Connectome-based prediction of decreased trust propensity in older adults with mild cognitive impairment: A resting-state functional magnetic resonance imaging study.

Trust propensity (TP) relies more on social than economic rationality to transform the perceived probability of betrayal into positive reciprocity expectations in older adults with normal cognition. While deficits in social rationality have been observed in older adults with mild cognitive impairment (MCI), there is limited research on TP and its associated resting-state functional connectivity (RSFC) mechanisms in this population. To measure TP and related psychological functions (affect, motivation, executive cognition, and social cognition), MCI (n = 42) and normal healthy control (NHC, n = 115) groups completed a one-shot trust game and additional assessments of related psychological functions. RSFC associated with TP was analyzed using connectome-based predictive modeling (CPM) and lesion simulations. Our behavioral results showed that the MCI group trusted less (i.e., had lower TP) than the NHC group, with lower TP associated with higher sensitivity to the probability of betrayal in the MCI group. In the MCI group, only negative CPM models (RSFC negatively correlated with TP) significantly predicted TP, with a high salience network (SN) contribution. In contrast, in the NHC group, positive CPM models (RSFC positively correlated with TP) significantly predicted TP, with a high contribution from the default mode network (DMN). In addition, the total network strength of the NHC-specific positive network was lower in the MCI group than in the NHC group. Our findings demonstrated a decrease in TP in the MCI group compared to the NHC group, which is associated with deficits in social rationality (social cognition, associated with DMN) and increased sensitivity to betrayal (affect, associated with SN) in a trust dilemma. In conclusion, our study contributes to understanding MCI-related alterations in trust and their underlying neural mechanisms.

The anatomical structure of sex differences in trust propensity: A voxel-based morphometry study.

Trust is a key component of human relationships. Sex differences in trust behavior have been elucidated by parental investment theory and social role theory, attributing men's higher trust propensity to their increased engagement in physically and socially risky activities aimed at securing additional resources. Although sex differences in trust behavior exist and the neuropsychological signatures of trust are known, the underlying anatomical structure of sex differences is still unexplored. Our study aimed to investigate the anatomical structure of sex differences in trust behavior toward strangers (i.e., trust propensity, TP) by employing voxel-based morphometry (VBM) in a sample of healthy young adults. We collected behavioral data for TP as measured with participants in the role of trustors completing the one-shot trust game (TG) with anonymous partners as trustees. We conducted primary region of interest (ROI) and exploratory whole-brain (WB) VBM analyses of high-resolution structural images to test for the association between TP and regional gray matter volume (GMV) associated with sex differences. Confirming previous studies, our behavioral results demonstrated that men trusted more than women during the one-shot TG. Our WB analysis showed a greater GMV related to TP in men than women in the precuneus (PreC), whereas our ROI analysis in regions of the default-mode network (dorsomedial prefrontal cortex [dmPFC], PreC, superior temporal gyrus) to simulate the partner's trustworthiness, central-executive network (ventrolateral PFC) to implement a calculus-based trust strategy, and action-perception network (precentral gyrus) to performance cost-benefit calculations, as proposed by a neuropsychoeconomic model of trust. Our findings advance the neuropsychological understanding of sex differences in TP, which has implications for interpersonal partnerships, financial transactions, and societal engagements.

Studying the social mind: An updated summary of findings from the Vietnam Head Injury Study.

Lesion mapping studies allow us to evaluate the potential causal contribution of specific brain areas to human cognition and complement other cognitive neuroscience methods, as several authors have recently pointed out. Here, we present an updated summary of the findings from the Vietnam Head Injury Study (VHIS) focusing on the studies conducted over the last decade, that examined the social mind and its intricate neural and cognitive underpinnings. The VHIS is a prospective, long-term follow-up study of Vietnam veterans with penetrating traumatic brain injury (pTBI) and healthy controls (HC). The scope of the work is to present the studies from the latest phases (3 and 4) of the VHIS, 70 studies since 2011, when the Raymont et al. paper was published (Raymont et al., 2011). These studies have contributed to our understanding of human social cognition, including political and religious beliefs, theory of mind, but also executive functions, intelligence, and personality. This work finally discusses the usefulness of lesion mapping as an approach to understanding the functions of the human brain from basic science and clinical perspectives.

