Unraveling how the third-party brain under stress responds to injustices.

How third-party individuals respond to injustices is important for resolving conflict in society. A study in PLOS Biology shows that individuals experiencing acute stress prefer to aid victims over punishing offenders, an opposite pattern to non-stress conditions.

Natural Language Content Mediates the Association Between Active Interactions on Social Network Services and Subjective Well-Being.

Previous studies indicated that active interactions on social networking services (SNS) are positively linked to subjective well-being (SWB). However, how semantic SNS content affects the association between the degree of SNS interaction and SWB has not been investigated. We addressed this issue by conducting a mediation analysis using natural language processing. We first analyzed Twitter data and SWB scores from 217 participants and found that the degree of active interactions on Twitter (i.e., frequency of reply) was positively correlated with SWB. Next, our multivariate mediation analysis demonstrated that positive words served as SWB-promoting mechanisms for highly interactive people, whereas worrying words led to lower SWB for less interactive people, but negative words did not. This study revealed that natural language content explains why individuals who are highly interactive on SNS have higher SWB, whereas less interactive individuals show lower SWB.

Distinctive types of aversiveness are represented as the same in a portion of the dorsal anterior cingulate cortex: An fMRI study with the cue paradigm.

Some studies have argued that the dorsal anterior cingulate cortex (dACC) is generally activated in response to aversive information, including pain, negative affect, and cognitive conflict. Other studies have claimed that the dACC has subdivisions, and each division has a specific function. By manipulating emotionally and cognitively aversive cues, the present study determined whether the dACC is generally responsive to aversiveness or it has subdivisions for specific forms of aversiveness. Conjunction functional magnetic resonance imaging (fMRI) analysis showed that emotionally and cognitively aversive cues activated the same portion of the dACC. When these cues were contiguously presented, the region demonstrated additive activity, further supporting the overlapping representation of the two different forms of aversiveness in the dACC. Additional effective connectivity analysis showed that the dACC was co-activated with different brain regions depending on the cue type, characterizing its behavioral control mechanism. Complementary multivariate analyses showed that the reaction time was negatively correlated with the activity of the dACC and that the activity of the dACC under the emotional cue was predicted by the individual state anxiety score but not under the cognitive cue. We also found that the superior part of the dACC was uniquely activated in response to cognitively aversive cues, partially supporting the functional segregation account. Collectively, our results provide evidence that the specific locus of the dACC is generally responsive to distinctive motivational information, whereas the other loci may have segregated functions. Discussion includes recent neurocomputational theories that seem to satisfactorily account for the present results.

The initial decrease in 7T-BOLD signals detected by hyperalignment contains information to decode facial expressions.

The initial decrease in the blood oxygenation level-dependent (BOLD) signal reflects primary neuronal activity more than the later hemodynamic positive peak responses. Moreover, ultra-high field BOLD has high sensitivity for the initial de-oxygenation signal. However, it is not fully understood how much information about task events and cognitive processes the initial decrease in the BOLD signal contains. Multivoxel pattern analysis (MVPA) of the BOLD signal has enabled the quantification of information contained in the activity patterns, but it has mainly relied on the positive peak responses. Here, we applied a signal-based functional inter-individual alignment algorithm (i.e., hyper-alignment) to a 7T-BOLD timeseries scanned while participants conducted a facial expression discrimination task. We found that the MVPA decoding accuracy in the bilateral amygdala 2 s after the face onset was significantly beyond chance. Furthermore, we confirmed that the voxels contributing to the decoding accuracy at 2 s displayed a decreasing hemodynamics response. These results demonstrated that the initial decrease in 7T-BOLD signals contains finer information about task events and cognitive processes than thought previously.

Gender differences in guilt aversion in Korea and the United Kingdom.

Guilt aversion, which describes the tendency to reduce the discrepancy between a partner's expectation and his/her actual outcome, is a key driving force for cooperation in both the East and West. A recent study based on functional magnetic resonance imaging and online behavioral experiments reported that men show stronger guilt aversion than women and also suggested that men's predominance in guilt aversion arises from stronger sensitivity to social norms. However, since the participants of that study were all Japanese, it remains unaddressed how common the gender difference in guilt aversion is. Here, we conducted online behavioral studies on people from Korea and the UK (Korea; n = 294, UK; n = 347) using the same trust game. We confirmed that men exhibit stronger guilt aversion than women in both countries. Furthermore, consistent with the Japanese study, our Lasso regression analysis for UK participants revealed that Big Five Conscientiousness (rule-based decision) correlated with guilt aversion in men. In contrast, guilt aversion in Korean men correlated with Big Five Neuroticism. Thus, our results suggest that gender differences in guilt aversion are universal but the underlying cognitive processes may be influenced by cultural differences.

