Choose, rate or squeeze: Comparison of economic value functions elicited by different behavioral tasks

Electrophysiological population dynamics reveal context dependencies during decision making in human frontal cortex

Evidence from monkeys and humans suggests that the orbitofrontal cortex (OFC) encodes the subjective value of options under consideration during choice. Data from non-human primates suggests that these value signals are context-dependent, representing subjective value in a way influenced by the decision makers' recent experience. Using electrodes distributed throughout cortical and subcortical structures, human epilepsy patients performed an auction task where they repeatedly reported the subjective values they placed on snack food items. High-gamma activity in many cortical and subcortical sites including the OFC positively correlated with subjective value. Other OFC sites showed signals contextually modulated by the subjective value of previously offered goods-a context dependency predicted by theory but not previously observed in humans. These results suggest that value and value-context signals are simultaneously present but separately represented in human frontal cortical activity.

Decision neuroscience and neuroeconomics: Recent progress and ongoing challenges

In the past decade, decision neuroscience and neuroeconomics have developed many new insights in the study of decision making. This review provides an overarching update on how the field has advanced in this time period. Although our initial review a decade ago outlined several theoretical, conceptual, methodological, empirical, and practical challenges, there has only been limited progress in resolving these challenges. We summarize significant trends in decision neuroscience through the lens of the challenges outlined for the field and review examples where the field has had significant, direct, and applicable impacts across economics and psychology. First, we review progress on topics including reward learning, explore-exploit decisions, risk and ambiguity, intertemporal choice, and valuation. Next, we assess the impacts of emotion, social rewards, and social context on decision making. Then, we follow up with how individual differences impact choices and new exciting developments in the prediction and neuroforecasting of future decisions. Finally, we consider how trends in decision-neuroscience research reflect progress toward resolving past challenges, discuss new and exciting applications of recent research, and identify new challenges for the field. This article is categorized under: Psychology > Reasoning and Decision Making Psychology > Emotion and Motivation.

Dynamic modulation of inequality aversion in human interpersonal negotiations

Negotiating with others about how finite resources should be distributed is an important aspect of human social life. However, little is known about mechanisms underlying human social-interactive decision-making in gradually evolving environments. Here, we report results from an iterative Ultimatum Game (UG), in which the proposer’s facial emotions and offer amounts were sampled probabilistically based on the participant’s decisions. Our model-free results confirm the prediction that both the proposer’s facial emotions and the offer amount should influence acceptance rates. Model-based analyses extend these findings, indicating that participants’ decisions in the UG are guided by aversion to inequality. We highlight that the proposer’s facial affective reactions to participant decisions dynamically modulate how human decision-makers perceive self–other inequality, relaxing its otherwise negative influence on decision values. This cognitive model underlies how offers initially rejected can gradually become more acceptable under increasing affective load (predictive accuracy ~86%). Furthermore, modelling human choice behaviour isolated the role of the central arousal systems, assessed by measuring pupil size. We demonstrate that pupil-linked central arousal systems selectively encode a key component of subjective decision values: the magnitude of self–other inequality. Taken together, our results demonstrate that, under affective influence, aversion to inequality is a malleable cognitive process.

The effect of a proposer’s facial emotions on a receiver’s likelihood to accept offers in an iterative Ultimatum Game is unknown. Here, modelling participant behaviour demonstrates that facial emotions dynamically tune participants’ inequality aversion.

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.

Can't decide how much to EAT? Effort variability for reward is associated with cognitive restraint

