Different impressions of other agents obtained through social interaction uniquely modulate dorsal and ventral pathway activities in the social human brain

Beyond human-likeness: Socialness is more influential when attributing mental states to robots

We sought to replicate and expand previous work showing that the more human-like a robot appears, the more willing people are to attribute mind-like capabilities and socially engage with it. Forty-two participants played games against a human, a humanoid robot, a mechanoid robot, and a computer algorithm while undergoing functional neuroimaging. We confirmed that the more human-like the agent, the more participants attributed a mind to them. However, exploratory analyses revealed that the perceived socialness of an agent appeared to be as, if not more, important for mind attribution. Our findings suggest top-down knowledge cues may be equally or possibly more influential than bottom-up stimulus cues when exploring mind attribution in non-human agents. While further work is now required to test this hypothesis directly, these preliminary findings hold important implications for robotic design and to understand and test the flexibility of human social cognition when people engage with artificial agents.

Opinion attribution improves motivation to exchange subjective opinions with humanoid robots

In recent years, the development of robots that can engage in non-task-oriented dialogue with people, such as chat, has received increasing attention. This study aims to clarify the factors that improve the user's willingness to talk with robots in non-task oriented dialogues (e.g., chat). A previous study reported that exchanging subjective opinions makes such dialogue enjoyable and enthusiastic. In some cases, however, the robot's subjective opinions are not realistic, i.e., the user believes the robot does not have opinions, thus we cannot attribute the opinion to the robot. For example, if a robot says that alcohol tastes good, it may be difficult to imagine the robot having such an opinion. In this case, the user's motivation to exchange opinions may decrease. In this study, we hypothesize that regardless of the type of robot, opinion attribution affects the user's motivation to exchange opinions with humanoid robots. We examined the effect by preparing various opinions of two kinds of humanoid robots. The experimental result suggests that not only the users' interest in the topic but also the attribution of the subjective opinions to them influence their motivation to exchange opinions. Another analysis revealed that the android significantly increased the motivation when they are interested in the topic and do not attribute opinions, while the small robot significantly increased it when not interested and attributed opinions. In situations where there are opinions that cannot be attributed to humanoid robots, the result that androids are more motivating when users have the interests even if opinions are not attributed can indicate the usefulness of androids.

A Causal Role of Right Temporoparietal Junction in Prosocial Learning: A Transcranial Direct Current Stimulation Study

Prosocial behavior is a common and important aspect of everyday social life. To behave prosocially, we need to learn the consequences of our actions for other people, known as prosocial learning. Previous studies have identified the right temporoparietal junction (rTPJ) as the critical neurological substrate for prosocial behavior. However, little is known about the causal role of the rTPJ in prosocial learning. To clarify the role of the rTPJ in prosocial learning, we used a reinforcement learning paradigm and transcranial direct current stimulation (tDCS). A total of 75 participants were recruited and randomly assigned to the anodal or sham tDCS group. While receiving tDCS stimulation over the rTPJ, participants were instructed to choose between different stimuli that were probabilistically associated with rewards for themselves in the self-learning condition or for another person in the prosocial-learning condition. Participants were able to learn to obtain rewards for themselves or others, and learning performance in the self-learning condition was better than that in the prosocial-learning condition. However, anodal tDCS over the rTPJ significantly improved learning performance in the prosocial-learning condition. These results indicate that the rTPJ plays a causal role in prosocial learning.

Asymmetric communication: cognitive models of humans toward an android robot

In the development of dialogue systems for android robots, the goal is to achieve human-like communication. However, subtle differences between android robots and humans are noticeable, leading even human-like android robots to be perceived differently. Understanding how humans accept android robots and optimizing their behavior is crucial. Generally, human customers have various expectations and anxieties when interacting with a robotic salesclerk instead of a human. Asymmetric communication arises when android robots treat customers like humans while customers treat robots as machines. Focusing on human-robot interaction in a tourist guide scenario, In this paper, we propose an asymmetric communication strategy that does not use estimation technology for preference information, but instead performs changing the agent's character in order to pretend to tailor to the customer. In line with this, we prepared an experimental method to evaluate asymmetric communication strategies, using video clips to simulate dialogues. Participants completed questionnaires without prior knowledge of whether the salesclerk was human-like or robotic. The method allowed us to assess how participants treated the salesclerk and the effectiveness of the asymmetric communication strategy. Additionally, during our demonstration in a dialogue robot competition, 29 visitors had a positive impression of the android robot's asymmetric communication strategy and reported a high level of satisfaction with the dialogue.

Increased neural activity of right temporo-parietal junction causes different effect on altruism in situations of advantageous and disadvantageous inequity

Altruism is defined as the performance of "costly acts that confer economic benefits on other individuals", which is one of the major puzzles in the behavioural sciences today. Altruistic behaviour not only facilitates interpersonal adaptation and harmony but also enhances social welfare and social responsibility. The right temporo-parietal junction (rTPJ) has been proposed as playing a key role in guiding human altruistic behaviour, but its precise functional contribution to altruistic behaviour in situations of advantageous and disadvantageous inequity remains unclear. The purpose of this study was to modulate the activation of the rTPJ through transcranial direct current stimulation (tDCS) in order to clarify the causal role of the rTPJ in altruistic behaviour in situations of advantageous and disadvantageous inequity. A total of 106 participants were randomly assigned to one of three stimulation conditions: anodal tDCS stimulation on the rTPJ; sham tDCS stimulation on the rTPJ and anodal tDCS stimulation on the primary visual cortex (VC)as the control group, and. After 20 min of stimulation, participants undertook a modified dictator game that measured altruistic behaviour. Mixed-effect logistic regressions were applied to statistical analyses in this study. The results indicated that anodal tDCS over the rTPJ increased participants' altruistic tendency by increasing their tendency to choose altruistic options in trials with higher cost, as well as their tendency to behave altruistically in situations of advantageous but not disadvantageous inequity. These results suggested that increased neural activity of the rTPJ leads to different impacts on altruism in these two different inequity situations.

