Cognitive regulation alters social and dietary choice by changing attribute representations in domain-general and domain-specific brain circuits

Regulation of craving training to support healthy food choices under stress: A randomized control trial employing the hierarchical drift-diffusion model

Stress increases the likelihood of consuming unhealthy food in some individuals. Previous research has demonstrated that the Regulation of Craving - Training (ROC-T) intervention can reduce unhealthy food intake. However, its effectiveness under stress and the underlying mechanism remained uncertain. This study aimed to assess the efficacy of the ROC-T intervention in improving healthy food choices and to explore the intervention mechanism through computational modeling employing the hierarchical drift-diffusion model (HDDM). This study adopted a 2 (ROC-T intervention vs. control) * 2 (stress vs. no-stress) between-subject experimental design. A total of 118 employees (72 women, Mage = 28.74) participated in the online experiment. Results show that the ROC-T intervention increases healthy food choices under stress and no-stress conditions. The HDDM results reveal a significant two-way interaction for non-decision time (Bayes factor, BF = 32.722) and initial bias (BF = 27.350). Specifically, in the no-stress condition, the ROC-T intervention resulted in lower non-decision time and higher initial bias compared with the control group. The findings validated the negative impact of stress on healthy food choices, and that the ROC-T intervention promotes healthy food choices both under stress and no-stress conditions.

Acute stress during witnessing injustice shifts third-party interventions from punishing the perpetrator to helping the victim

People tend to intervene in others' injustices by either punishing the transgressor or helping the victim. Injustice events often occur under stressful circumstances. However, how acute stress affects a third party's intervention in injustice events remains open. Here, we show a stress-induced shift in third parties' willingness to engage in help instead of punishment by acting on emotional salience and central-executive and theory-of-mind networks. Acute stress decreased the third party's willingness to punish the violator and the severity of the punishment and increased their willingness to help the victim. Computational modeling revealed a shift in preference of justice recovery from punishment the offender toward help the victim under stress. This finding is consistent with the increased dorsolateral prefrontal engagement observed with higher amygdala activity and greater connectivity with the ventromedial prefrontal cortex in the stress group. A brain connectivity theory-of-mind network predicted stress-induced justice recovery in punishment. Our findings suggest a neurocomputational mechanism of how acute stress reshapes third parties' decisions by reallocating neural resources in emotional, executive, and mentalizing networks to inhibit punishment bias and decrease punishment severity.

Body mass index-dependent shifts along large-scale gradients in human cortical organization explain dietary regulatory success

Making healthy dietary choices is essential for keeping weight within a normal range. Yet many people struggle with dietary self-control despite good intentions. What distinguishes neural processing in those who succeed or fail to implement healthy eating goals? Does this vary by weight status? To examine these questions, we utilized an analytical framework of gradients that characterize systematic spatial patterns of large-scale neural activity, which have the advantage of considering the entire suite of processes subserving self-control and potential regulatory tactics at the whole-brain level. Using an established laboratory food task capturing brain responses in natural and regulatory conditions (N = 123), we demonstrate that regulatory changes of dietary brain states in the gradient space predict individual differences in dietary success. Better regulators required smaller shifts in brain states to achieve larger goal-consistent changes in dietary behaviors, pointing toward efficient network organization. This pattern was most pronounced in individuals with lower weight status (low-BMI, body mass index) but absent in high-BMI individuals. Consistent with prior work, regulatory goals increased activity in frontoparietal brain circuits. However, this shift in brain states alone did not predict variance in dietary success. Instead, regulatory success emerged from combined changes along multiple gradients, showcasing the interplay of different large-scale brain networks subserving dietary control and possible regulatory strategies. Our results provide insights into how the brain might solve the problem of dietary control: Dietary success may be easier for people who adopt modes of large-scale brain activation that do not require significant reconfigurations across contexts and goals.

A neurocomputational account of the link between social perception and social action

People selectively help others based on perceptions of their merit or need. Here, we develop a neurocomputational account of how these social perceptions translate into social choice. Using a novel fMRI social perception task, we show that both merit and need perceptions recruited the brain's social inference network. A behavioral computational model identified two non-exclusive mechanisms underlying variance in social perceptions: a consistent tendency to perceive others as meritorious/needy (bias) and a propensity to sample and integrate normative evidence distinguishing high from low merit/need in other people (sensitivity). Variance in people's merit (but not need) bias and sensitivity independently predicted distinct aspects of altruism in a social choice task completed months later. An individual's merit bias predicted context-independent variance in people's overall other-regard during altruistic choice, biasing people towards prosocial actions. An individual's merit sensitivity predicted context-sensitive discrimination in generosity towards high and low merit recipients by influencing other-regard and self-regard during altruistic decision-making. This context-sensitive perception-action link was associated with activation in the right temporoparietal junction. Together, these findings point towards stable, biologically based individual differences in perceptual processes related to abstract social concepts like merit, and suggest that these differences may have important behavioral implications for an individual's tendency toward favoritism or discrimination in social settings.

Pupil Size Sensitivity to Listening Demand Depends on Motivational State

Motivation plays a role when a listener needs to understand speech under acoustically demanding conditions. Previous work has demonstrated pupil-linked arousal being sensitive to both listening demands and motivational state during listening. It is less clear how motivational state affects the temporal evolution of the pupil size and its relation to subsequent behavior. We used an auditory gap detection task (N = 33) to study the joint impact of listening demand and motivational state on the pupil size response and examine its temporal evolution. Task difficulty and a listener's motivational state were orthogonally manipulated through changes in gap duration and monetary reward prospect. We show that participants' performance decreased with task difficulty, but that reward prospect enhanced performance under hard listening conditions. Pupil size increased with both increased task difficulty and higher reward prospect, and this reward prospect effect was largest under difficult listening conditions. Moreover, pupil size time courses differed between detected and missed gaps, suggesting that the pupil response indicates upcoming behavior. Larger pre-gap pupil size was further associated with faster response times on a trial-by-trial within-participant level. Our results reiterate the utility of pupil size as an objective and temporally sensitive measure in audiology. However, such assessments of cognitive resource recruitment need to consider the individual's motivational state.

A neural signature of social support mitigates negative emotion

Social support can mitigate the impact of distressing events. Such stress buffering elicits activity in many brain regions, but it remains unclear (1) whether this activity constitutes a stable brain signature, and (2) whether brain activity can predict buffering across people. Here, we developed a neural signature that predicted social buffering of negative emotion in response to real life stressors. During neuroimaging, participants (n = 95) responded to stressful autobiographical memories either naturally, or by imagining a conversation with a peer. Using supervised dimensionality reduction and machine learning techniques, we identified a spatio-temporal neural signature that distinguished between these two trials. Activation of this signature was associated with less negative affect across trials, and people who most activated the signature reported more supportive social connections and lower loneliness outside the lab. Together, this work provides a behaviorally relevant neurophysiological marker for social support that underlies stress buffering.