The science of justice: The neuropsychology of social punishment.

The social punishment (SP) of norm violations has received much attention across multiple disciplines. However, current models of SP fail to consider the role of motivational processes, and none can explain the observed behavioral and neuropsychological differences between the two recognized forms of SP: second-party punishment (2PP) and third-party punishment (3PP). After reviewing the literature giving rise to the current models of SP, we propose a unified model of SP which integrates general psychological descriptions of decision-making as a confluence of affect, cognition, and motivation, with evidence that SP is driven by two main factors: the amount of harm (assessed primarily in the salience network) and the norm violator's intention (assessed primarily in the default-mode and central-executive networks). We posit that motivational differences between 2PP and 3PP, articulated in mesocorticolimbic pathways, impact final SP by differentially impacting the assessments of harm and intention done in these domain-general large-scale networks. This new model will lead to a better understanding of SP, which might even improve forensic, procedural, and substantive legal practices.

Cognitive empathy mediates the relationship between gray matter volume size of dorsomedial prefrontal cortex and social network size: A voxel-based morphometry study.

Social networks are an important factor in developing and maintaining social relationships. The social brain network comprises brain regions that differ in terms of their location, structure, and functioning, and these differences tend to vary among individuals with different social network sizes. However, it remains unknown how social cognitive abilities such as empathy can affect social network size. The goal of our study was to examine the relationship between brain regions in the social brain network, empathy, and individual social network size by using the Social Network Index, which measures social network diversity, size, and complexity by assessing 12 different types of relationships. We performed voxel-based morphometry and mediation analyses using data from questionnaires and structural magnetic resonance imaging data in a sample of 204 young adults. Our findings showed that the gray matter volume of the dorsomedial prefrontal cortex (dmPFC) was inversely associated with social network size and cognitive empathy mediated this association, suggesting that decreased gray matter volume in the dmPFC is associated with greater utilization of cognitive empathy, which, in turn, seems to increase social network size. A potential mechanism explaining this inverse relationship could be cognitive pruning, a phenomenon that occurs in the brain between early adolescence and adulthood, but future longitudinal studies are needed. In conclusion, our findings provide information about the neurocognitive mechanisms involved in the formation and maintenance of social networks.

Right BA 10 lesions impair performance on real-world planning but are not sensitive to problem novelty or tower tasks.

The prefrontal cortex (PFC) is associated with many cognitive functions, including planning. In the neuropsychology literature planning is reduced to "look ahead" ability and most extensively studied with the "tower" tasks. The most influential theoretical explanation is that planning is required in the absence of a routine solution and PFC patients have difficulty coping with novelty. There is an alternate view of planning that emphasizes the distinction between real world tasks and laboratory tower tasks. This account focuses on the structure of problem spaces and why patients with lesions to right PFC have difficulty navigating ill-structured problem spaces. To further explore these issues we administered two real world travel planning tasks to 56 Vietnam War veterans with penetrating brain lesions and 14 matched normal controls. One planning task involved familiar knowledge while the other involved knowledge unfamiliar to our participants. Participants also completed the D-KEFS tower task. A subset of 18 patients-with lesions to right anterior prefrontal cortex (BA 10)-were impaired in the travel planning task compared to normal controls. The task familiarity/novelty dimension affected performance across participant groups (familiar-task scores were higher than unfamiliar-task scores), but it did not differentially affect any group. An examination of cognitive strategies utilized by participants revealed that the impaired patient group had difficulty maintaining a sufficient level of abstraction and engaged the task at a much more concrete level than other participants. Interestingly, patients impaired in the real-world planning tasks were not impaired in the tower tasks. We conclude that patients with lesions to right BA 10 have difficulty in real-world planning tasks that can be attributed to difficulties in engaging problems at the appropriate level of abstraction.

Understanding altruistic behavior: The joint role of prefrontal damage and OXTR genotype.