Role of right temporoparietal junction for counterfactual evaluation of partner's decision in ultimatum game

Humans assess the distributions of resources based on their aversion to unfairness. If a partner distributes in an unfair manner even though the partner had a less unfair distribution option, a recipient will believe that the partner should have chosen the counterfactual option. In this study, we investigated the neural basis for fairness evaluation of actual and counterfactual options in the ultimatum game. In this task, a partner chose one distribution option out of two options, and a participant accepted or rejected the option. The behavioral results showed that the acceptance rate was influenced by counterfactual evaluation (CE), among others, as defined by the difference of monetary amount between the actual and counterfactual options. The functional magnetic resonance imaging results showed that CE was associated with the right ventral angular gyrus (vAG) that provided one of convergent inputs to the supramarginal gyrus related to decision utility, which reflects gross preferences for the distribution options. Furthermore, inhibitory repetitive transcranial magnetic stimulation administered to the right vAG reduced the behavioral component associated with CE. These results suggest that our acceptance/rejection of distribution options relies on multiple processes (monetary amount, disadvantageous inequity, and CE) and that the right vAG causally contributes to CE.

Formalising social representation to explain psychiatric symptoms

Recent work in social cognition has moved beyond a focus on how people process social rewards to examine how healthy people represent other agents and how this is altered in psychiatric disorders. However, formal modelling of social representation has not kept pace with these changes, impeding our understanding of how core aspects of social cognition function, and fail, in psychopathology. Here, we suggest that belief-based computational models provide a basis for an integrated sociocognitive approach to psychiatry, with the potential to address important but unexamined pathologies of social representation, such as maladaptive schemas and illusory social agents.

Modulations of one's sense of agency during human-machine interactions: A behavioural study using a full humanoid robot

Although previous investigations reported a reduced sense of agency when individuals act with traditional machines, little is known about the mechanisms underpinning interactions with human-like automata. The aim of this study was twofold: (1) to investigate the effect of the machine's physical appearance on the individuals' sense of agency and (2) to explore the cognitive mechanisms underlying the individuals' sense of agency when they are engaged in a joint task. Twenty-eight participants performed a joint Simon task together with another human or an automated artificial system as a co-agent. The physical appearance of the automated artificial system was manipulated so that participants could cooperate either with a servomotor or a full humanoid robot during the joint task. Both participants' response times and temporal estimations of action-output delays (i.e., an implicit measure of agency) were collected. Results showed that participants' sense of agency for self- and other-generated actions sharply declined during interactions with the servomotor compared with the human-human interactions. Interestingly, participants' sense of agency for self- and other-generated actions was reinforced when participants interacted with the humanoid robot compared with the servomotor. These results are discussed further.

Behavioral and neuro-cognitive bases for emergence of norms and socially shared realities via dynamic interaction

In the digital era, new socially shared realities and norms emerge rapidly, whether they are beneficial or harmful to our societies. Although these are emerging properties from dynamic interaction, most research has centered on static situations where isolated individuals face extant norms. We investigated how perceptual norms emerge endogenously as shared realities through interaction, using behavioral and fMRI experiments coupled with computational modeling. Social interactions fostered convergence of perceptual responses among people, not only overtly but also at the covert psychophysical level that generates overt responses. Reciprocity played a critical role in increasing the stability (reliability) of the psychophysical function within each individual, modulated by neural activity in the mentalizing network during interaction. These results imply that bilateral influence promotes mutual cognitive anchoring of individual views, producing shared generative models at the collective level that enable endogenous agreement on totally new targets-one of the key functions of social norms.

Evidence of the unidimensional structure of mind perception

The last decade has witnessed intense interest in how people perceive the minds of other entities (humans, non-human animals, and non-living objects and forces) and how this perception impacts behavior. Despite the attention paid to the topic, the psychological structure of mind perception-that is, the underlying properties that account for variance across judgements of entities-is not clear and extant reports conflict in terms of how to understand the structure. In the present research, we evaluated the psychological structure of mind perception by having participants evaluate a wide array of human, non-human animal, and non-animal entities. Using an entirely within-participants design, varied measurement approaches, and data-driven analyses, four studies demonstrated that mind perception is best conceptualized along a single dimension.