Higher subjective socioeconomic status is linked to increased charitable giving and mentalizing-related neural value coding

Socioeconomic status (SES), a concept related to an individual's economic and social position relative to others, can shape social interactions like altruistic behaviors. However, little is known about the exact neurocognitive mechanisms that link SES with altruism. Our study aimed to provide a comprehensive account of the sociocognitive and neural mechanisms through which SES affects charitable giving - an important variant of human altruism. To this end, participants completed a charitable donation task while their brain activity was measured using functional magnetic resonance imaging (fMRI). We also assessed participants' socio-cognitive ability to infer other people's mental states (i.e., mentalizing) - a driver of prosocial behavior - in an independent social task. Behaviorally, we found that both charitable giving and social cognition were status-dependent, as subjective SES positively predicted donations and mentalizing capacity. Moreover, the link between SES and charitable giving was mediated by individuals' mentalizing capacity. At the neural level, a multivariate pattern analysis of fMRI data revealed that higher subjective SES was associated with stronger value coding in the right temporoparietal junction (rTPJ). The strength of this value representation predicted charitable giving and was linked to mentalizing. Furthermore, we observed an increased negative functional coupling between rTPJ and left putamen with higher SES. Together, increased charitable giving in higher-status individuals could be explained by status-dependent recruitment of mentalizing-related value coding and altered functional connectivity in the brain. Our findings provide insights into the socio- and neurocognitive mechanisms explaining why and when higher SES leads to prosociality, which might ultimately inform targeted interventions to promote prosocial behavior in human societies.

Neural signatures of social inferences predict the number of real-life social contacts and autism severity

We regularly infer other people's thoughts and feelings from observing their actions, but how this ability contributes to successful social behavior and interactions remains unknown. We show that neural activation patterns during social inferences obtained in the laboratory predict the number of social contacts in the real world, as measured by the social network index, in three neurotypical samples (total n = 126) and one sample of autistic adults (n = 23). We also show that brain patterns during social inference generalize across individuals in these groups. Cross-validated associations between brain activations and social inference localize selectively to the right posterior superior temporal sulcus and were specific for social, but not nonsocial, inference. Activation within this same brain region also predicts autism-like trait scores from questionnaires and autism symptom severity. Thus, neural activations produced while thinking about other people's mental states predict variance in multiple indices of social functioning in the real world.

Deliberative control is more than just reactive: Insights from sequential sampling models

Activating relevant responses is a key function of automatic processes in De Neys's model; however, what determines the order or magnitude of such activation is ambiguous. Focusing on recently developed sequential sampling models of choice, we argue that proactive control shapes response generation but does not cleanly fit into De Neys's automatic-deliberative distinction, highlighting the need for further model development.

Recruitment of dlPFC during dietary self-regulation predicts the transience of regulatory effects

Recent work on the cognitive regulation of dietary decision-making suggests that regulation can alter both the choices that people make in the moment and longer-lasting preferences. However, it is unclear what mechanisms lead to temporary or lingering changes. To address this question, we used fMRI during a task employing the cognitive regulation of food choice and assessed changes in food preference from baseline to post-regulation. We found evidence that regulation may result in a temporary reconfiguration of the neural drivers of choice, de-emphasizing goal-inconsistent value-related computations in the ventromedial prefrontal cortex and resulting in more goal-consistent changes in value-related computations in the dorsolateral prefrontal cortex (dlPFC). Moreover, we find that the extent to which the dlPFC was recruited to represent different regulatory goals during the moment of choice negatively predicted the extent to which those regulatory goals produced lingering changes in preference. Our results suggest that the recruitment of the dlPFC in the service of regulation may have a downside: it is effective at changing behavior in the moment, but its effects on preferences are transient.

Thinking more or thinking differently? Using drift-diffusion modeling to illuminate why accuracy prompts decrease misinformation sharing

Recent experiments have found that prompting people to think about accuracy reduces misinformation sharing intentions. The process by which this effect operates, however, remains unclear. Do accuracy prompts cause people to "stop and think," increasing deliberation? Or do they change what people think about, drawing attention to accuracy? Since these two accounts predict the same behavioral outcomes (i.e., increased sharing discernment following a prompt), we used computational modeling of sharing decisions with response time data, as well as out-of-sample ratings of headline perceived accuracy, to test the accounts' divergent predictions across six studies (N = 5633). The results suggest that accuracy prompts do not increase the amount of deliberation people engage in. Instead, they increase the weight participants put on accuracy while deliberating. By showing that prompting people makes them think better even without thinking more, our results challenge common dual-process interpretations of the accuracy-prompt effect. Our findings also highlight the importance of understanding how social media distracts people from considering accuracy, and provide evidence for scalable interventions that redirect people's attention.

A computational account of how individuals resolve the dilemma of dirty money

Money can be tainted when it is associated with direct or indirect harm to others. Deciding whether to accept "dirty money" poses a dilemma because money can be used to help others, but accepting dirty money has moral costs. How people resolve the dilemma of dirty money remains unknown. One theory casts the dilemma as a valuation conflict that can be resolved by integrating the costs and benefits of accepting dirty money. Here, we use behavioral experiments and computational modeling to test the valuation conflict account and unveil the cognitive computations employed when deciding whether to accept or reject morally tainted cash. In Study 1, British participants decided whether to accept "dirty" money obtained by inflicting electric shocks on another person (versus "clean" money obtained by shocking oneself). Computational models showed that the source of the money (dirty versus clean) impacted decisions by shifting the relative valuation of the money's positive and negative attributes, rather than imposing a uniform bias on decision-making. Studies 2 and 3 replicate this finding and show that participants were more willing to accept dirty money when the money was directed towards a good cause, and observers judged such decisions to be more praiseworthy than accepting dirty money for one's own profit. Our findings suggest that dirty money can be psychologically "laundered" through charitable activities and have implications for understanding and preventing the social norms that can justify corrupt behavior.

Evidence accumulation, not 'self-control', explains dorsolateral prefrontal activation during normative choice

What role do regions like the dorsolateral prefrontal cortex (dlPFC) play in normative behavior (e.g., generosity, healthy eating)? Some models suggest that dlPFC activation during normative choice reflects controlled inhibition or modulation of default hedonistic preferences. Here, we develop an alternative account, showing that evidence accumulation models predict trial-by-trial variation in dlPFC response across three fMRI paradigms and two self-control contexts (altruistic sacrifice and healthy eating). Using these models to simulate a variety of self-control dilemmas generated a novel prediction: although dlPFC activity might typically increase for norm-consistent choices, deliberate self-regulation focused on normative goals should decrease or even reverse this pattern (i.e., greater dlPFC response for hedonistic, self-interested choices). We confirmed these predictions in both altruistic and dietary choice contexts. Our results suggest that dlPFC response during normative choice may depend more on value-based evidence accumulation than inhibition of our baser instincts.