Altruism is a type of prosocial behavior that is carried out in the absence of personal benefit or even at an expense to self. Trait altruism varies greatly across individuals, and the reasons for this variability are still not fully understood. Growing evidence suggests that altruism may be partly determined by the oxytocin receptor (OXTR) gene, which regulates the emotions underlying altruistic attitudes, such as empathy and trust. Neuroimaging and lesion studies have also implied several higher-order brain regions, including the prefrontal cortex, in altruistic behaviors. Yet the existing reports are contradictory and suggest that the top-down control exercised by the prefrontal cortex may promote both altruistic and self-interested behaviors and, thus, could obscure one's natural proclivity towards altruism encoded by OXTR. Here, we hypothesized that extensive prefrontal damage would result in an increased influence of the OXTR genotype on one's altruistic attitudes and actions. To test this hypothesis, we recruited 115 male combat veterans with penetrating traumatic brain injury to the prefrontal cortex and other brain regions, as well as 35 demographically matched control subjects without brain injury. Participants completed a self-report altruism questionnaire and were genotyped for four OXTR single nucleotide polymorphisms implicated in prosocial behavior, including rs53576, rs1042778, rs2254298 and rs7632287. Consistent with the previous studies, we found that individuals homozygotic for the G allele of rs53576 and rs7632287 were significantly more altruistic than carriers of at least one "vulnerable" A allele. Remarkably, in patients with prefrontal cortex damage, greater lesion extent was associated with significantly lower altruism scores in carriers of the A allele of rs7632287, but not in G-homozygotes, suggesting that significant disruption of the prefrontal cortex increased the influence of genetic polymorphisms on prosocial behavior. This study presents the first account of an interaction effect between the OXTR genotype and the location and extent of brain damage.

The connectome-based prediction of trust propensity in older adults: A resting-state functional magnetic resonance imaging study.

A recent neuropsychoeconomic model of trust propensity argues that an individual uses economic (executive functions) and social (social cognition) rationality strategies to transform the risk of treachery (affect) into positive expectations of reciprocity, promoting trust in another person. Previous studies have shown that the trust of older adults is associated with affect and social cognition. However, little is known about the intrinsic functional connectivity correlated with trust propensity or whether trust propensity is associated with executive functions in older adults. In this study, we examined the association between trust propensity (measured by a one-shot trust game [TG]), social preference (measured by a one-shot dictator game), and executive functions (measured by a battery of neuropsychological tests). We also performed connectome-based predictive modeling (CPM) and computational lesion analysis to identify the key large-scale resting-state functional connectivity (RSFC) underlying the prediction of trust propensity. Our behavioral results showed a lower trust propensity in older adults in our study than in younger adults in a previous meta-analysis. Furthermore, trust propensity was associated with social preference, but there was no significant relationship between trust propensity and executive functions. The neuroimaging results showed that the cingulo-opercular network (CON) and the default mode network (DMN), rather than the frontoparietal network (FPN), significantly contributed to the prediction of trust propensity in older adults. Our findings suggest that older adults rely less on economic rationality (executive functions, associated with FPN) in trust games. Rather, they are likely to depend more on social rationality (social cognition, associated with social preference and DMN) to resolve the risk of treachery (affect, associated with CON) in trust dilemmas. This study contributes to a better understanding of the neural underpinnings of older adults' trust propensity.

Connectome-based individualized prediction of reciprocity propensity and sensitivity to framing: a resting-state functional magnetic resonance imaging study.

BACKGROUND: The social representation theory states that individual differences in reciprocity decisions are composed of a stable central core (i.e., reciprocity propensity, RP) and a contextual-dependent periphery (i.e., sensitivity to the framing effect; SFE, the effect by how the decision is presented). However, the neural underpinnings that explain RP and SFE are still unknown. METHOD: Here, we employed prediction and lesion models to decode resting-state functional connectivity (RSFC) of RP and SFE for reciprocity decisions of healthy volunteers who underwent RS functional magnetic resonance imaging and completed one-shot trust (give frame) and distrust (take frame) games as trustees. RESULTS: Regarding the central core, reciprocity rates were positively associated between the give and take frame. Neuroimaging results showed that inter-network RSFC between the default-mode network (DMN; associated with mentalizing) and cingulo-opercular network (associated with cognitive control) contributed to the prediction of reciprocity under both frames. Regarding the periphery, behavioral results demonstrated a significant framing effect-people reciprocated more in the give than in the take frame. Our neuroimaging results revealed that intra-network RSFC of DMN (associated with mentalizing) contributed dominantly to the prediction of SFE. CONCLUSION: Our findings provide evidence for distinct neural mechanisms of RP and SFE in reciprocity decisions.

