Executive function and underlying brain network distinctions for callous-unemotional traits and conduct problems in adolescents.

The complexity of executive function (EF) impairments in youth antisocial phenotypes of callous-unemotional (CU) traits and conduct problems (CP) challenge identifying phenotypic specific EF deficits. We can redress these challenges by (1) accounting for EF measurement error and (2) testing distinct functional brain properties accounting for differences in EF. Thus, we employed a latent modeling approach for EFs (inhibition, shifting, fluency, common EF) and extracted connection density from matching contemporary EF brain models with a sample of 112 adolescents (ages 13-17, 42% female). Path analysis indicated CU traits associated with lower inhibition. Inhibition network density positively associated with inhibition, but this association was strengthened by CU and attenuated by CP. Common EF associated with three-way interactions between density*CP by CU for the inhibition and shifting networks. This suggests those higher in CU require their brain to work harder for lower inhibition, whereas those higher in CP have difficulty engaging inhibitory brain responses. Additionally, those with CP interacting with CU show distinct brain patterns for a more general EF capacity. Importantly, modeling cross-network connection density in contemporary EF models to test EF involvement in core impairments in CU and CP may accelerate our understanding of EF in these phenotypes.

Efficiency of Heterogenous Functional Connectomes Explains Variance in Callous-Unemotional Traits After Computational Lesioning of Cortical Midline and Salience Regions.

Introduction: Callous-unemotional (CU) traits are a youth antisocial phenotype hypothesized to be a result of differences in the integration of multiple brain systems. However, mechanistic insights into these brain systems are a continued challenge. Where prior work describes activation and connectivity, new mechanistic insights into the brain's functional connectome can be derived by removing nodes and quantifying changes in network properties (hereafter referred to as computational lesioning) to characterize connectome resilience and vulnerability. Methods: Here, we study the resilience of connectome integration in CU traits by estimating changes in efficiency after computationally lesioning individual-level connectomes. From resting-state data of 86 participants (48% female, age 14.52 ± 1.31) drawn from the Nathan Kline institute's Rockland study, individual-level connectomes were estimated using graphical lasso. Computational lesioning was conducted both sequentially and by targeting global and local hubs. Elastic net regression was applied to determine how these changes explained variance in CU traits. Follow-up analyses characterized modeled node hubs, examined moderation, determined impact of targeting, and decoded the brain mask by comparing regions to meta-analytic maps. Results: Elastic net regression revealed that computational lesioning of 23 nodes, network modularity, and Tanner stage explained variance in CU traits. Hub assignment of selected hubs differed at higher CU traits. No evidence for moderation between simulated lesioning and CU traits was found. Targeting global hubs increased efficiency and targeting local hubs had no effect at higher CU traits. Identified brain mask meta-analytically associated with more emotion and cognitive terms. Although reliable patterns were found across participants, adolescent brains were heterogeneous even for those with a similar CU traits score. Conclusion: Adolescent brain response to simulated lesioning revealed a pattern of connectome resiliency and vulnerability that explains variance in CU traits, which can aid prediction of youth at greater risk for higher CU traits.

A revised prosocial behavior game: Testing associations with psychopathic traits and the effects of moral elevation using a randomized clinical trial.