The computational relationship between reinforcement learning, social inference, and paranoia

Theoretical accounts suggest heightened uncertainty about the state of the world underpin aberrant belief updates, which in turn increase the risk of developing a persecutory delusion. However, this raises the question as to how an agent’s uncertainty may relate to the precise phenomenology of paranoia, as opposed to other qualitatively different forms of belief. We tested whether the same population (n = 693) responded similarly to non-social and social contingency changes in a probabilistic reversal learning task and a modified repeated reversal Dictator game, and the impact of paranoia on both. We fitted computational models that included closely related parameters that quantified the rigidity across contingency reversals and the uncertainty about the environment/partner. Consistent with prior work we show that paranoia was associated with uncertainty around a partner’s behavioural policy and rigidity in harmful intent attributions in the social task. In the non-social task we found that pre-existing paranoia was associated with larger decision temperatures and commitment to suboptimal cards. We show relationships between decision temperature in the non-social task and priors over harmful intent attributions and uncertainty over beliefs about partners in the social task. Our results converge across both classes of model, suggesting paranoia is associated with a general uncertainty over the state of the world (and agents within it) that takes longer to resolve, although we demonstrate that this uncertainty is expressed asymmetrically in social contexts. Our model and data allow the representation of sociocognitive mechanisms that explain persecutory delusions and provide testable, phenomenologically relevant predictions for causal experiments.

Neural similarity between mentalizing and live social interaction during the transition to adolescence

Social interactions are essential for human development, yet little neuroimaging research has examined their underlying neurocognitive mechanisms using socially interactive paradigms during childhood and adolescence. Recent neuroimaging research has revealed activity in the mentalizing network when children engage with a live social partner, even when mentalizing is not required. While this finding suggests that social‐interactive contexts may spontaneously engage mentalizing, it is not a direct test of how similarly the brain responds to these two contexts. The current study used representational similarity analysis on data from 8‐ to 14‐year‐olds who made mental and nonmental judgments about an abstract character and a live interaction partner during fMRI. A within‐subject, 2 (Mental/Nonmental) × 2 (Peer/Character) design enabled us to examine response pattern similarity between conditions, and estimate fit to three conceptual models of how the two contexts relate: (1) social interaction and mentalizing about an abstract character are represented similarly; (2) interactive peers and abstract characters are represented differently regardless of the evaluation type; and (3) mental and nonmental states are represented dissimilarly regardless of target. We found that the temporal poles represent mentalizing and peer interactions similarly (Model 1), suggesting a neurocognitive link between the two in these regions. Much of the rest of the social brain exhibits different representations of interactive peers and abstract characters (Model 2). Our findings highlight the importance of studying social‐cognitive processes using interactive approaches, and the utility of pattern‐based analyses for understanding how social‐cognitive processes relate to each other.

Mental State Attribution to Robots: A Systematic Review of Conceptions, Methods, and Findings

The topic of mental state attribution to robots has been approached by researchers from a variety of disciplines, including psychology, neuroscience, computer science, and philosophy. As a consequence, the empirical studies that have been conducted so far exhibit considerable diversity in terms of how the phenomenon is described and how it is approached from a theoretical and methodological standpoint. This literature review addresses the need for a shared scientific understanding of mental state attribution to robots by systematically and comprehensively collating conceptions, methods, and findings from 155 empirical studies across multiple disciplines. The findings of the review include that: (1) the terminology used to describe mental state attribution to robots is diverse but largely homogenous in usage; (2) the tendency to attribute mental states to robots is determined by factors such as the age and motivation of the human as well as the behavior, appearance, and identity of the robot; (3) there is a computer < robot < human pattern in the tendency to attribute mental states that appears to be moderated by the presence of socially interactive behavior; (4) there are conflicting findings in the empirical literature that stem from different sources of evidence, including self-report and non-verbal behavioral or neurological data. The review contributes toward more cumulative research on the topic and opens up for a transdisciplinary discussion about the nature of the phenomenon and what types of research methods are appropriate for investigation.

Mutual gaze with a robot affects human neural activity and delays decision-making processes

In most everyday life situations, the brain needs to engage not only in making decisions but also in anticipating and predicting the behavior of others. In such contexts, gaze can be highly informative about others’ intentions, goals, and upcoming decisions. Here, we investigated whether a humanoid robot’s gaze (mutual or averted) influences the way people strategically reason in a social decision-making context. Specifically, participants played a strategic game with the robot iCub while we measured their behavior and neural activity by means of electroencephalography (EEG). Participants were slower to respond when iCub established mutual gaze before their decision, relative to averted gaze. This was associated with a higher decision threshold in the drift diffusion model and accompanied by more synchronized EEG alpha activity. In addition, we found that participants reasoned about the robot’s actions in both conditions. However, those who mostly experienced the averted gaze were more likely to adopt a self-oriented strategy, and their neural activity showed higher sensitivity to outcomes. Together, these findings suggest that robot gaze acts as a strong social signal for humans, modulating response times, decision threshold, neural synchronization, as well as choice strategies and sensitivity to outcomes. This has strong implications for all contexts involving human-robot interaction, from robotics to clinical applications.

Do People Regard Robots as Human-Like Social Partners? Evidence From Perspective-Taking in Spatial Descriptions

Spatial communications are essential to the survival and social interaction of human beings. In science fiction and the near future, robots are supposed to be able to understand spatial languages to collaborate and cooperate with humans. However, it remains unknown whether human speakers regard robots as human-like social partners. In this study, human speakers describe target locations to an imaginary human or robot addressee under various scenarios varying in relative speaker–addressee cognitive burden. Speakers made equivalent perspective choices to human and robot addressees, which consistently shifted according to the relative speaker–addressee cognitive burden. However, speakers’ perspective choice was only significantly correlated to their social skills when the addressees were humans but not robots. These results suggested that people generally assume robots and humans with equal capabilities in understanding spatial descriptions but do not regard robots as human-like social partners.