Functional Connectivity Prediction With Deep Learning for Graph Transformation.

Inferring resting-state functional connectivity (FC) from anatomical brain wiring, known as structural connectivity (SC), is of enormous significance in neuroscience for understanding biological neuronal networks and treating mental diseases. Both SC and FC are networks where the nodes are brain regions, and in SC, the edges are the physical fiber nerves among the nodes, while in FC, the edges are the nodes' coactivation relations. Despite the importance of SC and FC, until very recently, the rapidly growing research body on this topic has generally focused on either linear models or computational models that rely heavily on heuristics and simple assumptions regarding the mapping between FC and SC. However, the relationship between FC and SC is actually highly nonlinear and complex and contains considerable randomness; additional factors, such as the subject's age and health, can also significantly impact the SC-FC relationship and hence cannot be ignored. To address these challenges, here, we develop a novel SC-to-FC generative adversarial network (SF-GAN) framework for mapping SC to FC, along with additional metafeatures based on a newly proposed graph neural network-based generative model that is capable of learning the stochasticity. Specifically, a new graph-based conditional generative adversarial nets model is proposed, where edge convolution layers are leveraged to encode the graph patterns in the SC in the form of a graph representation. New edge deconvolution layers are then utilized to decode the representation back to FC. Additional metafeatures of subjects' profile information are integrated into the graph representation with newly designed sparse-regularized layers that can automatically select features that impact FC. Finally, we have also proposed new post hoc explainer of our SF-GAN, which can identify which subgraphs in SC strongly influence which subgraphs in FC by a new multilevel edge-correlation-guided graph clustering problem. The results of experiments conducted to test the new model confirm that it significantly outperforms existing state-of-the-art methods, with additional interpretability for identifying important metafeatures and subgraphs.

Damage to the dorsolateral prefrontal cortex is associated with repetitive compulsive behaviors in patients with penetrating brain injury.

Background: Damage to cortico-striato-thalamo-cortical (CSTC) circuits is associated with the development of repetitive behaviours in animals and humans. However, the types of repetitive behaviours that are developed after injury to these structures are poorly defined. This study examines the effect of damage to separate elements of CSTC circuits sustained by veterans of the Vietnam War on obsessions, compulsions, and tics. Methods: We performed partial correlations (correcting for cognition, age, education, and global brain damage) between volume loss from traumatic brain injury in specific elements of CSTC circuits (lateral and medial orbitofrontal and dorsolateral prefrontal cortices, anterior cingulate cortex, thalamus, and basal ganglia) and scores on a modified version of the Yale-Brown Obsessive Compulsive Scale Symptom Checklist and the Yale Global Tic Severity Scale in 83 Vietnam war veterans with penetrating brain injuries at different sites throughout the brain. Results: We found that volume loss in the left dorsolateral prefrontal cortex was associated with the development of compulsive behaviours (r=0.32, padj<0.05) whereas volume loss in the basal ganglia was associated with the development of tics (r=0.33, padj<0.05). Conclusion: Our findings indicate that damage to specific CSTC elements can be associated with the development of compulsive behaviours and tics that are not necessarily accompanied by obsessions.

Altered effective connectivity from the posterior insula to the amygdala mediates the relationship between psychopathic traits and endorsement of the Harm foundation.

Psychopathic traits have been demonstrated to be associated with different moral foundations. However, the neuropsychological mechanism underlying the relationship between psychopathic traits and moral foundations remains obscure. Our study examined the effective connectivity (EC) of psychopathy-related brain regions and its association with endorsement to moral foundations (Harm, Fairness, Loyalty, Authority, and Purity)-combining questionnaire measures, resting-state fMRI (RS-fMRI), and Granger causality analysis. We administered the Levenson Self-Report Psychopathy Scale and Moral Foundation Questionnaire to 78 college students after RS-fMRI scanning. Our results showed that total and primary psychopathy negatively predicted endorsement of the Harm foundation. The EC from the posterior insula to the amygdala was negatively associated with primary psychopathy but positively associated with endorsement of the Harm foundation. Altered posterior insula-amygdala EC partially mediated the relationship between primary psychopathy and endorsement of the Harm foundation. Our findings demonstrated that individuals with elevated psychopathic traits may have atypical processes in recognizing and integrating bodily state information into emotional responses -leading to less concern for harm-related morality. Our findings deepen the understanding of the neuropsychological mechanism underlying the relationship between psychopathic traits and morality, providing potential neurobiological explanations for increased moral transgressions, especially those harm-related transgressions, committed by psychopathic individuals.