An fMRI study of cognitive regulation of reward processing in generalized anxiety disorder (GAD)

BACKGROUND

Cognitive regulation can affect the process of decision making. Generalized anxiety disorder (GAD) patients seem to have an impairment in cognitive regulation of reward processing concerning food stimuli. This study aims to explore the impact of GAD in cognitive regulation of food-related rewards.

METHODS

GAD patients (n=11) and healthy controls (n=15) performed a cognitive regulation craving task with food images while undergoing a functional magnetic resonance imaging (fMRI) acquisition. Between-group differences in functional connectivity were measured using dorsolateral prefrontal cortex (dlPFC) and ventromedial prefrontal cortex (vmPFC) seeds during cognitive regulation.

RESULTS

During cognitive regulation, there was a significant interaction for functional connectivity between the right dlPFC and bilateral vmPFC with the thalamus. GAD patients had lower functional connectivity for cognitive regulation conditions (distance and indulge) than for the non-regulated condition in these clusters, while control participants presented the opposite pattern. GAD group presented fixed food valuation scores after cognitive regulation.

CONCLUSIONS

GAD participants showed inflexibility while valuating food images, that could be produced by cognitive regulation deficits underpinned by functional connectivity alterations between prefrontal regions and the thalamus. These results show cognitive inflexibility and difficulty in the modulation of cognitive responses during decision making in GAD patients.

Negative Affect, Affect Regulation, and Food Choice: A Value-Based Decision-Making Analysis

Maladaptive eating is one of the greatest threats to health and well-being in the 21st century. Psychological factors that drive maladaptive eating are of interest as they may offer low-cost intervention targets. One such factor is negative affect. If negative affect does lead to maladaptive eating, interventions that reduce negative affect should lead to improved eating and food choice. One relevant class of techniques is affect regulation strategies. In the present research, we use survey data and a value-based decision-making task to demonstrate that negative affect is associated with maladaptive eating and food choice. We find that negative affect decreases the weight that participants place on the health benefits of food. We also show that teaching participants to use reappraisal to downregulate negative affect leads to healthier food choices. These findings indicate that reappraisal applied to incidental negative affect may be an effective method for improving eating and food choice.

Distinctive roles of mPFC subregions in forming impressions and guiding social interaction based on others' social behaviour

People can quickly form impressions of others from their social behaviour, which can guide their future social interactions. This study investigated how the type and timing of others' social decisions affect the impression formation and social interactions. In each trial, participants watched a responder's decision in an ultimatum game, decided whether to choose the responder as their next partner for proposer or responder and reported the perceived warmth, competence and likability of the responder. Participants preferred responders who accepted (i.e. accepters) unfair offers for the responder and those who rejected (i.e. rejecters) unfair offers for the proposer in their next ultimatum game, and the rostral medial prefrontal cortex (mPFC) activity encoded such a strategic context-dependent valuation when choosing partners. Slow rejecters were perceived as warmer than fast rejecters, which was mirrored by the anterior mid-cingulate cortex activity when watching others' decisions, possibly detecting and resolving conflicting impressions. Finally, those who perceived accepters vs rejecters as warmer showed higher ventral mPFC responses to accepters vs rejecters when choosing a partner, regardless of the context. The present study suggests that distinctive subregions of the mPFC may be differentially involved in forming impressions and guiding social interactions with others based on their social behaviours.

Temporal dynamics of decision making: A synthesis of computational and neurophysiological approaches

As interest in the temporal dynamics of decision-making has grown, researchers have increasingly turned to computational approaches such as the drift diffusion model (DDM) to identify how cognitive processes unfold during choice. At the same time, technological advances in noninvasive neurophysiological methods such as electroencephalography and magnetoencephalography now allow researchers to map the neural time course of decision making with millisecond precision. Combining these approaches can potentially yield important new insights into how choices emerge over time. Here we review recent research on the computational and neurophysiological correlates of perceptual and value-based decision making, from DDM parameters to scalp potentials and oscillatory neural activity. Starting with motor response preparation, the most well-understood aspect of the decision process, we discuss evidence that urgency signals and shifts in baseline activation, rather than shifts in the physiological value of the choice-triggering response threshold, are responsible for adjusting response times under speeded choice scenarios. Research on the neural correlates of starting point bias suggests that prestimulus activity can predict biases in motor choice behavior. Finally, studies examining the time dynamics of evidence construction and evidence accumulation have identified signals at frontocentral and centroparietal electrodes associated respectively with these processes, emerging 300-500 ms after stimulus onset. These findings can inform psychological theories of decision-making, providing empirical support for attribute weighting in value-based choice while suggesting theoretical alternatives to dual-process accounts. Further research combining computational and neurophysiological approaches holds promise for providing greater insight into the moment-by-moment evolution of the decision process. This article is categorized under: Psychology > Reasoning and Decision Making Neuroscience > Cognition Economics > Individual Decision-Making.

Altruism under Stress: Cortisol Negatively Predicts Charitable Giving and Neural Value Representations Depending on Mentalizing Capacity

Altruism, defined as costly other-regarding behavior, varies considerably across people and contexts. One prominent context in which people frequently must decide on how to socially act is under stress. How does stress affect altruistic decision-making and through which neurocognitive mechanisms? To address these questions, we assessed neural activity associated with charitable giving under stress. Human participants (males and females) completed a charitable donation task before and after they underwent either a psychosocial stressor or a control manipulation, while their brain activity was measured using functional magnetic resonance imaging. As the ability to infer other people's mental states (i.e., mentalizing) predicts prosocial giving and may be susceptible to stress, we examined whether stress effects on altruism depend on participants' general capacity to mentalize, as assessed in an independent task. Although our stress manipulation per se had no influence on charitable giving, increases in the stress hormone cortisol were associated with reductions in donations in participants with high mentalizing capacity, but not in low mentalizers. Multivariate neural response patterns in the right dorsolateral prefrontal cortex (DLPFC) were less predictive of postmanipulation donations in high mentalizers with increased cortisol, indicating decreased value coding, and this effect mediated the (moderated) association between cortisol increases and reduced donations. Our findings provide novel insights into the modulation of altruistic decision-making by suggesting an impact of the stress hormone cortisol on mentalizing-related neurocognitive processes, which in turn results in decreased altruism. The DLPFC appears to play a key role in mediating this cortisol-related shift in altruism.SIGNIFICANCE STATEMENT Altruism is a fundamental building block of our society. Emerging evidence indicates a major role of acute stress and stress-related neuromodulators in social behavior and decision-making. How and through which mechanisms stress may impact altruism remains elusive. We observed that the stress hormone cortisol was linked to diminished altruistic behavior. This effect was mediated by reduced value representations in the right dorsolateral prefrontal cortex and critically depended on the individual capacity to infer mental states of others. Our findings provide novel insights into the modulation of human altruism linked to stress-hormone dynamics and into the involved sociocognitive and neural mechanisms, with important implications for future developments of more targeted interventions for stress-related decrements in social behavior and social cognition.

