Leor M. Hackel

Instrumental learning of traits versus rewards: dissociable neural correlates and effects on choice

Humans learn about people and objects through positive and negative experiences, yet they can also look beyond the immediate reward of an interaction to encode trait-level attributes. We found that perceivers encoded both reward and trait-level information through feedback in an instrumental learning task, but relied more heavily on trait representations in cross-context decisions. Both learning types implicated ventral striatum, but trait learning also recruited a network associated with social impression formation.

The Group Mind: The Pervasive Influence of Social Identity on Cognition

Humans evolved in social groups and are adapted for group living. In this chapter, we review recent behavioral, physiological, and neuroscience research that provides the psychological and neural architecture for collectively shared representations of the world – the “group mind.” We describe how collective identities structure a wide range of human cognitive processes, from rapid evaluation and face memory to mental state attribution and representations of physical distance. This research underscores how psychological and neural processes underlying human cognition are context-dependent, dynamic, and flexibly shaped by motivational states, rather than inevitable, reflexive, and fixed.

Social identity shapes social valuation: Evidence from prosocial behavior and vicarious reward

Abstract People frequently engage in more prosocial behavior toward members of their own groups, as compared to other groups. Such group-based prosociality may reflect either strategic considerations concerning ones own future outcomes or intrinsic value placed on the outcomes of in-group members. In a functional magnetic resonance imaging experiment, we examined vicarious reward responses to witnessing the monetary gains of in-group and out-group members, as well as prosocial behavior towards both types of individuals. We found that individuals’ investment in their group—a motivational component of social identification—tracked the intensity of their responses in ventral striatum to in-group (vs out-group) members’ rewards, as well as their tendency towards group-based prosociality. Individuals with strong motivational investment in their group preferred rewards for an in-group member, whereas individuals with low investment preferred rewards for an out-group member. These findings suggest that the motivational importance of social identity—beyond mere similarity to group members—influences vicarious reward and prosocial behavior. More broadly, these findings support a theoretical framework in which salient social identities can influence neural representations of subjective value, and suggest that social preferences can best be understood by examining the identity contexts in which they unfold.

Propagation of Economic Inequality Through Reciprocity and Reputation

Reciprocity and reputation are powerful tools for encouraging cooperation on a broad scale. Here, we highlight a potential side effect of these social phenomena: exacerbating economic inequality. In two novel economic games, we manipulated the amount of money with which participants were endowed and then gave them the opportunity to share resources with others. We found that people reciprocated more toward higher-wealth givers, compared with lower-wealth givers, even when those givers were equally generous. Wealthier givers also achieved better reputations than less wealthy ones and therefore received more investments in a social marketplace. These discrepancies were well described by a formal model of reinforcement learning: Individuals who weighted monetary outcomes, rather than generosity, when learning about interlocutors also most strongly helped wealthier individuals. This work demonstrates that reciprocity and reputation—although globally increasing prosociality—can widen wealth gaps and provides a precise account of how inequality grows through social processes.

Social identity shapes social perception and evaluation: Using neuroimaging to look inside the social brain