Evidence of the role of the cerebellum in cognitive theory of mind using voxel-based lesion mapping.

Theory of Mind (ToM) is a social-cognitive skill that allows the understanding of the intentions, beliefs, and desires of others. There is a distinction between affective and cognitive ToM, with evidence showing that these processes rely on partially distinct neural networks. The role of the cerebellum in social cognition has only been rarely explored. In this study, we tested whether the cerebellum is necessary for cognitive and affective ToM performance. We investigated adults with traumatic brain injury (n = 193) and healthy controls (n = 52) using voxel-based lesion-symptom mapping (VLSM) and by measuring the impact on functional connectivity. First, we observed that damage to the cerebellum affected pure Cognitive ToM processing. Further, we found a lateralization effect for the role of the cerebellum in cognitive ToM with participants with left cerebellar injury performing worse than those with right cerebellar injury. Both VLSM and standard statistical analysis provided evidence that left cerebellar Crus I and lobule VI contributed to ToM processing. Lastly, we found that disconnection of the left thalamic projection and the left fronto-striatal fasciculus was associated with poor cognitive ToM performance. Our study is the first to reveal direct causal neuropsychological evidence for a role of the cerebellum in some but not all types of ToM, processing. It reinforces the idea that social cognition relies on a complex network functionally connected through white matter pathways that include the cerebellum. It supports evidence that the neural networks underpinning the different types of ToM can be differentiated.

Designing Man's New Best Friend: Enhancing Human-Robot Dog Interaction through Dog-Like Framing and Appearance.

To understand how to improve interactions with dog-like robots, we evaluated the importance of "dog-like" framing and physical appearance on interaction, hypothesizing multiple interactive benefits of each. We assessed whether framing Aibo as a puppy (i.e., in need of development) versus simply a robot would result in more positive responses and interactions. We also predicted that adding fur to Aibo would make it appear more dog-like, likable, and interactive. Twenty-nine participants engaged with Aibo in a 2 × 2 (framing × appearance) design by issuing commands to the robot. Aibo and participant behaviors were monitored per second, and evaluated via an analysis of commands issued, an analysis of command blocks (i.e., chains of commands), and using a T-pattern analysis of participant behavior. Participants were more likely to issue the "Come Here" command than other types of commands. When framed as a puppy, participants used Aibo's dog name more often, praised it more, and exhibited more unique, interactive, and complex behavior with Aibo. Participants exhibited the most smiling and laughing behaviors with Aibo framed as a puppy without fur. Across conditions, after interacting with Aibo, participants felt Aibo was more trustworthy, intelligent, warm, and connected than at their initial meeting. This study shows the benefits of introducing a socially robotic agent with a particular frame and importance on realism (i.e., introducing the robot dog as a puppy) for more interactive engagement.

An fMRI investigation of the intention-outcome interactions in second- and third-party punishment.

Second-party punishment (SPP) and third-party punishment (TPP) are two basic forms of costly punishment that play an essential role in maintaining social orders. Despite scientific breakthroughs in understanding that costly punishment is driven by an integration of the wrongdoers' intention and the outcome of their actions, so far, few studies have compared the neurocognitive processes associated with the intention-outcome integration between SPP and TPP. Here, we combined economic exchange games measuring SPP and TPP with functional magnetic resonance imaging (fMRI) to compare the neuropsychological architectures underlying the intention-outcome integration during one-shot interactions with anonymous partners across four types of norm violations (no norm, accidental, attempted, and intentional violations). Our behavioral findings showed that third-parties punished only attempted norm violations less frequently than second-parties. Our neuroimaging findings revealed higher activities in the right temporoparietal junction (TPJ) and dorsolateral prefrontal cortex (dlPFC) for attempted norm violations during TPP relative to SPP; more activities in these regions with less punishment frequency; and enhancement of functional connectivity of the right TPJ with the right dlPFC and dorsomedial PFC. Our findings demonstrated specific psychological and neural mechanisms of intention-outcome interactions between SPP and TPP -helping to unravel the complex neurocognitive processes of costly punishment.