Filling the gaps: Cognitive control as a critical lens for understanding mechanisms of value-based decision-making

While often seeming to investigate rather different problems, research into value-based decision making and cognitive control have historically offered parallel insights into how people select thoughts and actions. While the former studies how people weigh costs and benefits to make a decision, the latter studies how they adjust information processing to achieve their goals. Recent work has highlighted ways in which decision-making research can inform our understanding of cognitive control. Here, we provide the complementary perspective: how cognitive control research has informed understanding of decision-making. We highlight three particular areas of research where this critical interchange has occurred: (1) how different types of goals shape the evaluation of choice options, (2) how people use control to adjust the ways they make their decisions, and (3) how people monitor decisions to inform adjustments to control at multiple levels and timescales. We show how adopting this alternate viewpoint offers new insight into the determinants of both decisions and control; provides alternative interpretations for common neuroeconomic findings; and generates fruitful directions for future research.

Effects of mindset on hormonal responding, neural representations, subjective experience and intake

A person can alternate between food-related mindsets, which in turn may depend on one's emotional state or situation. Being in a certain mindset can influence food-related thoughts, but interestingly it might also affect eating-related physiological responses. The current study investigates the influence of an induced 'loss of control' mindset as compared to an 'in control' mindset on hormonal, neural and behavioural responses to chocolate stimuli. Mindsets were induced by having female chocolate lovers view a short movie during two sessions in a within-subjects design. Neural responses to visual chocolate stimuli were measured using an ultra-high field (7T) scanner. Momentary ghrelin and glucagon-like peptide 1 (GLP-1) levels were determined on five moments and were simultaneously assessed with self-reports on perceptions of chocolate craving, hunger and feelings of control. Furthermore, chocolate intake was measured using a bogus chocolate taste test. It was hypothesized that the loss of control mindset would lead to hormonal, neural and behavioural responses that prepare for ongoing food intake, even after eating, while the control mindset would lead to responses reflecting satiety. Results show that neural activity in the mesocorticolimbic system was stronger for chocolate stimuli than for neutral stimuli and that ghrelin and GLP-1 levels responded to food intake, irrespective of mindset. Self-reported craving and actual chocolate intake were affected by mindset, in that cravings and intake were higher with a loss of control mindset than with a control mindset. Interestingly, these findings suggest that physiology on the one hand (hormonal and neural responses) and behavior and subjective experience (food intake and craving) on the other hand are not in sync, are not equally affected by mindset.

Neural Representations of Food-Related Attributes in the Human Orbitofrontal Cortex during Choice Deliberation in Anorexia Nervosa

Decisions about what to eat recruit the orbitofrontal cortex (OFC) and involve the evaluation of food-related attributes such as taste and health. These attributes are used differently by healthy individuals and patients with disordered eating behavior, but it is unclear whether these attributes are decodable from activity in the OFC in both groups and whether neural representations of these attributes are differentially related to decisions about food. We used fMRI combined with behavioral tasks to investigate the representation of taste and health attributes in the human OFC and the role of these representations in food choices in healthy women and women with anorexia nervosa (AN). We found that subjective ratings of tastiness and healthiness could be decoded from patterns of activity in the OFC in both groups. However, health-related patterns of activity in the OFC were more related to the magnitude of choice preferences among patients with AN than healthy individuals. These findings suggest that maladaptive decision-making in AN is associated with more consideration of health information represented by the OFC during deliberation about what to eat.SIGNIFICANCE STATEMENT An open question about the OFC is whether it supports the evaluation of food-related attributes during deliberation about what to eat. We found that healthiness and tastiness information was decodable from patterns of neural activity in the OFC in both patients with AN and healthy controls. Critically, neural representations of health were more strongly related to choices in patients with AN, suggesting that maladaptive overconsideration of healthiness during deliberation about what to eat is related to activity in the OFC. More broadly, these results show that activity in the human OFC is associated with the evaluation of relevant attributes during value-based decision-making. These findings may also guide future research into the development of treatments for AN.

Advances in modeling learning and decision-making in neuroscience

An organism's survival depends on its ability to learn about its environment and to make adaptive decisions in the service of achieving the best possible outcomes in that environment. To study the neural circuits that support these functions, researchers have increasingly relied on models that formalize the computations required to carry them out. Here, we review the recent history of computational modeling of learning and decision-making, and how these models have been used to advance understanding of prefrontal cortex function. We discuss how such models have advanced from their origins in basic algorithms of updating and action selection to increasingly account for complexities in the cognitive processes required for learning and decision-making, and the representations over which they operate. We further discuss how a deeper understanding of the real-world complexities in these computations has shed light on the fundamental constraints on optimal behavior, and on the complex interactions between corticostriatal pathways to determine such behavior. The continuing and rapid development of these models holds great promise for understanding the mechanisms by which animals adapt to their environments, and what leads to maladaptive forms of learning and decision-making within clinical populations.

The prefrontal cortex and (uniquely) human cooperation: a comparative perspective

Humans have an exceptional ability to cooperate relative to many other species. We review the neural mechanisms supporting human cooperation, focusing on the prefrontal cortex. One key feature of human social life is the prevalence of cooperative norms that guide social behavior and prescribe punishment for noncompliance. Taking a comparative approach, we consider shared and unique aspects of cooperative behaviors in humans relative to nonhuman primates, as well as divergences in brain structure that might support uniquely human aspects of cooperation. We highlight a medial prefrontal network common to nonhuman primates and humans supporting a foundational process in cooperative decision-making: valuing outcomes for oneself and others. This medial prefrontal network interacts with lateral prefrontal areas that are thought to represent cooperative norms and modulate value representations to guide behavior appropriate to the local social context. Finally, we propose that more recently evolved anterior regions of prefrontal cortex play a role in arbitrating between cooperative norms across social contexts, and suggest how future research might fruitfully examine the neural basis of norm arbitration.