Resting functional connectivity of the left inferior frontal gyrus with the dorsomedial prefrontal cortex and temporoparietal junction reflects the social network size for active interactions.

The size of an individual active social network is a key parameter of human social behavior and is correlated with subjective well-being. However, it remains unknown how the social network size of active interactions is represented in the brain. Here, we examined whether resting-state functional magnetic resonance imaging (fMRI) connectivity is associated with the social network size of active interactions using behavioral data of a large sample (N = 222) on Twitter. Region of interest (ROI)-to-ROI analysis, graph theory analysis, seed-based analysis, and decoding analysis together provided compelling evidence that people who have a large social network size of active interactions, as measured by "reply," show higher fMRI connectivity of the left inferior frontal gyrus with the dorsomedial prefrontal cortex and temporoparietal junction, which represents the core of the theory of mind network. These results demonstrated that people who have a large social network size of active interactions maintain activity of the identified functional connectivity in daily life, possibly providing a mechanism for efficient information transmission between the brain networks related to language and theory-of-mind.

A message of the majority with scientific evidence encourages young people to show their prosocial nature in COVID-19 vaccination.

The most promising way to prevent the explosive spread of COVID-19 infection is to achieve herd immunity through vaccination. It is therefore important to motivate those who are less willing to be vaccinated. To address this issue, we conducted an online survey of 6232 Japanese people to investigate age- and gender-dependent differences in attitudes towards COVID-19 vaccination and the underlying psychological processes. We asked participants to read one of nine different messages about COVID-19 vaccination and rate their willingness to be vaccinated. We also collected their 17 social personality trait scores and demographic information. We found that males 10-20 years old were least willing to be vaccinated. We also found that prosocial traits are the driving force for young people, but the motivation in older people also depends on risk aversion and self-interest. Furthermore, an analysis of 9 different messages demonstrated that for young people (particularly males), the message emphasizing the majority's intention to vaccinate and scientific evidence for the safety of the vaccination had the strongest positive effect on the willingness to be vaccinated, suggesting that the "majority + scientific evidence" message nudges young people to show their prosocial nature in action.

Functional Connectivity Basis and Underlying Cognitive Mechanisms for Gender Differences in Guilt Aversion.

Prosocial behavior is pivotal to our society. Guilt aversion, which describes the tendency to reduce the discrepancy between a partner's expectation and his/her actual outcome, drives human prosocial behavior as does well-known inequity aversion. Although women are reported to be more inequity averse than men, gender differences in guilt aversion remain unexplored. Here, we conducted a functional magnetic resonance imaging (fMRI) study (n = 52) and a large-scale online behavioral study (n = 4723) of a trust game designed to investigate guilt and inequity aversions. The fMRI study demonstrated that men exhibited stronger guilt aversion and recruited right dorsolateral prefrontal cortex (DLPFC)-ventromedial PFC (VMPFC) connectivity more for guilt aversion than women, while VMPFC-dorsal medial PFC (DMPFC) connectivity was commonly used in both genders. Furthermore, our regression analysis of the online behavioral data collected with Big Five and demographic factors replicated the gender differences and revealed that Big Five Conscientiousness (rule-based decision) correlated with guilt aversion only in men, but Agreeableness (empathetic consideration) correlated with guilt aversion in both genders. Thus, this study suggests that gender differences in prosocial behavior are heterogeneous depending on underlying motives in the brain and that the consideration of social norms plays a key role in the stronger guilt aversion in men.

Differential ability of network and natural language information on social media to predict interpersonal and mental health traits.