Attachment security and striatal functional connectivity in typically developing children

Attachment security is formed through interactions with a main caregiver during the first three years of life and reflects inter-individual differences in mental representations for the relationship. The striatum is known to be a key structure to initiate attachment behaviours and maintain attachment relationships as well as to modulate reward-related processing as part of the approach module in current neurobiological models of human attachment. Although findings have suggested critical roles of the striatum in inter-individual differences in attachment, most studies were based on a wide variety of tasks and very few have investigated these associations in intrinsic brain connectivity in typically developing children. In the present study, using resting-state functional magnetic resonance imaging, we examined the striatal functional connectivity according to children’s attachment security in 68 nine-year-olds (Secure attachment = 39, Insecure attachment = 29, mean age/SD = 9.62/0.69). Children with secure attachment demonstrated increased functional connectivity in the tempro-limbic region, compared to children with insecure attachment. In addition, the child-reported attachment security scores were negatively associated with the caudate-prefrontal connectivity, but positively with the putamen-visual area connectivity. These data demonstrate that inter-individual differences in attachment can be captured in striatal functional connectivity organization in the typical brain.

Behavioral Cues of Humanness in Complex Environments: How People Engage With Human and Artificially Intelligent Agents in a Multiplayer Videogame

The development of AI that can socially engage with humans is exciting to imagine, but such advanced algorithms might prove harmful if people are no longer able to detect when they are interacting with non-humans in online environments. Because we cannot fully predict how socially intelligent AI will be applied, it is important to conduct research into how sensitive humans are to behaviors of humans compared to those produced by AI. This paper presents results from a behavioral Turing Test, in which participants interacted with a human, or a simple or "social" AI within a complex videogame environment. Participants (66 total) played an open world, interactive videogame with one of these co-players and were instructed that they could interact non-verbally however they desired for 30 min, after which time they would indicate their beliefs about the agent, including three Likert measures of how much participants trusted and liked the co-player, the extent to which they perceived them as a "real person," and an interview about the overall perception and what cues participants used to determine humanness. T-tests, Analysis of Variance and Tukey's HSD was used to analyze quantitative data, and Cohen's Kappa and χ2 was used to analyze interview data. Our results suggest that it was difficult for participants to distinguish between humans and the social AI on the basis of behavior. An analysis of in-game behaviors, survey data and qualitative responses suggest that participants associated engagement in social interactions with humanness within the game.

Neural mechanisms of deception in a social context: an fMRI replication study

Deception is a form of manipulation aimed at misleading another person by conveying false or truthful messages. Manipulative truthful statements could be considered as sophisticated deception and elicit an increased cognitive load. However, only one fMRI study reported its neural correlates. To provide independent evidence for sophisticated deception, we carried out an fMRI study replicating the experimental paradigm and Bayesian statistical approach utilized in that study. During the experiment, participants played a game against an opponent by sending deliberate deceptive or honest messages. Compared to truth-telling, deceptive intentions, regardless of how they were fulfilled, were associated with increased BOLD signals in the bilateral temporoparietal junction (TPJ), left precuneus, and right superior temporal sulcus (STS). The right TPJ participates in the attribution of mental states, acting in a social context, and moral behaviour. Moreover, the other revealed brain areas have been considered nodes in the theory of mind brain neural system. Therefore, the obtained results reflect an increased demand for socio‑cognitive processes associated with deceptive intentions. We replicated the original study showing the involvement of the right TPJ and expanded upon it by revealing the involvement of the left TPJ, left precuneus and right STS in actions with deceptive intentions.

Re-imaging the intentional stance

The commonly used paradigm to investigate Dennet's 'intentional stance' compares neural activation when participants compete with a human versus a computer. This paradigm confounds whether the opponent is natural or artificial and whether it is intentional or an automaton. This functional magnetic resonance imaging study is, to our knowledge, the first to investigate the intentional stance by orthogonally varying perceptions of the opponents' intentionality (responding actively or passively according to a script) and embodiment (human or a computer). The mere perception of the opponent (whether human or computer) as intentional activated the mentalizing network: the temporoparietal junction (TPJ) bilaterally, right temporal pole, anterior paracingulate cortex (aPCC) and the precuneus. Interacting with humans versus computers induced activations in a more circumscribed right lateralized subnetwork within the mentalizing network, consisting of the TPJ and the aPCC, possibly reflective of the tendency to spontaneously attribute intentionality to humans. The interaction between intentionality (active versus passive) and opponent (human versus computer) recruited the left frontal pole, possibly in response to violations of the default intentional stance towards humans and computers. Employing an orthogonal design is important to adequately capture Dennett's conception of the intentional stance as a mentalizing strategy that can apply equally well to humans and other intentional agents.