BACKGROUND: Prosocial behavior is negatively associated with psychopathic traits and paradigms which measure prosocial behavior in the laboratory may be useful in better understanding moderators of this association. METHODS: We revised a previously validated game of prosocial behavior by including a new trial type (i.e., trials where the participant will lose money and the charity will gain money). This version of the game was administered online and participants were randomized to group (exposed to a control stimulus video or a video used to elicit moral elevation, i.e. a positive response to witnessing another's act of kindness). We used repeated game administration to test whether a moral elevation stimulus affected game behavior and moderated the negative association between psychopathic traits and prosocial behavior. RESULTS: Prosocial behavior on the new trial types added in this revised game correlated strongly with prosocial behavior on the old trial type (i.e., trials where the participant will gain money and the charity will lose money; r = 0.71; p-value<0.001; n = 485). Graphing trial acceptance rates by trial characteristics demonstrated expected patterns of behavior. Number of prosocial choices on the game correlated with psychopathic trait score (Levenson Factor 1 score; r = -0.52; p-value<0.001). Game repetition with a control stimulus in between runs, supported high immediate test-retest reliability of overall game behavior. Exposure to the moral elevation stimulus in between runs did not affect game behavior nor moderate the association between psychopathic traits and prosocial behavior. CONCLUSIONS: Choices on this revised game of prosocial behavior, which can be administered online, are associated with psychopathic traits scores. The game appears to have high immediate test-retest reliability. Exposure to the moral elevation stimulus did not affect prosocial behavior or impact the relationship between psychopathic trait scores and prosocial behavior. Future research should continue to test potential moderators of this relationship. Limitations of the current study are discussed.

Resting-state connectivity underlying cognitive control's association with perspective taking in callous-unemotional traits.

Callous-Unemotional (CU) traits are often associated with impairments in perspective taking and cognitive control (regulating goal directed behavior); and adolescents with CU traits demonstrate aberrant brain activation/connectivity in areas underlying these processes. Together cognitive control and perspective taking are thought to link mechanistically to explain CU traits. Because increased cognitive control demands modulate perspective taking ability among both typically developing samples and individuals with elevated CU traits, understanding the neurophysiological substrates of these constructs could inform efforts to alleviate societal costs of antisocial behavior. The present study uses GIMME to examine the heterogenous functional brain properties (i.e., connection density, node centrality) underlying cognitive control's influence on perspective taking among adolescents on a CU trait continuum. Results reveal that cognitive control had a negative indirect association with CU traits via perspective taking; and brain connectivity indirectly associated with lower CU traits - specifically the social network via perspective taking and conflict network via cognitive control. Additionally, less negative connection density between the social and conflict networks was directly associated with higher CU traits. Our results support the growing literature on cognitive control's influence on socio-cognitive functioning in CU traits and extends that work by identifying underlying functional brain properties.

Social cognitive processes explain bias in juror decisions.

Jury decisions are among the most consequential social decisions in which bias plays a notable role. While courts take measures to reduce the influence of non-evidentiary factors, jurors may still incorporate biases into their decisions. One common bias, crime-type bias, is the extent to which the perceived strength of a prosecutor's case depends on the severity of the crime. Moral judgment, affect and social cognition have been proposed as core processes underlying this and other biases. Behavioral evidence alone has been insufficient to distinguish these explanations. To identify the mechanism underlying crime-type bias, we collected functional magnetic resonance imaging patterns of brain activation from mock jurors reading criminal scenarios. Brain patterns from crime-type bias were most similar to those associated with social cognition (mentalizing and racial bias) but not affect or moral judgment. Our results support a central role for social cognition in juror decisions and suggest that crime-type bias and cultural bias may arise from similar mechanisms.

Friend or foe: classifying collaborative interactions using fNIRS.

To succeed, effective teams depend on both cooperative and competitive interactions between individual teammates. Depending on the context, cooperation and competition can amplify or neutralize a team's problem solving ability. Therefore, to assess successful collaborative problem solving, it is first crucial to distinguish competitive from cooperative interactions. We investigate the feasibility of using lightweight brain sensors to distinguish cooperative from competitive interactions in pairs of participants (N=84) playing a decision-making game involving uncertain outcomes. We measured brain activity using functional near-infrared spectroscopy (fNIRS) from social, motor, and executive areas during game play alone and in competition or cooperation with another participant. To distinguish competitive, cooperative, and alone conditions, we then trained support vector classifiers using combinations of features extracted from fNIRS data. We find that features from social areas of the brain outperform other features for discriminating competitive, cooperative, and alone conditions in cross-validation. Comparing the competitive and alone conditions, social features yield a 5% improvement over motor and executive features. Social features show promise as means of distinguishing competitive and cooperative environments in problem solving settings. Using fNIRS data provides a real-time measure of subjective experience in an ecologically valid environment. These results have the potential to inform intelligent team monitoring to provide better real-time feedback and improve team outcomes in naturalistic settings.