Neurocomputational mechanisms engaged in moral choices and moral learning

The neural circuitry involved in moral decisions has been studied since the early days of cognitive neuroscience, mainly using moral dilemma. However, the neurocomputational mechanisms describing how the human brain makes moral decisions and learns in various moral contexts are only starting to be established. Here we review recent results from an emerging field using model-based fMRI, which describes moral choices at a mechanistic level. These findings unify the field of moral decision making, extend a conceptual framework previously developed for value-based decision making and characterize how moral processes are computed in the brain. Moral dilemma can be modeled as value-based decisions that weigh self-interests against moral costs/harm to others and different types of prediction errors can be distinguished in different aspects of moral learning. These key computational signals help to describe moral choices and moral learning at an algorithmic level and to reveal how these cognitive operations are implemented in the brain. This researches provide a foundation to account for the neurocomputational mechanisms underlying moral decision making.

Neurocomputational models of altruistic decision-making and social motives: Advances, pitfalls, and future directions

This article discusses insights from computational models and social neuroscience into motivations, precursors, and mechanisms of altruistic decision-making and other-regard. We introduce theoretical and methodological tools for researchers who wish to adopt a multilevel, computational approach to study behaviors that promote others' welfare. Using examples from recent studies, we outline multiple mental and neural processes relevant to altruism. To this end, we integrate evidence from neuroimaging, psychology, economics, and formalized mathematical models. We introduce basic mechanisms-pertinent to a broad range of value-based decisions-and social emotions and cognitions commonly recruited when our decisions involve other people. Regarding the latter, we discuss how decomposing distinct facets of social processes can advance altruistic models and the development of novel, targeted interventions. We propose that an accelerated synthesis of computational approaches and social neuroscience represents a critical step towards a more comprehensive understanding of altruistic decision-making. We discuss the utility of this approach to study lifespan differences in social preference in late adulthood, a crucial future direction in aging global populations. Finally, we review potential pitfalls and recommendations for researchers interested in applying a computational approach to their research. This article is categorized under: Economics > Interactive Decision-Making Psychology > Emotion and Motivation Neuroscience > Cognition Economics > Individual Decision-Making.

Alpha oscillations and event-related potentials reflect distinct dynamics of attribute construction and evidence accumulation in dietary decision making

How does regulatory focus alter attribute value construction (AVC) and evidence accumulation (EA)? We recorded electroencephalogram during food choices while participants responded naturally or regulated their choices by attending to health attributes or decreasing attention to taste attributes. Using a drift diffusion model, we predicted the time course of neural signals associated with AVC and EA. Results suggested that event-related potentials (ERPs) correlated with the time course of model-predicted taste-attribute signals, with no modulation by regulation. By contrast, suppression of frontal and occipital alpha power correlated with the time course of EA, tracked tastiness according to its goal relevance, and predicted individual variation in successful down-regulation of tastiness. Additionally, an earlier rise in frontal and occipital theta power represented food tastiness more strongly during regulation and predicted a weaker influence of food tastiness on behaviour. Our findings illuminate how regulation modifies the representation of attributes during the process of EA.

A Feature-Based Network Analysis and fMRI Meta-Analysis Reveal Three Distinct Types of Prosocial Decisions

Tasks that measure correlates of prosocial decision-making share one common feature: agents can make choices that increase the welfare of a beneficiary. However, prosocial decisions vary widely as a function of other task features. The diverse ways that prosociality is defined and the heterogeneity of prosocial decisions have created challenges for interpreting findings across studies and identifying their neural correlates. To overcome these challenges, we aimed to organize the prosocial decision-making task space of neuroimaging studies. We conducted a systematic search for studies in which participants made decisions to increase the welfare of others during functional magnetic resonance imaging. We identified shared and distinct features of these tasks and employed an unsupervised graph-based approach to assess how various forms of prosocial decision-making are related in terms of their low-level components (e.g. task features like potential cost to the agent or potential for reciprocity). Analyses uncovered three clusters of prosocial decisions, which we labeled as cooperation, equity and altruism. This feature-based representation of the task structure was supported by results of a neuroimaging meta-analysis that each type of prosocial decisions recruited diverging neural systems. Results clarify some of the existing heterogeneity in how prosociality is conceptualized and generate insight for future research and task paradigm development.

Weighting on waiting: Willpower and attribute weighting models of decision making

Willpower is often conceptualized as incorporating effortful and momentary suppression of immediate but ultimately inferior rewards. Yet, growing evidence instead supports a process of attribute weighting, whereby normatively optimal choices arise from separable evaluation of different attributes (e.g., time and money). Strategic allocation of attention settles conflicts between competing choice-relevant attributes, which could be expanded to include self-referential predictions ("resolve").

Enhancing models of social and strategic decision making with process tracing and neural data

Every decision we take is accompanied by a characteristic pattern of response delay, gaze position, pupil dilation, and neural activity. Nevertheless, many models of social decision making neglect the corresponding process tracing data and focus exclusively on the final choice outcome. Here, we argue that this is a mistake, as the use of process data can help to build better models of human behavior, create better experiments, and improve policy interventions. Specifically, such data allow us to unlock the "black box" of the decision process and evaluate the mechanisms underlying our social choices. Using these data, we can directly validate latent model variables, arbitrate between competing personal motives, and capture information processing strategies. These benefits are especially valuable in social science, where models must predict multi-faceted decisions that are taken in varying contexts and are based on many different types of information. This article is categorized under: Economics > Interactive Decision-Making Neuroscience > Cognition Psychology > Reasoning and Decision Making.

How peer influence shapes value computation in moral decision-making

Moral behavior is susceptible to peer influence. How does information from peers influence moral preferences? We used drift-diffusion modeling to show that peer influence changes the value of moral behavior by prioritizing the choice attributes that align with peers' goals. Study 1 (N = 100; preregistered) showed that participants accurately inferred the goals of prosocial and antisocial peers when observing their moral decisions. In Study 2 (N = 68), participants made moral decisions before and after observing the decisions of a prosocial or antisocial peer. Peer observation caused participants' own preferences to resemble those of their peers. This peer influence effect on value computation manifested as an increased weight on choice attributes promoting the peers' goals that occurred independently from peer influence on initial choice bias. Participants' self-reported awareness of influence tracked more closely with computational measures of prosocial than antisocial influence. Our findings have implications for bolstering and blocking the effects of prosocial and antisocial influence on moral behavior.