Food intake is inherently variable and often characterized by episodical restraint or overeating (uncontrolled eating). Such heightened variability in intake has been associated with higher variability in the brain response to food reward, but it is an open issue whether comparable associations with elevated variability in reward seeking exist. Here, we assessed whether restraint and uncontrolled eating as markers of trait-like variability in eating are associated with higher intra-individual variability in reward seeking as captured by a cost-benefit paradigm. To test this hypothesis, 81 healthy, overnight-fasting participants (M_BMI = 23.0 kg/m² ± 3.0) completed an effort allocation task (EAT) twice. In the EAT, participants had to exert physical effort to earn monetary and food rewards and indicated levels of wanting through visual analog scales (VAS). As predicted, we found that greater trial-by-trial effort variability was associated with lower scores on cognitive restraint, r_p(78) = -0.28, p = .011 (controlled for average effort). In line with previous findings, higher wanting variability was associated with higher BMI, r_p(78) = 0.25, p = .026 (controlled for average effort). Collectively, our results support the idea that higher variability in reward seeking is a potential risk factor for eating beyond homeostatic need. Since associations with variability measures of reward exceeded associations with average reward seeking, our findings may indicate that variability in the representation of the reward value could be a crucial aspect driving fluctuations in food intake.

Right Temporoparietal Junction Underlies Avoidance of Moral Transgression in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is characterized by a core difference in theory-of-mind (ToM) ability, which extends to alterations in moral judgment and decision-making. Although the function of the right temporoparietal junction (rTPJ), a key neural marker of ToM and morality, is known to be atypical in autistic individuals, the neurocomputational mechanisms underlying its specific changes in moral decision-making remain unclear. Here, we addressed this question by using a novel fMRI task together with computational modeling and representational similarity analysis (RSA). ASD participants and healthy control subjects (HCs) decided in public or private whether to incur a personal cost for funding a morally good cause (Good Context) or receive a personal gain for benefiting a morally bad cause (Bad Context). Compared with HC, individuals with ASD were much more likely to reject the opportunity to earn ill gotten money by supporting a bad cause than were HCs. Computational modeling revealed that this resulted from heavily weighing benefits for themselves and the bad cause, suggesting that ASD participants apply a rule of refusing to serve a bad cause because they evaluate the negative consequences of their actions more severely. Moreover, RSA revealed a reduced rTPJ representation of the information specific to moral contexts in ASD participants. Together, these findings indicate the contribution of rTPJ in representing information concerning moral rules and provide new insights for the neurobiological basis underpinning moral behaviors illustrated by a specific difference of rTPJ in ASD participants.SIGNIFICANCE STATEMENT Previous investigations have found an altered pattern of moral behaviors in individuals with autism spectrum disorder (ASD), which is closely associated with functional changes in the right temporoparietal junction (rTPJ). However, the specific neurocomputational mechanisms at play that drive the altered function of the rTPJ in moral decision-making remain unclear. Here, we show that ASD individuals are more inflexible when following a moral rule although an immoral action can benefit themselves, and experience an increased concern about their ill-gotten gains and the moral cost. Moreover, a selectively reduced rTPJ representation of information concerning moral rules was observed in ASD participants. These findings deepen our understanding of the neurobiological roots that underlie atypical moral behaviors in ASD individuals.

Neurocomputational mechanisms underlying immoral decisions benefiting self or others

Immoral behavior often consists of weighing transgression of a moral norm against maximizing personal profits. One important question is to understand why immoral behaviors vary based on who receives specific benefits and what are the neurocomputational mechanisms underlying such moral flexibility. Here, we used model-based functional magnetic resonance imaging to investigate how immoral behaviors change when benefiting oneself or someone else. Participants were presented with offers requiring a tradeoff between a moral cost (i.e. profiting a morally bad cause) and a benefit for either oneself or a charity. Participants were more willing to obtain ill-gotten profits for themselves than for a charity, driven by a devaluation of the moral cost when deciding for their own interests. The subjective value of an immoral offer, computed as a linear summation of the weighed monetary gain and moral cost, recruited the ventromedial prefrontal cortex (PFC) regardless of beneficiaries. Moreover, paralleling the behavioral findings, this region enhanced its functional coupling with mentalizing-related regions while deciding whether to gain morally tainted profits for oneself vs charity. Finally, individual differences in moral preference differentially modulated choice-specific signals in the dorsolateral PFC according to who benefited from the decisions. These findings provide insights for understanding the neurobiological basis of moral flexibility.

