Prefrontal connections express individual differences in intrinsic resistance to trading off honesty values against economic benefits

Increased Interpersonal Brain Synchronization in Romantic Couples Is Associated with Higher Honesty: An fNIRS Hyperscanning Study

Previous studies on the brain-brain interaction of deception have shown different patterns of interpersonal brain synchronization (IBS) between different genders. However, the brain-brain mechanisms in the cross-sex composition need to be better understood. Furthermore, there needs to be more discussion about how relationships (e.g., romantic couples vs. strangers) affect the brain-brain mechanism under interactive deception. To elaborate on these issues, we used the functional near-infrared spectroscopy (fNIRS)-based hyperscanning approach to simultaneously measure interpersonal brain synchronization (IBS) in romantic couples (heterosexual) and cross-sex stranger dyads during the sender-receiver game. The behavioral results found that the deception rate of males was lower than that of females, and romantic couples were deceived less than strangers. Significantly increased IBS was observed in the frontopolar cortex (FPC) and right temporoparietal junction (rTPJ) of the romantic couple group. Moreover, the IBS is negatively correlated with the deception rate. No significantly increased IBS was observed in cross-sex stranger dyads. The result corroborated the lower deception of males and romantic couples in cross-sex interactions. Furthermore, IBS in the PFC and rTPJ was the underlying dual-brain neural basis for supporting honesty in romantic couples.

Cognitive control and dishonesty

Dishonesty is ubiquitous and imposes substantial financial and social burdens on society. Intuitively, dishonesty results from a failure of willpower to control selfish behavior. However, recent research suggests that the role of cognitive control in dishonesty is more complex. We review evidence that cognitive control is not needed to be honest or dishonest per se, but that it depends on individual differences in what we call one's 'moral default': for those who are prone to dishonesty, cognitive control indeed aids in being honest, but for those who are already generally honest, cognitive control may help them cheat to occasionally profit from small acts of dishonesty. Thus, the role of cognitive control in (dis)honesty is to override the moral default.

Does moral commitment predict resistance to corruption? experimental evidence from a bribery game

Corruption is ubiquitous in practice and has severe negative consequences for organizations and societies at large. Drawing on a laboratory experiment, we propose that individuals high in moral commitment are less likely to engage in corrupt behaviors and prefer foregoing financial benefits. Specifically, we posit that individuals refrain from corruption (i) the more they endorse integrity (incorruptibility) as a protected value and (ii) the higher their level of Honesty-Humility. The results of a two-step experiment largely support our expectations: people who treat compromises to integrity as unacceptable were less willing to accept bribes, and Honesty-Humility decreased bribe-giving. The findings are robust to demographic variables (e.g., age, gender, cultural background) and additional personal characteristics (e.g., risk tolerance, dispositional greed) and have important implications for ongoing theory-building efforts and business practice.

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.

Prosocial Gains and Losses: Modulations of Human Social Decision-Making by Loss-Gain Context

The role of the loss-gain context in human social decision-making remains heavily debated, with mixed evidence showing that losses (vs. gains) boost both selfish and prosocial motivations. Herein, we propose that the loss context, compared to the gain context, exacerbates intuitive reactions in response to the conflict between self-interest and prosocial preferences, regardless of whether those dominant responses are selfish or altruistic. We then synthesize evidence from three lines of research to support the account, which indicates that losses may either enhance or inhibit altruistic behaviors depending on the dominant responses in the employed interactive economic games, prosocial/proself traits, and the explicit engagement of deliberative processes. The current perspective contributes to the ongoing debate on the association between loss-gain context and human prosociality by putting forward a theoretical framework to integrate previous conflicting perspectives.

Neuro-Computational Foundations of Moral Preferences

Moral preferences pervade many aspects of our lives, dictating how we ought to behave, whom we can marry, and even what we eat. Despite their relevance, one fundamental question remains unanswered: Where do individual moral preferences come from? It is often thought that all types of preferences reflect properties of domain-general neural decision mechanisms that employ a common "neural currency" to value choice options in many different contexts. This view, however, appears at odds with the observation that many humans consider it intuitively wrong to employ the same scale to compare moral value (e.g., of a human life) with material value (e.g., of money). In this paper, we directly test if moral subjective values are represented by similar neural processes as financial subjective values. In a study combining fMRI with a novel behavioral paradigm, we identify neural representations of the subjective values of human lives or financial payoffs by means of structurally identical computational models. Correlating isomorphic model variables from both domains with brain activity reveals specific patterns of neural activity that selectively represent values in the moral (rTPJ) or financial (vmPFC) domain. Intriguingly, our findings show that human lives and money are valued in (at least partially) distinct neural currencies, supporting theoretical proposals that human moral behavior is guided by processes that are distinct from those underlying behavior driven by personal material benefit.

Neural basis of corruption in power-holders

Corruption often involves bribery, when a briber suborns a power-holder to gain advantages usually at a cost of moral transgression. Despite its wide presence in human societies, the neurocomputational basis of bribery remains elusive. Here, using model-based fMRI, we investigated the neural substrates of how a power-holder decides to accept or reject a bribe. Power-holders considered two types of moral cost brought by taking bribes: the cost of conniving with a fraudulent briber, encoded in the anterior insula, and the harm brought to a third party, represented in the right temporoparietal junction. These moral costs were integrated into a value signal in the ventromedial prefrontal cortex. The dorsolateral prefrontal cortex was selectively engaged to guide anti-corrupt behaviors when a third party would be harmed. Multivariate and connectivity analyses further explored how these neural processes depend on individual differences. These findings advance our understanding of the neurocomputational mechanisms underlying corrupt behaviors.