OBJECTIVE: Previous studies have shown that digital footprints (mainly Social Networking Services, or SNS) can predict personality traits centered on the Big Five. The present study investigates to what extent different types of SNS information predicts wider traits and attributes. METHOD: We collected an intensive set of 24 (52 subscales) personality traits and attributes (N = 239) and examined whether machine learning models trained on four different types of SNS (i.e., Twitter) information (network, time, word statistics, and bag of words) predict the traits and attributes. RESULTS: We found that four types of SNS information can predict 23 subscales collectively. Furthermore, we validated our hypothesis that the network and word statistics information, respectively, exhibit unique strengths for the prediction of inter-personal traits such as autism and mental health traits such as schizophrenia and anxiety. We also found that intelligence is predicted by all four types of SNS information. CONCLUSIONS: These results reveal that the different types of SNS information can collectivity predict wider human traits and attributes than previously recognized, and also that each information type has unique predictive strengths for specific traits and attributes, suggesting that personality prediction from SNS is a powerful tool for both personality psychology and information technology.

Dissociable Behavioral and Neural Correlates for Target-Changing and Conforming Behaviors in Interpersonal Aggression.

Actors in interpersonal aggression such as bullies change their targets frequently, but the underlying behavioral and neural mechanisms are unknown. Here, using the catch-ball task we recently developed to examine human interpersonal aggression, we found target-changing and conforming to other participants' aggression are major driving forces of increased aggression (i.e., throwing strong balls). We also found that target-changing was correlated with a participant's extraversion, consistent with a bistrategic view, in which both prosocial and coercive motivations drive interpersonal aggression. In contrast, conforming to others was correlated with social anxiety. In addition, questionnaires about participants' past experiences of bullying suggested that target-changers and conformers were predominantly bullies and victims in the past. An analysis of resting-state functional magnetic resonance imaging (fMRI) revealed that functional connectivity between the dorsal anterior cingulate cortex (dACC) and insula were correlated with target-changing behavior, while functional connectivity between the amygdala and temporo-parietal junction (TPJ) was correlated with conformity. These results demonstrate that target-changing and conforming behaviors have dissociable behavioral and neural mechanisms and may contribute to real-world interpersonal aggressions differently.

Value computations underlying human proposer behavior in the ultimatum game.

Interacting with others to decide how finite resources should be allocated between potentially competing parties is an important part of social life. Considering that not all of our proposals to others are always accepted, the outcomes of such social interactions are probabilistic and risky. Here, we highlight cognitive processes related to value computations in human social interactions, based on mathematical modeling of the proposer behavior in the Ultimatum Game. Our results suggest that the perception of risk is an overarching process across nonsocial and social decision-making domains, whereas the nonlinear weighting of others' acceptance probabilities appears to be more closely associated with social interactive decision-making situations in which others' valuation processes needs to be inferred. Despite the complexity of social interactive decision-making, human participants adjust their risk and probability weighting parameters while interacting with opponents with different social value orientations, and these parameters governing participants' decision-making strategies are influenced by the inferences participants make about their opponents (e.g., how prosocial they think their opponent is relative to themselves), as well as their own social value orientation. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Activity in the dorsal ACC causes deterioration of sequential motor performance due to anxiety.

Performance anxiety can profoundly affect motor performance, even in experts such as professional athletes and musicians. Previously, the neural mechanisms underlying anxiety-induced performance deterioration have predominantly been investigated for individual one-shot actions. Sports and music, however, are characterized by action sequences, where many individual actions are assembled to develop a performance. Here, utilizing a novel differential sequential motor learning paradigm, we first show that performance at the junctions between pre-learnt action sequences is particularly prone to anxiety. Next, utilizing functional magnetic resonance imaging (fMRI), we reveal that performance deterioration at the junctions is parametrically correlated with activity in the dorsal anterior cingulate cortex (dACC). Finally, we show that 1 Hz repetitive transcranial magnetic stimulation of the dACC attenuates the performance deterioration at the junctions. These results demonstrate causality between dACC activity and impairment of sequential motor performance due to anxiety, and suggest new intervention techniques against the deterioration.

Computing Social Value Conversion in the Human Brain.