Dissociable roles of left and right temporoparietal junction in strategic competitive interaction

Although many studies have shown that the temporoparietal junction (TPJ) is involved in inferring others' beliefs, neural correlates of 'second-order' inferences (inferring another's inference about one's own belief) are still elusive. Here we report a functional magnetic resonance imaging experiment to examine the involvement of TPJ for second-order inferences. Participants played an economic game with three types of opponents: a human opponent outside the scanner, an artificial agent that followed a fixed probabilistic strategy according to a game-theoretic solution (FIX) and an artificial agent that adjusted its choices through a machine-learning algorithm (LRN). Participants' choice behaviors against the human opponent and LRN were similar but remarkably different from those against FIX. The activation of the left TPJ (LTPJ) was correlated with choice behavior against the human opponent and LRN but not against FIX. The overall activity pattern of the LTPJ for the human opponent was also similar to that for LRN but not for FIX. In contrast, the right TPJ (RTPJ) showed higher activation for the human opponent than FIX and LRN. These results suggest that, while the RTPJ is associated with the perception of human agency, the LTPJ is involved in second-order inferences in strategic decision making.

Using second-person neuroscience to elucidate the mechanisms of social interaction

Although a large proportion of our lives are spent participating in social interactions, the investigation of the neural mechanisms supporting these interactions has largely been restricted to situations of social observation - that is, situations in which an individual observes a social stimulus without opportunity for interaction. In recent years, efforts have been made to develop a truly social, or 'second-person', neuroscientific approach to these investigations in which neural processes are examined within the context of a real-time reciprocal social interaction. These developments have helped to elucidate the behavioural and neural mechanisms of social interactions; however, further theoretical and methodological innovations are still needed. Findings to date suggest that the neural mechanisms supporting social interaction differ from those involved in social observation and highlight a role of the so-called 'mentalizing network' as important in this distinction. Taking social interaction seriously may also be particularly important for the advancement of the neuroscientific study of different psychiatric conditions.

Brain stimulation to left prefrontal cortex modulates attentional orienting to gaze cues

In social interactions, we rely on non-verbal cues like gaze direction to understand the behaviour of others. How we react to these cues is determined by the degree to which we believe that they originate from an entity with a mind capable of having internal states and showing intentional behaviour, a process called mind perception. While prior work has established a set of neural regions linked to mind perception, research has just begun to examine how mind perception affects social-cognitive mechanisms like gaze processing on a neuronal level. In the current experiment, participants performed a social attention task (i.e. attentional orienting to gaze cues) with either a human or a robot agent (i.e. manipulation of mind perception) while transcranial direct current stimulation (tDCS) was applied to prefrontal and temporo-parietal brain areas. The results show that temporo-parietal stimulation did not modulate mechanisms of social attention, neither in response to the human nor in response to the robot agent, whereas prefrontal stimulation enhanced attentional orienting in response to human gaze cues and attenuated attentional orienting in response to robot gaze cues. The findings suggest that mind perception modulates low-level mechanisms of social cognition via prefrontal structures, and that a certain degree of mind perception is essential in order for prefrontal stimulation to affect mechanisms of social attention. This article is part of the theme issue 'From social brains to social robots: applying neurocognitive insights to human-robot interaction'.

A novel fMRI paradigm to dissociate the behavioral and neural components of mixed-strategy decision making from non-strategic decisions in humans

During competitive interactions, such as predator-prey or team sports, the outcome of one's actions is dependent on both their own choices and those of their opponents. Success in these rivalries requires that individuals choose dynamically and unpredictably, often adopting a mixed strategy. Understanding the neural basis of strategic decision making is complicated by the fact that it recruits various cognitive processes that are often shared with non-strategic forms of decision making, such as value estimation, working memory, response inhibition, response selection, and reward processes. Although researchers have explored neural activity within key brain regions during mixed-strategy games, how brain activity differs in the context of strategic interactions versus non-strategic choices is not well understood. We developed a novel behavioral paradigm to dissociate choice behavior during mixed-strategy interactions from non-strategic choices, and we used task-based functional magnetic resonance imaging (fMRI) to contrast brain activation. In a block design, participants competed in the classic mixed-strategy game, "matching pennies," against a dynamic computer opponent designed to exploit predictability in players' response patterns. Results were contrasted with a non-strategic task that had comparable sensory input, motor output, and reward rate; thus, differences in behavior and brain activation reflect strategic processes. The mixed-strategy game was associated with activation of a distributed cortico-striatal network compared to the non-strategic task. We propose that choosing in mixed-strategy contexts requires additional cognitive demands present to a lesser degree during the control task, illustrating the strength of this design in probing function of cognitive systems beyond core sensory, motor, and reward processes.

University students’ mobile news consumption activities and evaluative/affective reactions to political news during election campaigns: A diary study

Smartphones have now become routinely used tools for people’s everyday life news consumption. This article presents a diary study involving 49 university students in the United States documenting their process of consuming political news via smartphones. Participants reported the information about the news and used 23 pairs of semantic differential scales to evaluate and express their affective reactions to the news. Among 176 political news items submitted, the highest proportion was election news. Significant demographic differences were found in participants’ choices of semantic adjectives. Differences were also found in proportions of election and non-election news submitted. A higher proportion of election news was marked as ‘light’, ‘stale’, ‘shallow’, ‘worthless’, ‘dishonest’ and ‘harmful’ than those labelled for non-election news. Findings provide valuable insights into university students’ political news mobile consumption activities and their assessment and sentiment surrounding election news and general political news during the 2016 US Presidential election campaign.