Addiction history moderates the effect of prefrontal 10-Hz transcranial alternating current stimulation on habitual action selection

Individuals with substance use disorders (SUDs) transition more quickly from goal-directed to habitual action-selection, but the neural mechanisms underlying this phenomenon remain unclear. Data from animal models suggest that drugs of abuse can modify the neurocircuits that regulate action-selection, enhancing circuits that drive inflexible, habit-based stimulus-response (S-R) action-selection and weakening circuits that drive flexible, goal-directed actions. Here, we tested the effect of bilateral 10-Hz transcranial alternating current stimulation (10Ηz-tACs) of the dorsolateral prefrontal cortex on action-selection in men and women with a SUD history and an age- and sex-matched control group. We tested the hypothesis that true 10Ηz-tACS versus active sham stimulation would reduce perseverative errors after changed response contingencies for well-learned S-R associations, reflecting reduced habit-based action-selection, specifically in the SUD group. We found that 10 Hz-tACS increased perseverative errors in the control group, but in the SUD group, 10 Hz-tACS effects on perseverative errors depended on substance abuse duration: a longer addiction history was associated with a greater reduction of perseverative errors. These results suggest that 10Ηz-tACs altered circuit level dynamics regulating behavioral flexibility, and provide a foundation for future studies to test stimulation site, frequency, and timing specificity. Moreover, these data suggest that chronic substance abuse is associated with altered circuit dynamics that are ameliorated by 10Ηz-tACs. Determining the generalizability of these effects and their duration merits investigation as a direction for novel therapeutic interventions. These findings are timely based on growing interest in transcranial stimulation methods for treating SUDs.NEW & NOTEWORTHY Treating the executive dysfunction associated with addiction is hampered by redundancies in pharmacological regulation of different behavioral control circuits. Thus, nonpharmacological interventions hold promise for addiction treatment. Here, we show that, among people with an addiction history, 10-Hz transcranial alternating current stimulation (10Hz-tACS) of the dorsolateral prefrontal cortex can reduce habitual actions. The fact that 10Hz-tACS can regulate behavioral flexibility suggests its possible utility in reducing harmful habitual actions.

With a little help from my friends: The effect of social proximity on emotion regulation-related brain activity

When experiencing negative emotions, individuals often reach out for social support to help regulate their emotions. In times of an acute crisis, however, close friends might not be available, and physical closeness might be impossible. This functional magnetic resonance imaging (fMRI) study investigated the effect of social proximity on the effectiveness of social support for regulating emotions and the underlying neural mechanisms. Participants regulated their emotions in response to negative images either alone (intrapersonal regulation), or with help of a picture and supporting sentence provided by the best friend, or by a stranger (interpersonal regulation). Regulation success was enhanced for the support of friends compared to regulating alone or with the support of strangers. This effect was accompanied by the interplay of large-scale brain networks involved in processing emotions, social cognition, and cognitive control. Interpersonal regulation appeared to be implemented by lateral prefrontal regions. The amygdala showed increased activation for strangers. The activation profile of the social cognition network suggests a role in supporting empathic and mentalizing processes. The results highlight the power of social connectedness for boosting emotion regulation ability and the different neural networks that contribute to this effect.

Cognitive and hormonal regulation of appetite for food presented in the olfactory and visual modalities

The ability to regulate appetite is essential to avoid food over-consumption. The desire for a particular food can be triggered by its odor before it is even seen. Using fMRI, we identify the neural systems modulated by cognitive regulation when experiencing appetizing food stimuli presented in both olfactory and visual modalities, while being hungry. Regulatory instruction modulated bids for food items and inhalation patterns. Distinct brain regions were observed for up and down appetite-regulation, respectively the dorsomedial prefrontal cortex (dmPFC) and dorsolateral PFC. Food valuation engaged the ventromedial PFC and bilateral striatum. Furthermore, we identified a neurobiological marker for successful appetite upregulation. Individuals with higher blood levels of ghrelin were better at exercising up-regulation, and engaged the dmPFC more. These findings characterize the neural circuitry regulating food consumption within the healthy population and highlight how cognitive regulation modulates olfactomotor measures of olfaction.

Integrating Models of Self-Regulation

Self-regulation is a core aspect of human functioning that helps facilitate the successful pursuit of personal goals. There has been a proliferation of theories and models describing different aspects of self-regulation both within and outside of psychology. All of these models provide insights about self-regulation, but sometimes they talk past each other, make only shallow contributions, or make contributions that are underappreciated by scholars working in adjacent areas. The purpose of this article is to integrate across the many different models in order to refine the vast literature on self-regulation. To achieve this objective, we first review some of the more prominent models of self-regulation coming from social psychology, personality psychology, and cognitive neuroscience. We then integrate across these models based on four key elements—level of analysis, conflict, emotion, and cognitive functioning—specifically identifying points of convergence but also points of insufficient emphasis. We close with prescriptions for future research.

Neural Substrates of Food Valuation and Its Relationship With BMI and Healthy Eating in Higher BMI Individuals

Considerable evidence points to a link between body mass index (BMI), eating behavior, and the brain's reward system. However, much of this research focuses on food cue reactivity without examining the subjective valuation process as a potential mechanism driving individual differences in BMI and eating behavior. The current pre-registered study (https://osf.io/n4c95/) examined the relationship between BMI, healthy eating, and subjective valuation of healthy and unhealthy foods in a community sample of individuals with higher BMI who intended to eat more healthily. Particularly, we examined: (1) alterations in neurocognitive measures of subjective valuation related to BMI and healthy eating; (2) differences in the neurocognitive valuation for healthy and unhealthy foods and their relation to BMI and healthy eating; (3) and whether we could conceptually replicate prior findings demonstrating differences in neural reactivity to palatable vs. plain foods. To this end, we scanned 105 participants with BMIs ranging from 23 to 42 using fMRI during a willingness-to-pay task that quantifies trial-by-trial valuation of 30 healthy and 30 unhealthy food items. We measured out of lab eating behavior via the Automated Self-Administered 24 H Dietary Assessment Tool, which allowed us to calculate a Healthy Eating Index (HEI). We found that our sample exhibited robust, positive linear relationships between self-reported value and neural responses in regions previously implicated in studies of subjective value, suggesting an intact valuation system. However, we found no relationship between valuation and BMI nor HEI, with Bayes Factor indicating moderate evidence for a null relationship. Separating the food types revealed that healthy eating, as measured by the HEI, was inversely related to subjective valuation of unhealthy foods. Imaging data further revealed a stronger linkage between valuation of healthy (compared to unhealthy) foods and corresponding response in the ventromedial prefrontal cortex (vmPFC), and that the interaction between healthy and unhealthy food valuation in this region is related to HEI. Finally, our results did not replicate reactivity differences demonstrated in prior work, likely due to differences in the mapping between food healthiness and palatability. Together, our findings point to disruptions in the valuation of unhealthy foods in the vmPFC as a potential mechanism influencing healthy eating.