Static and dynamic topological organizations of the costly punishment network predict individual differences in punishment propensity.

Human costly punishment plays a vital role in maintaining social norms. Recently, a brain network model is conceptually proposed indicating that the implement of costly punishment depends on a subset of nodes in three high-level networks. This model, however, has not yet been empirically examined from an integrated perspective of large-scale brain networks. Here, we conducted comprehensive graph-based network analyses of resting-state functional magnetic resonance imaging data to explore system-level characteristics of intrinsic functional connectivity among 18 regions related to costly punishment. Nontrivial organizations (small-worldness, connector hubs, and high flexibility) were found that were qualitatively stable across participants and over time but quantitatively exhibited low test-retest reliability. The organizations were predictive of individual costly punishment propensities, which was reproducible on independent samples and robust against different analytical strategies and parameter settings. Moreover, the prediction was specific to system-level network organizations (rather than interregional functional connectivity) derived from positive (rather than negative or combined) connections among the specific (rather than randomly chosen) subset of regions from the three high-order (rather than primary) networks. Collectively, these findings suggest that human costly punishment emerges from integrative behaviors among specific regions in certain functional networks, lending support to the brain network model for costly punishment.

Connectome-based model predicts individual psychopathic traits in college students.

BACKGROUND: Psychopathic traits have been suggested to increase the risk of violations of socio-moral norms. Previous studies revealed that abnormal neural signatures are associated with elevated psychopathic traits; however, whether the intrinsic network architecture can predict psychopathic traits at the individual level remains unclear. METHODS: The present study utilized connectome-based predictive modeling (CPM) to investigate whether whole-brain resting-state functional connectivity (RSFC) can predict psychopathic traits in the general population. Resting-state fMRI data were collected from 84 college students with varying psychopathic traits measured by the Levenson Self-Report Psychopathy Scale (LSRP). RESULTS: Functional connections that were negatively correlated with psychopathic traits predicted individual differences in total LSRP and secondary psychopathy score but not primary score. Particularly, nodes with the most connections in the predictive connectome anchored in the prefrontal cortex (e.g., anterior prefrontal cortex and orbitofrontal cortex) and limbic system (e.g., anterior cingulate cortex and insula). In addition, the connections between the occipital network (OCCN) and cingulo-opercular network (CON) served as a significant predictive connectome for total LSRP and secondary psychopathy score. CONCLUSION: CPM constituted by whole-brain RSFC significantly predicted psychopathic traits individually in the general population. The brain areas including the prefrontal cortex and limbic system and large-scale networks including the CON and OCCN play special roles in the predictive model-possibly reflecting atypical cognitive control and affective processing for individuals with elevated psychopathic traits. These findings may facilitate detection and potential intervention of individuals with maladaptive psychopathic tendency.

The neural signatures of social hierarchy-related learning and interaction: A coordinate- and connectivity-based meta-analysis.

Numerous neuroimaging studies have investigated the neural mechanisms of two mutually independent yet closely related cognitive processes aiding humans to navigate complex societies: social hierarchy-related learning (SH-RL) and social hierarchy-related interaction (SH-RI). To integrate these heterogeneous results into a more fine-grained and reliable characterization of the neural basis of social hierarchy, we combined coordinate-based meta-analyses with connectivity and functional decoding analyses to understand the underlying neuropsychological mechanism of SH-RL and SH-RI. We identified the anterior insula and temporoparietal junction (dominance detection), medial prefrontal cortex (information updating and computation), and intraparietal sulcus region, amygdala, and hippocampus (social hierarchy representation) as consistent activated brain regions for SH-RL, but the striatum, amygdala, and hippocampus associated with reward processing for SH-RI. Our results provide an overview of the neural architecture of the neuropsychological processes underlying how we understand, and interact within, social hierarchy.