On February 26, 2012, 17-year-old Trayvon Martin was shot and killed by neighborhood watch captain George Zimmerman—who thought the teenager looked suspicious—sparking a national outrage and discussion about race in the United States. Why had an innocent, unarmed African American teenager died on his way home? In the aftermath, some sought answers not in explicit racism and prejudice, but rather in the domain of implicit racism—arguing, as two social psychologists wrote in an op-ed (newspaper opinion piece), that “our minds are colored by race” (Goff & Richardson, 2012, n.p.). According to a standard dual process account developed over the last 25 years, the implicit effects of race that colored George Zimmerman’s mind that night were sadly predictable. Seeing a Black face would likely trigger automatic negative evaluations and associations for Mr. Zimmerman, regardless of his explicit beliefs about race (see Devine, 1989). Moreover, due to his inexperience with Black faces, he may have failed to see Mr. Martin as an individual, but rather merely as an interchangeable member of the social category “African American.” According to the standard dual process account, these events took place automatically and inevitably, triggered in a reflex-like manner by the salient visual cue of race. However, in this chapter, we provide evidence that the psychological and neural processes underlying person perception are context-dependent, dynamic, and shaped by motivational states, rather than inevitable, reflexive, and predictable. Specifically, we review research showing that self-categorization and social identity structure social perception and evaluation. Self-categorization involves the activation of psychological connections between the self and some class of stimuli at the personal (i.e., defining oneself as unique from others) or collective (i.e., defining oneself in terms of similar characteristics to one’s social group) level (Turner, Hogg, Oakes, Reicher, & Wetherell, 1987; Turner, Oakes, Haslam, & McGarty, 1994). 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43Introduction and Overview. Part 1: Social Categorization: Responding to Others as Us vs. Them. T. Ito, The Neural Correlates of Social Categorization. B. Derks, Social Identity and Automatic Social Categorization. M. Zarate, Cerebral Hemispheric Asymmetries in Social Perception: Perceiving People as Individuals or Group Members. Part 2: From Identification to Intergroup Behavior. D. Scheepers, Social Identity Based Challenge and Threat. C. de Dreu, Oxytocin Promotes Intergroup Competition. S. Fiske, Social Neuroscience Evidence for Dehumanized Perception. Part 3: From Prejudice to Control. D. Amodio, Neural Mechanisms Underlying Prejudice Control. J. Richeson, How Interracial Interactions Deplete Attentional Resources. B. Bartholow, Stereotype Activation and Control of Race Bias: Cognitive Control of Inhibition and its Impairment by Alcohol. Part 4: The Targets Perspective: Physiological Responses to Stigma. J. Blascovich, Challenge and Threat in Response to Stigma. B. Major, Worldview Disconfirmation is Stressful: Threat vs. Challenge in Response to Low Status. M. Inzlicht, Stigma Impairs the Neural Mechanisms Underlying Self-control. Part 5: Improving Inter-group Relations. W. Berry Mendes, Neuro-endocrine Stress Responses during Inter-group Interactions. N. Ellemers, Moral Accountability and Control of Implicit Prejudice. R. Mendoza-Denton, How Cross-racial Friendships Reduce Interracial Anxiety.

Frontal cortical effects on feedback processing and reinforcement learning: Relation of EEG asymmetry with the feedback-related negativity and behavior

Reinforcement learning refers to the acquisition of approach or avoidance action tendencies through repeated reward/nonreward feedback. Although much research on reinforcement learning has focused on the striatum, the prefrontal cortex likely modulates this process. Given prior research demonstrating a consistent pattern of lateralized frontal cortical activity in affective responses and approach/avoidance tendencies in the EEG literature, we aimed to elucidate the role of frontal EEG asymmetry in reinforcement learning. Thirty-two participants completed a probabilistic selection task in which they learned to select some targets and avoid others though correct/incorrect feedback. EEG indices of frontal cortical asymmetry were computed from alpha power recorded at baseline and during task completion. We also examined the feedback-related negativity ERP component to assess feedback processing associated with activity in the dorsal anterior cingulate cortex. Results revealed that greater right-lateralized frontal cortical activity during learning was associated with better avoidance learning, but neither left- nor right-sided asymmetry reliably related to approach learning. Results also suggested that left frontal activity may relate to reinforcement feedback processing, as indicated by the feedback-related negativity (FRN). These findings offer preliminary evidence regarding the role of frontal cortical activity in reinforcement learning while integrating classic and contemporary research on lateralized frontal cortical functions.

On the neural implausibility of the modular mind: Evidence for distributed construction dissolves boundaries between perception, cognition, and emotion

Firestone & Scholl (F&S) rely on three problematic assumptions about the mind (modularity, reflexiveness, and context-insensitivity) to argue cognition does not fundamentally influence perception. We highlight evidence indicating that perception, cognition, and emotion are constructed through overlapping, distributed brain networks characterized by top-down activity and context-sensitivity. This evidence undermines F&Ss ability to generalize from case studies to the nature of perception.

