effect was specific to self-relevant injustices (Study 2) and generalized to violations of interpersonal justice (Study 3). Finally, participants primed with high power were more likely to take action against unfair treatment (Study 4). These findings suggest a process by which hierarchies may be maintained: Whereas the powerless are comparatively less sensitive to unfair treatment, the powerful may retain their social standing by quickly perceiving and responding to self-relevant injustices.

The neuroscience of motivated cognition.

Goals and needs shape individuals' thinking, a phenomenon known as motivated cognition. We highlight research from social psychology and cognitive neuroscience that provides insight into the structure of motivated cognition. In addition to demonstrating its ubiquity, we suggest that motivated cognition is often effortless and pervades information processing.

Common representation of pain and negative emotion in the midbrain periaqueductal gray.

Human neuroimaging offers a powerful way to connect animal and human research on emotion, with profound implications for psychological science. However, the gulf between animal and human studies remains a formidable obstacle: human studies typically focus on the cortex and a few subcortical regions such as the amygdala, whereas deeper structures such as the brainstem periaqueductal gray (PAG) play a key role in animal models. Here, we directly assessed the role of PAG in human affect by interleaving in a single fMRI session two conditions known to elicit strong emotional responses--physical pain and negative image viewing. Negative affect and PAG activity increased in both conditions. We next examined eight independent data sets, half featuring pain stimulation and half negative image viewing. In sum, these data sets comprised 198 additional participants. We found increased activity in PAG in all eight studies. Taken together, these findings suggest PAG is a key component of human affective responses.

Protecting the self: the effect of social-evaluative threat on neural representations of self.

One of the most robust ways that people protect themselves from social-evaluative threat is by emphasizing the desirability of their personal characteristics, yet the neural underpinnings of this fundamental process are unknown. The current fMRI study addresses this question by examining self-evaluations of desirability (in comparison with other people) as a response to threat. Participants judged how much personality traits described themselves in comparison with their average peer. These judgments were preceded by threatening or nonthreatening social-evaluative feedback. Self-evaluations made in response to threat significantly increased activation in a number of regions including the OFC, medial pFC, lateral pFC, amygdala, and insula. Individual differences in the extent to which threat increased desirability were significantly correlated with medial OFC activity. This is the first study to examine the neural associations of a fundamental self-protection strategy: responding to threat by emphasizing the self's desirability. Although neural research has separately examined self-evaluation processes from the regulation of social-evaluative threat, little is known about the interplay between the two. The findings build on this previous research by showing that regions, often associated with self-evaluation, are modulated by the degree to which people respond to threat by emphasizing their own desirability.