Cues of Violent Intergroup Conflict Diminish Perceptions of Robotic Personhood

Convergent lines of evidence indicate that anthropomorphic robots are represented using neurocognitive mechanisms typically employed in social reasoning about other people. Relatedly, a growing literature documents that contexts of threat can exacerbate coalitional biases in social perceptions. Integrating these research programs, the present studies test whether cues of violent intergroup conflict modulate perceptions of the intelligence, emotional experience, or overall personhood of robots. In Studies 1 and 2, participants evaluated a large, bipedal all-terrain robot; in Study 3, participants evaluated a small, social robot with humanlike facial and vocal characteristics. Across all studies, cues of violent conflict caused significant decreases in perceived robotic personhood, and these shifts were mediated by parallel reductions in emotional connection with the robot (with no significant effects of threat on attributions of intelligence/skill). In addition, in Study 2, participants in the conflict condition estimated the large bipedal robot to be less effective in military combat, and this difference was mediated by the reduction in perceived robotic personhood. These results are discussed as they motivate future investigation into the links among threat, coalitional bias and human–robot interaction.

Theory of Mind and Humanoid Robots From a Lifespan Perspective

Abstract. This review focuses on some relevant issues concerning the relationship between theory of mind (ToM) and humanoid robots. Humanoid robots are employed in different everyday-life contexts, so it seems relevant to question whether the relationships between human beings and humanoids can be characterized by a mode of interaction typical of the relationships between human beings, that is, the attribution of mental states. Because ToM development continuously undergoes changes from early childhood to late adulthood, we adopted a lifespan perspective. We analyzed contributions from the literature by organizing them around the partition between “mental states and actions” and “human-like features.” Finally, we considered how studying human–robot interaction, within a ToM context, can contribute to our understanding of the intersubjective nature of this interaction.

Fronto-parietal coding of goal-directed actions performed by artificial agents

With advances in technology, artificial agents such as humanoid robots will soon become a part of our daily lives. For safe and intuitive collaboration, it is important to understand the goals behind their motor actions. In humans, this process is mediated by changes in activity in fronto-parietal brain areas. The extent to which these areas are activated when observing artificial agents indicates the naturalness and easiness of interaction. Previous studies indicated that fronto-parietal activity does not depend on whether the agent is human or artificial. However, it is unknown whether this activity is modulated by observing grasping (self-related action) and pointing actions (other-related action) performed by an artificial agent depending on the action goal. Therefore, we designed an experiment in which subjects observed human and artificial agents perform pointing and grasping actions aimed at two different object categories suggesting different goals. We found a signal increase in the bilateral inferior parietal lobule and the premotor cortex when tool versus food items were pointed to or grasped by both agents, probably reflecting the association of hand actions with the functional use of tools. Our results show that goal attribution engages the fronto-parietal network not only for observing a human but also a robotic agent for both self-related and social actions. The debriefing after the experiment has shown that actions of human-like artificial agents can be perceived as being goal-directed. Therefore, humans will be able to interact with service robots intuitively in various domains such as education, healthcare, public service, and entertainment.

Interacting With Robots to Investigate the Bases of Social Interaction

Humans show a great natural ability at interacting with each other. Such efficiency in joint actions depends on a synergy between planned collaboration and emergent coordination, a subconscious mechanism based on a tight link between action execution and perception. This link supports phenomena as mutual adaptation, synchronization, and anticipation, which cut drastically the delays in the interaction and the need of complex verbal instructions and result in the establishment of joint intentions, the backbone of social interaction. From a neurophysiological perspective, this is possible, because the same neural system supporting action execution is responsible of the understanding and the anticipation of the observed action of others. Defining which human motion features allow for such emergent coordination with another agent would be crucial to establish more natural and efficient interaction paradigms with artificial devices, ranging from assistive and rehabilitative technology to companion robots. However, investigating the behavioral and neural mechanisms supporting natural interaction poses substantial problems. In particular, the unconscious processes at the basis of emergent coordination (e.g., unintentional movements or gazing) are very difficult-if not impossible-to restrain or control in a quantitative way for a human agent. Moreover, during an interaction, participants influence each other continuously in a complex way, resulting in behaviors that go beyond experimental control. In this paper, we propose robotics technology as a potential solution to this methodological problem. Robots indeed can establish an interaction with a human partner, contingently reacting to his actions without losing the controllability of the experiment or the naturalness of the interactive scenario. A robot could represent an "interactive probe" to assess the sensory and motor mechanisms underlying human-human interaction. We discuss this proposal with examples from our research with the humanoid robot iCub, showing how an interactive humanoid robot could be a key tool to serve the investigation of the psychological and neuroscientific bases of social interaction.