Computational neuroscience approaches to social cognition

How do we form impressions of people and groups and use these representations to guide our actions? From its inception, social neuroscience has sought to illuminate such complex forms of social cognition, and recently these efforts have been invigorated by the use of computational modeling. Computational modeling provides a framework for delineating specific processes underlying social cognition and relating them to neural activity and behavior. We provide a primer on the computational modeling approach and describe how it has been used to elucidate psychological and neural mechanisms of impression formation, social learning, moral decision making, and intergroup bias.

My Brain Contains Multitudes: The Value of a Flexible Approach to Identity

Humans value our identities as individuals and as members of groups: We feel a sense of meaning when we construct our life stories (McAdams, 2001) and a sense of belonging when we lose ourselves in a collective (Baumeister & Leary, 1995; Brewer, 1991). Yet it has long remained unclear how this value is represented in the brain. Meanwhile, in the last two decades, a robust research literature has characterized the computations by which the brain represents, learns about, and uses a common currency of value to guide decisions about diverse goods (Chib, Rangel, Shimojo, & O’Doherty, 2009; Hare, O’Doherty, Camerer, Schultz, & Rangel, 2008; Kable & Glimcher, 2009; Rangel, Camerer, & Montague, 2008). Yet this work has tended to focus on material gains, such as money, food, or possessions. By fitting these ideas together in the identity-value model (IVM), Elliot T. Berkman, Jordan L. Livingston, and Lauren E. Kahn (this issue) offer a powerful approach for understanding how the brain uses identity to guide behavior. Valuation can serve as a bridge between abstract social motives and neural computation: To the extent that people find identity motivationally meaningful, identity should influence neural representations of value within a common currency (Levy & Glimcher, 2012; Ruff & Fehr, 2014). At the same time, the IVM assumes that identity is, on the whole, a “relatively stable mental representation of the self” (p. 79). Berkman and colleagues acknowledge that identity (or aspects of it) can be somewhat malleable but assume that identity is broadly stable enough to have a consistent impact on valuation across settings. Here, we suggest that this assumption may not hold true when considering people’s identification with social groups—termed social identification. Social identification involves defining oneself as part of a group and feeling invested in that group (Leach et al., 2008; Tajfel & Turner, 1979; Turner, Oakes, Haslam, & McGarty, 1994). Social groups play an important role in people’s lives: Groups provide access to material and social resources (Brewer, 1988; Correll & Park, 2005), promote a sense of belonging (Baumeister & Leary, 1995; Brewer, 1991), and reduce people’s uncertainty about how to act (Hogg, 2000). As a result, people are more motivated by and willing to pay for outcomes that fulfill the norms of their groups (Akerlof & Kranton, 2000; Oyserman, Fryberg, & Yoder, 2007). These insights suggest that social identities can alter value representations—an insight included in the IVM. However, we elucidate three ways in which social identities are highly flexible, suggesting that identity can impact value in different ways across contexts. We suggest expanding the IVM to give social identity a more central role, and in doing so to account for these forms of flexibility.

Power Effects on Instrumental Learning: Evidence From the Brain and Behavior.

We investigated whether high power facilitates instrumental learning relative to low power—an effect that would support power effects on goal-pursuit and decision-making. Because power is known to increase instrumentality in action, we expected that high power would enhance instrumental learning involving both approach and avoidance responses, relative to low power. Studies 1 and 2 revealed that manipulated power modulated instrumental learning, such that relative to low power, high power facilitated the learning of approach and avoidance responses through reinforcement. Furthermore, Study 2 revealed stronger neural processing of valid versus invalid feedback, indexed by the feedback-related negativity (FRN) component of the event-related potential (ERP), among high-power participants, but not low-power or control participants. These results suggest higher power engaged more strategic processing of goal-relevant feedback—a finding that illuminates the links between power, goal pursuit, and social behavior.