Social signals play powerful roles in shaping self-oriented reward valuation and decision making. These signals activate social and valuation/decision areas, but the core computation for their integration into the self-oriented decision machinery remains unclear. Here, we study how a fundamental social signal, social value (others' reward value), is converted into self-oriented decision making in the human brain. Using behavioral analysis, modeling, and neuroimaging, we show three-stage processing of social value conversion from the offer to the effective value and then to the final decision value. First, a value of others' bonus on offer, called offered value, was encoded uniquely in the right temporoparietal junction (rTPJ) and also in the left dorsolateral prefrontal cortex (ldlPFC), which is commonly activated by offered self-bonus value. The effective value, an intermediate value representing the effective influence of the offer on the decision, was represented in the right anterior insula (rAI), and the final decision value was encoded in the medial prefrontal cortex (mPFC). Second, using psychophysiological interaction and dynamic causal modeling analyses, we demonstrated three-stage feedforward processing from the rTPJ and ldPFC to the rAI and then from rAI to the mPFC. Further, we showed that these characteristics of social conversion underlie distinct sociobehavioral phenotypes. We demonstrate that the variability in the conversion underlies the difference between prosocial and selfish subjects, as seen from the differential strength of the rAI and ldlPFC coupling to the mPFC responses, respectively. Together, these findings identified fundamental neural computation processes for social value conversion underlying complex social decision making behaviors.SIGNIFICANCE STATEMENT In daily life, we make decisions based on self-interest, but also in consideration for others' status. These social influences modulate valuation and decision signals in the brain, suggesting a fundamental process called value conversion that translates social information into self-referenced decisions. However, little is known about the conversion process and its underlying brain mechanisms. We investigated value conversion using human fMRI with computational modeling and found three essential stages in a progressive brain circuit from social to empathic and decision areas. Interestingly, the brain mechanism of conversion differed between prosocial and individualistic subjects. These findings reveal how the brain processes and merges social information into the elemental flow of self-interested decision making.

Interactive effects of OXTR and GAD1 on envy-associated behaviors and neural responses.

Inequity aversion (negative feelings induced by outcome differences between the self and other) plays a key role in human social behaviors. The neurotransmitters oxytocin and GABA have been implicated in neural responses to inequity. However, it remains poorly understood not only how individual genetic factors related to oxytocin and GABA affect the neural mechanisms behind inequity aversion, but also how these genes interact. To address these issues, we examined relationships between genotypes, behavioral decisions and brain activities during the ultimatum game. We identified interactive effects between the polymorphisms of the oxytocin receptor gene (OXTR) and glutamate decarboxylase 1 gene for GABA synthesis (GAD1) on envy aversion (i.e., disadvantageous inequity aversion) and on envy-induced activity in the dorsal ACC (dACC). Thus, our integrated approach suggested interactive genetic effects between OXTR and GAD1 on envy aversion and the underlying neural substrates.

Behavioral and functional connectivity basis for peer-influenced bystander participation in bullying.

Recent studies have shown that the reactions of bystanders who witness bullying significantly affect whether the bullying persists. However, the underlying behavioral and neural mechanisms that determine a peer-influenced bystander's participation in bullying remain largely unknown. Here, we designed a new 'catch-ball' task where four players choose to throw a sequence of normal or strong (aggressive) balls in turn and examined whether the players (n = 43) participated in other players' bullying. We analyzed behaviors with a computational model that quantifies the tendencies of a participant's (i) baseline propensity for bullying, (ii) reactive revenge, (iii) conformity to bullying, and (iv) capitulation to threat and estimated these effects on the choice of balls. We found only conformity had a positive effect on the throwing of strong balls. Furthermore, we identified a correlation between a participant's conformity and social anxiety. Our mediation analysis of resting-state functional magnetic resonance imaging revealed that there were significant relationships of each participant's functional connectivity between the amygdala and right temporoparietal junction (TPJ) and social anxiety to the participant's conformity to bullying. We also found that amygdala-TPJ connectivity partially mediated the relationship between social anxiety and conformity. These results highlighted the anxiety-based conformity and amygdala network on peer-influenced bystander participation in bullying.

Brain response patterns to economic inequity predict present and future depression indices.

Widening economic inequity has been suggested to associate with depression. However, little is known about the underlying neural mechanisms of this link. Here, we demonstrate that functional magnetic resonance imaging activity patterns in the amygdala and hippocampus induced by the inequity between the self and other rewards during an economic game can predict participants' present and future (measured one year later) depression indices. Such predictions were not possible using participant's behavioural and socio-economic status measures. These findings suggest that sensitivity to economic inequity has a critical effect on human mood states, and the amygdala and hippocampus play a key role in individual differences in the effect.