Deceptive but Not Honest Manipulative Actions Are Associated with Increased Interaction between Middle and Inferior Frontal gyri

The prefrontal cortex is believed to be responsible for execution of deceptive behavior and its involvement is associated with greater cognitive efforts. It is also generally assumed that deception is associated with the inhibition of default honest actions. However, the precise neurophysiological mechanisms underlying this process remain largely unknown. The present study was aimed to use functional magnetic resonance imaging to reveal the underlying functional integration within the prefrontal cortex during the task which requires that subjects to deliberately mislead an opponent through the sequential execution of deceptive and honest claims. To address this issue, we performed psychophysiological interaction (PPI) analysis, which allows for statistical assessment of changes in functional relationships between active brain areas in changing psychological contexts. As a result the whole brain PPI-analysis established that both manipulative honest and deceptive claiming were associated with an increase in connectivity between the left middle frontal gyrus and right temporo-parietal junction (rTPJ). Taking into account the role played by rTPJ in processes associated with the theory of mind the revealed data can reflect possible influence of socio-cognitive context on the process of selecting manipulative claiming regardless their honest or deceptive nature. Direct comparison between deceptive and honest claims revealed pattern enhancement of coupling between the left middle frontal gyrus and the left inferior frontal gyrus. This finding provided evidence that the execution of deception relies to a greater extent on higher-order hierarchically-organized brain mechanisms of executive control required to select between two competing deceptive or honest task sets.

Mind-Reading and Behavior-Reading against Agents with and without Anthropomorphic Features in a Competitive Situation

Humans use two distinct cognitive strategies separately to understand and predict other humans' behavior. One is mind-reading, in which an internal state such as an intention or an emotional state is assumed to be a source of a variety of behaviors. The other is behavior-reading, in which an actor's behavior is modeled based on stimulus-response associations without assuming internal states behind the behavior. We hypothesize that anthropomorphic features are key for an observer switching between these two cognitive strategies in a competitive situation. We provide support for this hypothesis through two studies using four agents with different appearances. We show that only a human agent was thought to possess both the ability to generate a variety of behaviors and internal mental states, such as minds and emotions (Study 1). We also show that humans used mixed (opposing) strategies against a human agent and exploitative strategies against the agents with mechanical appearances when they played a repeated zero-sum game (Study 2). Our findings show that humans understand that human behavior is varied; that humans have internal states, such as minds and emotions; that the behavior of machines is governed by a limited number of fixed rules; and that machines do not possess internal mental states. Our findings also suggest that the function of mind-reading is to trigger a strategy for use against agents with variable behavior and that humans exploit others who lack behavioral variability based on behavior-reading in a competitive situation.

We perceive a mind in a robot when we help it

People sometimes perceive a mind in inorganic entities like robots. Psychological research has shown that mind perception correlates with moral judgments and that immoral behaviors (i.e., intentional harm) facilitate mind perception toward otherwise mindless victims. We conducted a vignette experiment (N = 129; M_age = 21.8 ± 6.0 years) concerning human-robot interactions and extended previous research’s results in two ways. First, mind perception toward the robot was facilitated when it received a benevolent behavior, although only when participants took the perspective of an actor. Second, imagining a benevolent interaction led to more positive attitudes toward the robot, and this effect was mediated by mind perception. These results help predict what people’s reactions in future human-robot interactions would be like, and have implications for how to design future social rules about the treatment of robots.

Semantic Differential Scale Method Can Reveal Multi-Dimensional Aspects of Mind Perception

As humans, we tend to perceive minds in both living and non-living entities, such as robots. From a questionnaire developed in a previous mind perception study, authors found that perceived minds could be located on two dimensions “experience” and “agency.” This questionnaire allowed the assessment of how we perceive minds of various entities from a multi-dimensional point of view. In this questionnaire, subjects had to evaluate explicit mental capacities of target characters (e.g., capacity to feel hunger). However, we sometimes perceive minds in non-living entities, even though we cannot attribute these evidently biological capacities to the entity. In this study, we performed a large-scale web survey to assess mind perception by using the semantic differential scale method. We revealed that two mind dimensions “emotion” and “intelligence,” respectively, corresponded to the two mind dimensions (experience and agency) proposed in a previous mind perception study. We did this without having to ask about specific mental capacities. We believe that the semantic differential scale is a useful method to assess the dimensions of mind perception especially for non-living entities that are hard to be attributed to biological capacities.

Contribution of Neuroimaging Studies to Understanding Development of Human Cognitive Brain Functions

Humans experience significant physical and mental changes from birth to adulthood, and a variety of perceptual, cognitive and motor functions mature over the course of approximately 20 years following birth. To deeply understand such developmental processes, merely studying behavioral changes is not sufficient; simultaneous investigation of the development of the brain may lead us to a more comprehensive understanding. Recent advances in noninvasive neuroimaging technologies largely contribute to this understanding. Here, it is very important to consider the development of the brain from the perspectives of “structure” and “function” because both structure and function of the human brain mature slowly. In this review, we first discuss the process of structural brain development, i.e., how the structure of the brain, which is crucial when discussing functional brain development, changes with age. Second, we introduce some representative studies and the latest studies related to the functional development of the brain, particularly for visual, facial recognition, and social cognition functions, all of which are important for humans. Finally, we summarize how brain science can contribute to developmental study and discuss the challenges that neuroimaging should address in the future.