Neural Indicators Of Food Cue Reactivity, Regulation, And Valuation And Their Associations With Body Composition And Daily Eating Behavior

Exposure to food cues activates the brain's reward system and undermines efforts to regulate impulses to eat. During explicit regulation, lateral prefrontal cortex activates and modulates activity in reward regions and decreases food cravings. However, it is unclear the extent to which between-person differences in recruitment of regions associated with reward processing, subjective valuation, and regulation during food cue exposure-absent instructions to regulate-predict body composition and daily eating behaviors. In this preregistered study, we pooled data from five fMRI samples (N = 262) to examine whether regions associated with reward, valuation, and regulation, as well as whole-brain pattern expression indexing these processes, were recruited during food cue exposure and associated with body composition and real-world eating behavior. Regression models for a single a priori analytic path indicated that univariate and multivariate measures of reward and valuation were associated with individual differences in BMI and enactment of daily food cravings. Specification curve analyses further revealed reliable associations between univariate and multivariate neural indicators of reactivity, regulation, and valuation, and all outcomes. These findings highlight the utility of these methods to elucidate brain-behavior associations and suggest that multiple processes are implicated in proximal and distal markers of eating behavior.

Brain Activity Associated With Regulating Food Cravings Predicts Changes in Self-Reported Food Craving and Consumption Over Time

Neural patterns associated with viewing energy-dense foods can predict changes in eating-related outcomes. However, most research on this topic is limited to one follow-up time point, and single outcome measures. The present study seeks to add to that literature by employing a more refined assessment of food craving and consumption outcomes along with a more detailed neurobiological model of behavior change over several time points. Here, a community sample of 88 individuals (age: M = 39.17, SD = 3.47; baseline BMI: M = 31.5, SD = 3.9, range 24–42) with higher body mass index (BMI) performed a food craving reactivity and regulation task while undergoing functional magnetic resonance imaging. At that time—and 1, 3, and 6 months later—participants reported craving for and consumption of healthy and unhealthy foods via the Food Craving Inventory (FCI) and ASA24 (N at 6 months = 52–55 depending on the measure). A priori hypotheses that brain activity associated with both viewing and regulating personally desired unhealthy, energy-dense foods would be associated with self-reported craving for and consumption of unhealthy foods at baseline were not supported by the data. Instead, regression models controlling for age, sex, and BMI demonstrated that brain activity across several regions measured while individuals were regulating their desires for unhealthy food was associated with the self-reported craving for and consumption of healthy food. The hypothesis that vmPFC activity would predict patterns of healthier eating was also not supported. Instead, linear mixed models controlling for baseline age and sex, as well as changes in BMI, revealed that more regulation-related activity in the dlPFC, dACC, IFG, and vmPFC at baseline predicted decreases in the craving for and consumption of healthy foods over the course of 6 months.

Retrospective Valuation of Experienced Outcome Encoded in Distinct Reward Representations in the Anterior Insula and Amygdala

Our ability to evaluate an experience retrospectively is important because it allows us to summarize its total value, and this summary value can then later be used as a guide in deciding whether the experience merits repeating, or whether instead it should rather be avoided. However, when an experience unfolds over time, humans tend to assign disproportionate weight to the later part of the experience, and this can lead to poor choice in repeating, or avoiding experience. Using model-based computational analyses of fMRI recordings in 27 male volunteers, we show that the human brain encodes the summary value of an extended sequence of outcomes in two distinct reward representations. We find that the overall experienced value is encoded accurately in the amygdala, but its merit is excessively marked down by disincentive anterior insula activity if the sequence of experienced outcomes declines temporarily. Moreover, the statistical strength of this neural code can separate efficient decision-makers from suboptimal decision-makers. Optimal decision-makers encode overall value more strongly, and suboptimal decision-makers encode the disincentive markdown (DM) more strongly. The separate neural implementation of the two distinct reward representations confirms that suboptimal choice for temporally extended outcomes can be the result of robust neural representation of a displeasing aspect of the experience such as temporary decline.SIGNIFICANCE STATEMENT One of the numerous foibles that prompt us to make poor decisions is known as the "Banker's fallacy," the tendency to focus on short-term growth at the expense of long-term value. This effect leads to unwarranted preference for happy endings. Here, we show that the anterior insula in the human brain marks down the overall value of an experience as it unfolds over time if the experience entails a sequence of predominantly negative temporal contrasts. By contrast, the amygdala encodes overall value accurately. These results provide neural indices for the dichotomy of decision utility and experienced utility popularized as Thinking fast and slow by Daniel Kahneman.

BOLD activity during emotion reappraisal positively correlates with dietary self-control success

We combined established emotion regulation and dietary choice tasks with fMRI to investigate behavioral and neural associations in self-regulation across the two domains in human participants. We found that increased BOLD activity during the successful reappraisal of positive and negative emotional stimuli was associated with dietary self-control success. This cross-task correlation was present in medial and lateral prefrontal cortex as well as the striatum. In contrast, BOLD activity during the food choice task was not associated with self-reported emotion regulation efficacy. These results suggest that neural processes utilized during the reappraisal of emotional stimuli may also facilitate dietary choices that override palatability in favor of healthfulness. In summary, our findings indicate that the neural systems supporting emotion reappraisal can generalize to other behavioral contexts that require reevaluation of rewarding stimuli and outcomes to promote choices that conform with the current goal.

Emotion Regulation Modulates Dietary Decision-Making via Activity in the Prefrontal-Striatal Valuation System

The consumption of indulgent, carbohydrate- and fat-rich foods is often used as a strategy to cope with negative affect because they provide immediate self-reward. Such dietary choices, however, can severely affect people's health. One countermeasure could be to improve one's emotion regulation ability. We used functional magnetic resonance imaging to examine the neural activity underlying the downregulation of incidental emotions and its effect on subsequent food choices. We investigated whether emotion regulation leads to healthier food choices and how emotion regulation interacts with the brain's valuation and decision-making circuitry. We found that 1) the downregulation of incidental negative emotions was associated with a subsequent selective increase in decisions for tasty but also for healthy foods, 2) food preferences were predicted by palatability but also by the current emotional state, and 3) emotion regulation modulated decision-related activation in the ventromedial prefrontal cortex and ventral striatum. These results indicate that emotional states are indeed important for food choice and that the process of emotion regulation might boost the subsequent processing of health attributes, possibly via neural reward circuits. In consequence, our findings suggest that increasing emotion regulation ability could effectively modulate food choices by stimulating an incidental upvaluation of health attributes.

Value-based attention but not divisive normalization influences decisions with multiple alternatives

Violations of economic rationality principles in choices between three or more options are critical for understanding the neural and cognitive mechanisms of decision-making. A recent study reported that the relative choice accuracy between two options decreases as the value of a third (distractor) option increases and attributed this effect to divisive normalization of neural value representations. In two preregistered experiments, a direct replication and an eye-tracking experiment, we assessed the replicability of this effect and tested an alternative account that assumes value-based attention to mediate the distractor effect. Surprisingly, we could not replicate the distractor effect in our experiments. However, we found a dynamic influence of distractor value on fixations to distractors as predicted by the value-based attention theory. Computationally, we show that extending an established sequential sampling decision-making model by a value-based attention mechanism offers a comprehensive account of the interplay between value, attention, response times and decisions.