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.

Neurocomputational mechanisms at play when weighing concerns for extrinsic rewards, moral values, and social image

Humans not only value extrinsic monetary rewards but also their own morality and their image in the eyes of others. Yet violating moral norms is frequent, especially when people know that they are not under scrutiny. When moral values and monetary payoffs are at odds, how does the brain weigh the benefits and costs of moral and monetary payoffs? Here, using a neurocomputational model of decision value (DV) and functional (f)MRI, we investigated whether different brain systems are engaged when deciding whether to earn money by contributing to a “bad cause” and when deciding whether to sacrifice money to contribute to a “good cause,” both when such choices were made privately or in public. Although similar principles of DV computations were used to solve these dilemmas, they engaged 2 distinct valuation systems. When weighing monetary benefits and moral costs, people were willing to trade their moral values in exchange for money, an effect accompanied by DV computation engaging the anterior insula and the lateral prefrontal cortex (PFC). In contrast, weighing monetary costs against compliance with one’s moral values engaged the ventral putamen. Moreover, regardless of the type of dilemma, a brain network including the anterior cingulate cortex (ACC), anterior insula, and the right temporoparietal junction (TJP) was more engaged in public than in private settings. Together, these findings identify how the brain processes three sources of motivation: extrinsic rewards, moral values, and concerns for image.

Distinct brain systems are engaged when weighing whether to earn money by contributing to a ‘bad cause’ and when weighing whether to lose money to contribute to a ‘good cause,’ regardless of whether such choices are made privately or in public.

Resting-state Functional Connectivity and Deception: Exploring Individualized Deceptive Propensity by Machine Learning

Individuals show marked variability in determining to be honest or deceptive in daily life. A large number of studies have investigated the neural substrates of deception; however, the brain networks contributing to the individual differences in deception remain unclear. In this study, we sought to address this issue by employing a machine-learning approach to predict individuals' deceptive propensity based on the topological properties of whole-brain resting-state functional connectivity (RSFC). Participants finished the resting-state functional MRI (fMRI) data acquisition, and then, one week later, participated as proposers in a modified ultimatum game in which they spontaneously chose to be honest or deceptive. A linear relevance vector regression (RVR) model was trained and validated to examine the relationship between topological properties of networks of RSFC and actual deceptive behaviors. The machine-learning model sufficiently decoded individual differences in deception using three brain networks based on RSFC, including the executive controlling network (dorsolateral prefrontal cortex, middle frontal cortex, and orbitofrontal cortex), the social and mentalizing network (the temporal lobe, temporo-parietal junction, and inferior parietal lobule), and the reward network (putamen and thalamus). These networks have been found to form a signaling cognitive framework of deception by coding the mental states of others and the reward or values of deception or honesty, and integrating this information to make a final decision about being deceptive or honest. These findings suggest the potential of using RSFC as a task-independent neural trait for predicting deceptive propensity, and shed light on using machine-learning approaches in deception detection.

I lie, why don't you: Neural mechanisms of individual differences in self-serving lying

People tend to lie in varying degrees. To advance our understanding of the underlying neural mechanisms of this heterogeneity, we investigated individual differences in self-serving lying. We performed a functional magnetic resonance imaging study in 37 participants and introduced a color-reporting game where lying about the color would in general lead to higher monetary payoffs but would also be punished if get caught. At the behavioral level, individuals lied to different extents. Besides, individuals who are more dishonest showed shorter lying response time, whereas no significant correlation was found between truth-telling response time and the degree of dishonesty. At the neural level, the left caudate, ventromedial prefrontal cortex (vmPFC), right inferior frontal gyrus (IFG), and left dorsolateral prefrontal cortex (dlPFC) were key regions reflecting individual differences in making dishonest decisions. The dishonesty associated activity in these regions decreased with increased dishonesty. Subsequent generalized psychophysiological interaction analyses showed that individual differences in self-serving lying were associated with the functional connectivity among the caudate, vmPFC, IFG, and dlPFC. More importantly, regardless of the decision types, the neural patterns of the left caudate and vmPFC during the decision-making phase could be used to predict individual degrees of dishonesty. The present study demonstrated that lying decisions differ substantially from person to person in the functional connectivity and neural activation patterns which can be used to predict individual degrees of dishonesty.

The lateral prefrontal cortex and moral goal pursuit

In the face of competing desires, humans often strive to be fair, honest, and considerate of others. Research from social neuroscience implicates the lateral prefrontal cortex (LPFC) in our capacity to pursue such goals, yet its precise computational role is less clear. Here, we draw on insights from the neuroscience of hierarchical control and value-based choice to offer an integrative look at how LPFC supports the pursuit of moral goals. We conclude by highlighting how future work may leverage these insights to deepen our understanding of the dynamic neural code of morality.

Shared temptations: An fMRI study of dishonest profit maximization

A single case of a tempting-decision task involving financial gain is reported. The subject showed a prosocial Social Value Orientation and applied a profit-maximizing strategy. Differential brain activation patterns for self-serving and other-serving decisions were observed. Results provide new insight into the design of paradigms on bounded ethicality and self- and group-serving behavior.