Selective increase of intention-based economic decisions by noninvasive brain stimulation to the dorsolateral prefrontal cortex.

The intention behind another's action and the impact of the outcome are major determinants of human economic behavior. It is poorly understood, however, whether the two systems share a core neural computation. Here, we investigated whether the two systems are causally dissociable in the brain by integrating computational modeling, functional magnetic resonance imaging, and transcranial direct current stimulation experiments in a newly developed trust game task. We show not only that right dorsolateral prefrontal cortex (DLPFC) activity is correlated with intention-based economic decisions and that ventral striatum and amygdala activity are correlated with outcome-based decisions, but also that stimulation to the DLPFC selectively enhances intention-based decisions. These findings suggest that the right DLPFC is involved in the implementation of intention-based decisions in the processing of cooperative decisions. This causal dissociation of cortical and subcortical backgrounds may indicate evolutionary and developmental differences in the two decision systems.

Effects of subconscious and conscious emotions on human cue-reward association learning.

Life demands that we adapt our behaviour continuously in situations in which much of our incoming information is emotional and unrelated to our immediate behavioural goals. Such information is often processed without our consciousness. This poses an intriguing question of whether subconscious exposure to irrelevant emotional information (e.g. the surrounding social atmosphere) affects the way we learn. Here, we addressed this issue by examining whether the learning of cue-reward associations changes when an emotional facial expression is shown subconsciously or consciously prior to the presentation of a reward-predicting cue. We found that both subconscious (0.027 s and 0.033 s) and conscious (0.047 s) emotional signals increased the rate of learning, and this increase was smallest at the border of conscious duration (0.040 s). These data suggest not only that the subconscious and conscious processing of emotional signals enhances value-updating in cue-reward association learning, but also that the computational processes underlying the subconscious enhancement is at least partially dissociable from its conscious counterpart.

Activity in the nucleus accumbens and amygdala underlies individual differences in prosocial and individualistic economic choices.

Much decision-making requires balancing benefits to the self with benefits to the group. There are marked individual differences in this balance such that individualists tend to favor themselves whereas prosocials tend to favor the group. Understanding the mechanisms underlying this difference has important implications for society and its institutions. Using behavioral and fMRI data collected during the performance of the ultimatum game, we show that individual differences in social preferences for resource allocation, so-called "social value orientation," is linked with activity in the nucleus accumbens and amygdala elicited by inequity, rather than activity in insula, ACC, and dorsolateral pFC. Importantly, the presence of cognitive load made prosocials behave more prosocially and individualists more individualistically, suggesting that social value orientation is driven more by intuition than reflection. In parallel, activity in the nucleus accumbens and amygdala, in response to inequity, tracked this behavioral pattern of prosocials and individualists. In addition, we conducted an impunity game experiment with different participants where they could not punish unfair behavior and found that the inequity-correlated activity seen in prosocials during the ultimatum game disappeared. This result suggests that the accumbens and amygdala activity of prosocials encodes "outcome-oriented emotion" designed to change situations (i.e., achieve equity or punish). Together, our results suggest a pivotal contribution of the nucleus accumbens and amygdala to individual differences in sociality.

Reward prediction error signal enhanced by striatum-amygdala interaction explains the acceleration of probabilistic reward learning by emotion.

Learning does not only depend on rationality, because real-life learning cannot be isolated from emotion or social factors. Therefore, it is intriguing to determine how emotion changes learning, and to identify which neural substrates underlie this interaction. Here, we show that the task-independent presentation of an emotional face before a reward-predicting cue increases the speed of cue-reward association learning in human subjects compared with trials in which a neutral face is presented. This phenomenon was attributable to an increase in the learning rate, which regulates reward prediction errors. Parallel to these behavioral findings, functional magnetic resonance imaging demonstrated that presentation of an emotional face enhanced reward prediction error (RPE) signal in the ventral striatum. In addition, we also found a functional link between this enhanced RPE signal and increased activity in the amygdala following presentation of an emotional face. Thus, this study revealed an acceleration of cue-reward association learning by emotion, and underscored a role of striatum-amygdala interactions in the modulation of the reward prediction errors by emotion.