Trust in reciprocity (TR) is defined as the risky decision to invest valued resources in another party with the hope of mutual benefit. Several fMRI studies have investigated the neural correlates of TR in one-shot and multi-round versions of the investment game (IG). However, an overall characterization of the underlying neural networks remains elusive. Here, we employed a coordinate-based meta-analysis (activation likelihood estimation method, 30 papers) to investigate consistent brain activations in each of the IG stages (i.e., the trust, reciprocity and feedback stage). Our results showed consistent activations in the anterior insula (AI) during trust decisions in the one-shot IG and decisions to reciprocate in the multi-round IG, likely related to representations of aversive feelings. Moreover, decisions to reciprocate also consistently engaged the intraparietal sulcus, probably involved in evaluations of the reciprocity options. On the contrary, trust decisions in the multi-round IG consistently activated the ventral striatum, likely associated with reward prediction error signals. Finally, the dorsal striatum was found consistently recruited during the feedback stage of the multi-round IG, likely related to reinforcement learning. In conclusion, our results indicate different neural networks underlying trust, reciprocity and feedback learning. These findings suggest that although decisions to trust and reciprocate may elicit aversive feelings likely evoked by the uncertainty about the decision outcomes and the pressing requirements of social standards, multiple interactions allow people to build interpersonal trust for cooperation via a learning mechanism by which they arguably learn to distinguish trustworthy from untrustworthy partners.

With new technological advances, advice can come from different sources such as machines or humans, but how individuals respond to such advice and the neural correlates involved need to be better understood. We combined functional MRI and multivariate Granger causality analysis with an X-ray luggage-screening task to investigate the neural basis and corresponding effective connectivity involved with advice utilization from agents framed as experts. Participants were asked to accept or reject good or bad advice from a human or machine agent with low reliability (high false alarm rate). We showed that unreliable advice decreased performance overall and participants interacting with the human agent had a greater depreciation of advice utilization during bad advice compared to the machine agent. These differences in advice utilization can be perceivably due to reevaluation of expectations arising from association of dispositional credibility for each agent. We demonstrated that differences in advice utilization engaged brain regions that may be associated with evaluation of personal characteristics and traits (precuneus, posterior cingulate cortex, temporoparietal junction) and interoception (posterior insula). We found that the right posterior insula and left precuneus were the drivers of the advice utilization network that were reciprocally connected to each other and also projected to all other regions. Our behavioral and neuroimaging results have significant implications for society because of progressions in technology and increased interactions with machines.

As society becomes more reliant on machines and automation, understanding how people utilize advice is a necessary endeavor. Our objective was to reveal the underlying neural associations during advice utilization from expert human and machine agents with fMRI and multivariate Granger causality analysis. During an X-ray luggage-screening task, participants accepted or rejected good or bad advice from either the human or machine agent framed as experts with manipulated reliability (high miss rate). We showed that the machine-agent group decreased their advice utilization compared to the human-agent group and these differences in behaviors during advice utilization could be accounted for by high expectations of reliable advice and changes in attention allocation due to miss errors. Brain areas involved with the salience and mentalizing networks, as well as sensory processing involved with attention, were recruited during the task and the advice utilization network consisted of attentional modulation of sensory information with the lingual gyrus as the driver during the decision phase and the fusiform gyrus as the driver during the feedback phase. Our findings expand on the existing literature by showing that misses degrade advice utilization, which is represented in a neural network involving salience detection and self-processing with perceptual integration.

Focusing on sex differences is necessary to fully understand basic neurobiological processes such as the engagement of large-scale brain networks involved in attention. Prior work suggests that women show enhanced attention during tasks of reward/punishment relative to men. Yet, sex differences in the engagement of neural networks sub serving internal and external focus has been unexplored in regard to reward and punishment. Using data from a large sample (n = 190) of healthy participants from the Human Connectome Project, we investigated sex differences in default mode network (DMN), dorsal attention network (DAN), and frontal parietal network (FPN) activation during exposure to reward and punishment. To determine if sex differences are specific to valenced stimuli, we analyzed network activation during working memory. Results indicate that, relative to men, women have increased suppression of the DMN and greater activation of the DAN during exposure to reward and punishment. Given the relative roles of these networks in internal (DMN) and external (DAN) attention, this pattern of activation suggests that women have enhanced external attention to reward and punishment. In contrast, there were no sex differences in network activation during working memory, indicating that this sex difference is specific to the processing of reward and punishment. These findings suggest a neurobiological explanation for prior work showing women have greater sensitivity to reward/punishment and are more prone to psychiatric disorders characterized by enhanced attention to such stimuli. Furthermore, given the large sample from the Human Connectome Project, the current findings provide general implications for the study of sex as a biological variable in investigation of reward processes.

Third-party punishment (TPP) for norm violations is an essential deterrent in large-scale human societies, and builds on two essential cognitive functions: evaluating legal responsibility and determining appropriate punishment. Despite converging evidence that TPP is mediated by a specific set of brain regions, little is known about their effective connectivity (direction and strength of connections). Applying parametric event-related functional MRI in conjunction with multivariate Granger causality analysis, we asked healthy participants to estimate how much punishment a hypothetical perpetrator deserves for intentionally committing criminal offenses varying in levels of harm. Our results confirmed that TPP legal decisions are based on two domain-general networks: the mentalizing network for evaluating legal responsibility and the central-executive network for determining appropriate punishment. Further, temporal pole (TP) and dorsomedial prefrontal cortex (PFC) emerged as hubs of the mentalizing network, uniquely generating converging output connections to ventromedial PFC, temporo-parietal junction, and posterior cingulate. In particular, dorsomedial PFC received inputs only from TP and both its activation and its connectivity to dorsolateral PFC correlated with degree of punishment. This supports the hypothesis that dorsomedial PFC acts as the driver of the TPP activation pattern, leading to the decision on the appropriate punishment. In conclusion, these results advance our understanding of the organizational elements of the TPP brain networks and provide better insights into the mental states of judges and jurors tasked with blaming and punishing legal wrongs.