The Anterior Insula Tracks Behavioral Entropy during an Interpersonal Competitive Game

In competitive situations, individuals need to adjust their behavioral strategy dynamically in response to their opponent’s behavior. In the present study, we investigated the neural basis of how individuals adjust their strategy during a simple, competitive game of matching pennies. We used entropy as a behavioral index of randomness in decision-making, because maximizing randomness is thought to be an optimal strategy in the game, according to game theory. While undergoing functional magnetic resonance imaging (fMRI), subjects played matching pennies with either a human or computer opponent in each block, although in reality they played the game with the same computer algorithm under both conditions. The winning rate of each block was also manipulated. Both the opponent (human or computer), and the winning rate, independently affected subjects’ block-wise entropy during the game. The fMRI results revealed that activity in the bilateral anterior insula was positively correlated with subjects’ (not opponent’s) behavioral entropy during the game, which indicates that during an interpersonal competitive game, the anterior insula tracked how uncertain subjects’ behavior was, rather than how uncertain subjects felt their opponent's behavior was. Our results suggest that intuitive or automatic processes based on somatic markers may be a key to optimally adjusting behavioral strategies in competitive situations.

In our own image? Emotional and neural processing differences when observing human-human vs human-robot interactions

Notwithstanding the significant role that human-robot interactions (HRI) will play in the near future, limited research has explored the neural correlates of feeling eerie in response to social robots. To address this empirical lacuna, the current investigation examined brain activity using functional magnetic resonance imaging while a group of participants (n = 26) viewed a series of human-human interactions (HHI) and HRI. Although brain sites constituting the mentalizing network were found to respond to both types of interactions, systematic neural variation across sites signaled diverging social-cognitive strategies during HHI and HRI processing. Specifically, HHI elicited increased activity in the left temporal-parietal junction indicative of situation-specific mental state attributions, whereas HRI recruited the precuneus and the ventromedial prefrontal cortex (VMPFC) suggestive of script-based social reasoning. Activity in the VMPFC also tracked feelings of eeriness towards HRI in a parametric manner, revealing a potential neural correlate for a phenomenon known as the uncanny valley. By demonstrating how understanding social interactions depends on the kind of agents involved, this study highlights pivotal sub-routes of impression formation and identifies prominent challenges in the use of humanoid robots.

A specific hypoactivation of right temporo-parietal junction/posterior superior temporal sulcus in response to socially awkward situations in autism

People with autism spectrum disorder (ASD) often have difficulty comprehending social situations in the complex, dynamic contexts encountered in the real world. To study the social brain under conditions which approximate naturalistic situations, we measured brain activity with FUNCTIONAL MAGNETIC RESONANCE IMAGING: while participants watched a full-length episode of the sitcom The Office. Having quantified the degree of social awkwardness at each moment of the episode, as judged by an independent sample of controls, we found that both individuals with ASD and control participants showed reliable activation of several brain regions commonly associated with social perception and cognition (e.g. those comprising the 'mentalizing network') during the more awkward moments. However, individuals with ASD showed less activity than controls in a region near right temporo-parietal junction (RTPJ) extending into the posterior end of the right superior temporal sulcus (RSTS). Further analyses suggested that, despite the free-form nature of the experimental design, this group difference was specific to this RTPJ/RSTS area of the mentalizing network; other regions of interest showed similar activity across groups with respect to both location and magnitude. These findings add support to a body of evidence suggesting that RTPJ/RSTS plays a special role in social processes across modalities and may function atypically in individuals with ASD navigating the social world.

An integrative neural model of social perception, action observation, and theory of mind

In the field of social neuroscience, major branches of research have been instrumental in describing independent components of typical and aberrant social information processing, but the field as a whole lacks a comprehensive model that integrates different branches. We review existing research related to the neural basis of three key neural systems underlying social information processing: social perception, action observation, and theory of mind. We propose an integrative model that unites these three processes and highlights the posterior superior temporal sulcus (pSTS), which plays a central role in all three systems. Furthermore, we integrate these neural systems with the dual system account of implicit and explicit social information processing. Large-scale meta-analyses based on Neurosynth confirmed that the pSTS is at the intersection of the three neural systems. Resting-state functional connectivity analysis with 1000 subjects confirmed that the pSTS is connected to all other regions in these systems. The findings presented in this review are specifically relevant for psychiatric research especially disorders characterized by social deficits such as autism spectrum disorder.

Neural and sympathetic activity associated with exploration in decision-making: further evidence for involvement of insula

We previously reported that sympathetic activity was associated with exploration in decision-making indexed by entropy, which is a concept in information theory and indexes randomness of choices or the degree of deviation from sticking to recent experiences of gains and losses, and that activation of the anterior insula mediated this association. The current study aims to replicate and to expand these findings in a situation where contingency between options and outcomes is manipulated. Sixteen participants performed a stochastic decision-making task in which we manipulated a condition with low uncertainty of gain/loss (contingent-reward condition) and a condition with high uncertainty of gain/loss (random-reward condition). Regional cerebral blood flow was measured by (15)O-water positron emission tomography (PET), and cardiovascular parameters and catecholamine in the peripheral blood were measured, during the task. In the contingent-reward condition, norepinephrine as an index of sympathetic activity was positively correlated with entropy indicating exploration in decision-making. Norepinephrine was negatively correlated with neural activity in the right posterior insula, rostral anterior cingulate cortex, and dorsal pons, suggesting neural bases for detecting changes of bodily states. Furthermore, right anterior insular activity was negatively correlated with entropy, suggesting influences on exploration in decision-making. By contrast, in the random-reward condition, entropy correlated with activity in the dorsolateral prefrontal and parietal cortices but not with sympathetic activity. These findings suggest that influences of sympathetic activity on exploration in decision-making and its underlying neural mechanisms might be dependent on the degree of uncertainty of situations.