A Value-Based Framework for Understanding Cooperation

Understanding the roots of human cooperation, a social phenomenon embedded in pressing issues including climate change and social conflict, requires an interdisciplinary perspective. We propose a unifying value-based framework for understanding cooperation that integrates neuroeconomic models of decision-making with psychological variables involved in cooperation. We propose that the ventromedial prefrontal cortex serves as a neural integration hub for value computation during cooperative decisions, receiving inputs from various neurocognitive processes such as attention, memory, and learning. Next, we describe findings from social and personality psychology highlighting factors that shape the value of cooperation, including research on contexts and norms, personal and social identity, and intergroup relations. Our approach advances theoretical debates about cooperation by highlighting how previous findings are accommodated within a general value-based framework and offers novel predictions.

Under construction: ventral and lateral frontal lobe contributions to value-based decision-making and learning

Even apparently simple choices, like selecting a dessert in a pastry shop, involve options characterized by multiple motivationally relevant attributes. Neuroeconomic research suggests that the human brain may track the subjective value of such options, allowing disparate reward-predictive information to be compared in a common currency. However, the brain mechanisms involved in identifying value-predictive features and combining these to assess the value of each decision option remain unclear. Here, we review recent evidence from studies of multi-attribute decision-making in people with focal frontal lobe damage and in healthy people undergoing functional magnetic resonance imaging. This work suggests that ventromedial and lateral prefrontal cortex and orbitofrontal cortex are important for forming value judgments under conditions of complexity. We discuss studies supporting the involvement of these regions in selecting among and evaluating option attributes during value judgment and decision-making and when learning from reward feedback. These findings are consistent with roles for these regions in guiding value construction. They argue for a more nuanced understanding of how ventral and lateral prefrontal cortex contribute to discovering and recognizing value, processes that are required under the complex conditions typical of many everyday decisions.

Perceived relative social status and cognitive load influence acceptance of unfair offers in the Ultimatum Game

Participants in the Ultimatum Game will often reject unfair resource allocations at personal cost, reflecting a trade-off between financial gain and maintenance of social standing. Although this rejection behavior is linked to executive control, the exact role of cognitive regulation in relation to status cues is unclear. We propose that the salience of status cues affects how cognitive regulation resolves the conflict between financial gain and social status considerations. Situations that tax executive control by limiting available cognitive resources should increase acceptance rates for unfair offers, particularly when the conflict between economic self-interest and social reputation is high. Here, participants rated their own subjective social status, and then either mentally counted (Load) or ignored (No Load) simultaneously-presented tones while playing two rounds of the Ultimatum Game with an online (sham) “Proposer” of either high or low social status. A logistic regression revealed an interaction of Proposer status with cognitive load. Compared to the No Load group, the Load group showed higher acceptance rates for unfair offers from the high-status Proposer. In contrast, cognitive load did not influence acceptance rates for unfair offers from the low-status Proposer. Additionally, Proposer status interacted with the relative social distance between participant and Proposer. Participants close in social distance to the high-status Proposer were more likely to accept the unfair offer than those farther in social distance, whereas the opposite pattern was observed for offers from the low-status Proposer. Although rejection of unfair offers in the Ultimatum Game has previously been conceptualized as an intuitive response, these results instead suggest it reflects a deliberative strategy, dependent on cognitive resources, to prioritize social standing over short-term financial gain. This study reveals the dynamic interplay of cognitive resources and status concerns within this paradigm, providing new insights into when and why people reject inequitable divisions of resources.

Neuroeconomics, health psychology, and the interdisciplinary study of preventative health behavior

The goal of this article is to introduce readers to theories, tools, and evidence from the field of neuroeconomics and to describe how health psychology and neuroeconomics can be mutually informative in the study of preventative health behaviors. Preventative health behavior here refers to both individual actions that impact one's health (e.g., exercise) and broader behavioral patterns, such as those captured in personality constructs. Although neuroeconomic researchers have begun to incorporate health-relevant behaviors into their studies, the full potential of this research to inform preventative health models is as yet unrealized. What is needed to "translate up" is the unification of rich theoretical content from health psychology with investigations by neuroeconomic researchers of the decision-making process during health-relevant choices. We identify choice as a central, shared feature across models of preventative health behavior that can serve as an inroad for neuroeconomics to contribute to existing models and highlight commonalities that might not otherwise be apparent. A central premise of our argument is that, because health decisions are nearly always multiply determined, a more precise and mechanistic understanding of how choices are made is an important but understudied topic in health psychology. A partnership between health psychologists and neuroeconomic researchers can yield valuable insights into how preventative health choice is made and to identify targets and methods for intervention.

Comparing two neurocognitive models of self-control during dietary decisions

Self-control is the process of favoring abstract, distal goals over concrete, proximal goals during decision-making and is an important factor in health and well-being. We directly compare two prominent neurocognitive models of human self-control with the goal of identifying which, if either, best describes behavioral and neural data of dietary decisions in a large sample of overweight and obese adults motivated to eat more healthfully. We extracted trial-by-trial estimates of neural activity during incentive-compatible choice from three brain regions implicated in self-control, dorsolateral prefrontal cortex, ventral striatum and ventromedial prefrontal cortex and assessed evidence for the dual-process and value-based choice models of self-control using multilevel modeling. Model comparison tests revealed that the value-based choice model outperformed the dual-process model and best fit the observed data. These results advance scientific knowledge of the neurobiological mechanisms underlying self-control-relevant decision-making and are consistent with a value-based choice model of self-control.

Brain structures and functional connectivity associated with individual differences in trait proactive aggression

Although considerable efforts have been made to understand the neural underpinnings of (state) reactive aggression, which is triggered by provocation or perceived threat, little is known about the neural correlates of proactive aggression, which is driven by instrumental motivations to obtain personal gains through aggressive means and which varies dramatically across individuals in terms of tendency of appealing to such means. Here, by combining structural (grey matter density, GMD) and functional (resting-state functional connection, RSFC) fMRI, we investigated brain structures and functional networks related to trait proactive aggression. We found that individual differences in trait proactive aggression were positively associated with GMD in bilateral dorsolateral prefrontal cortex (DLPFC) and negatively correlated with GMD in posterior cingulate cortex (PCC); they were also negatively correlated with the strength of functional connectivity between left PCC and other brain regions, including right DLPFC, right IPL, right MPFC/ACC, and bilateral precuneus. These findings shed light on the differential brain bases of proactive and reactive aggressions and suggested the neural underpinnings of proactive aggression.