Four core properties of the human brain valuation system demonstrated in intracranial signals

Estimating the value of alternative options is a key process in decision-making. Human functional magnetic resonance imaging and monkey electrophysiology studies have identified brain regions, such as the ventromedial prefrontal cortex (vmPFC) and lateral orbitofrontal cortex (lOFC), composing a value system. In the present study, in an effort to bridge across species and techniques, we investigated the neural representation of value ratings in 36 people with epilepsy, using intracranial electroencephalography. We found that subjective value was positively reflected in both vmPFC and lOFC high-frequency activity, plus several other brain regions, including the hippocampus. We then demonstrated that subjective value could be decoded (1) in pre-stimulus activity, (2) for various categories of items, (3) even during a distractive task and (4) as both linear and quadratic signals (encoding both value and confidence). Thus, our findings specify key functional properties of neural value signals (anticipation, generality, automaticity, quadraticity), which might provide insights into human irrational choice behaviors.

Sour grapes and sweet victories: How actions shape preferences

Classical decision theory postulates that choices proceed from subjective values assigned to the probable outcomes of alternative actions. Some authors have argued that opposite causality should also be envisaged, with choices influencing subsequent values expressed in desirability ratings. The idea is that agents may increase their ratings of items that they have chosen in the first place, which has been typically explained by the need to reduce cognitive dissonance. However, evidence in favor of this reverse causality has been the topic of intense debates that have not reached consensus so far. Here, we take a novel approach using Bayesian techniques to compare models in which choices arise from stable (but noisy) underlying values (one-way causality) versus models in which values are in turn influenced by choices (two-way causality). Moreover, we examined whether in addition to choices, other components of previous actions, such as the effort invested and the eventual action outcome (success or failure), could also impact subsequent values. Finally, we assessed whether the putative changes in values were only expressed in explicit ratings, or whether they would also affect other value-related behaviors such as subsequent choices. Behavioral data were obtained from healthy participants in a rating-choice-rating-choice-rating paradigm, where the choice task involves deciding whether or not to exert a given physical effort to obtain a particular food item. Bayesian selection favored two-way causality models, where changes in value due to previous actions affected subsequent ratings, choices and action outcomes. Altogether, these findings may help explain how values and actions drift when several decisions are made successively, hence highlighting some shortcomings of classical decision theory.

The standard way to explain decisions is the so-called valuation/selection model, which includes 1) a value function that calculates desirability for every possible outcome of alternative actions and 2) a choice function that integrates outcome values and generates selection probability for every action. In this classical view, choices are therefore determined (in a probabilistic sense) by hidden values. However, some authors have argued that causality could also be reversed, meaning that values may in turn be influenced by choices. Yet existing demonstrations of reverse causality have been criticized because pseudo-effects may arise from statistical artifacts. Here, we take a novel computational approach that directly compares models with and without the existence of reverse causality, on the basis of behavioral data obtained from volunteers in a new task. The winning model is a generalization of the reverse causality hypothesis, showing that people tend to like more the items that they previously chose to pursue, and even more if they did obtain these items. These effects were manifest not only in desirability ratings but also in subsequent actions, showing that value changes were more profound than just verbal statements. Altogether, our results invite reconsideration of decision theory, showing that actions are not neutral to the values driving them, hence suggesting that the history of actions should be taken into account.

Adolescent Development of Value-Guided Goal Pursuit

Adolescents are challenged to orchestrate goal-directed actions in increasingly independent and consequential ways. In doing so, it is advantageous to use information about value to select which goals to pursue and how much effort to devote to them. Here, we examine age-related changes in how individuals use value signals to orchestrate goal-directed behavior. Drawing on emerging literature on value-guided cognitive control and reinforcement learning, we demonstrate how value and task difficulty modulate the execution of goal-directed action in complex ways across development from childhood to adulthood. We propose that the scope of value-guided goal pursuit expands with age to include increasingly challenging cognitive demands, and scaffolds on the emergence of functional integration within brain networks supporting valuation, cognition, and action.