Novel Cognitive Functions Arise at the Convergence of Macroscale Gradients.

Functions in higher-order brain regions are the source of extensive debate. Past trends have been to describe the brain in terms of a set of functional modules, especially posterior cortical areas, but a new emerging paradigm focuses on interactions between neighboring representations. In this review, we synthesize emerging evidence that a variety of novel functions in the higher-order brain regions are due to convergence. Convergence of macroscale gradients brings feature-rich representations into close proximity, presenting an opportunity for novel functions to arise. Using the TPJ as an example, we demonstrate that convergent areas have three properties, they: (1) are at the peak of the processing hierarchy, (2) combine the most abstracted representations, and (3) are equidistant from other convergent areas. As information moves from primary sensory cortices to higher-order brain regions, it becomes abstracted and hierarchical. Eventually, these processing gradients converge at a point equally and maximally distant from their sensory origins. This convergence, which produces multifaceted cognitive functions, such as mentalizing another person's thoughts or projecting into a future space, parallels evolutionary and developmental characteristics of such regions, resulting in new cognitive and affective faculties.

Neural Support for Contributions of Utility and Narrative Processing of Evidence in Juror Decision Making.

Efforts to explain complex human decisions have focused on competing theories emphasizing utility and narrative mechanisms. These are difficult to distinguish using behavior alone. Both narrative and utility theories have been proposed to explain juror decisions, which are among the most consequential complex decisions made in a modern society. Here, we asked jury-eligible male and female subjects to rate the strength of a series of criminal cases while recording the resulting patterns of brain activation. We compared patterns of brain activation associated with evidence accumulation to patterns of brain activation derived from a large neuroimaging database to look for signatures of the cognitive processes associated with different models of juror decision-making. Evidence accumulation correlated with multiple narrative processes, including reading and recall. Of the cognitive processes traditionally viewed as components of utility, activation patterns associated with uncertainty, but not value, were more active with stronger evidence. Independent of utility and narrative, activations linked to reasoning and relational logic also correlated with increasing evidence. Hierarchical modeling of cognitive processes associated with evidence accumulation supported a more prominent role for narrative in weighing evidence in complex decisions. However, utility processes were also associated with evidence accumulation. These complementary findings support an emerging view that integrates utility and narrative processes in complex decisions.SIGNIFICANCE STATEMENT The last decade has seen a sharply increased interest in narrative as a central cognitive process in human decision-making and as an important factor in the evolution of human societies. However, the roles of narrative versus utility models of decision-making remain hotly debated. While available models frequently produce similar behavioral predictions, they rely on different cognitive processes and so their roles can be separated using the right neural tests. Here, we use brain imaging during mock juror decisions to show that cognitive processes associated with narrative, and to a lesser extent utility, were engaged while subjects evaluated evidence. These results are consistent with interactions between narrative and utility processes during complex decision-making.

Resting-state network topology characterizing callous-unemotional traits in adolescence.

BACKGROUND: Callous-unemotional (CU) traits, a youth antisocial phenotype, are hypothesized to associate with aberrant connectivity (dis-integration) across the salience (SAL), default mode (DMN), and frontoparietal (FPN) networks. However, CU traits have a heterogeneous presentation and previous research has not modeled individual heterogeneity in resting-state connectivity amongst adolescents with CU traits. The present study models individual-specific network maps and examines topological features of individual and subgroup maps in relation to CU traits. METHODS: Participants aged 13-17 (n = 84, male = 55%, female = 45%) completed resting-state functional connectivity and the inventory of callous-unemotional traits as part of the Nathan Klein Rockland study. A sparse network approach (GIMME) was used to derive individual-level and subgroup maps of all participants. We then examined heterogeneous network features, including positive and negative connection density, associated with CU traits. RESULTS: Higher rates of CU traits increased probability of inclusion in one subgroup, which had the highest mean level of CU traits. Analysis of network features reveals less density (positive and negative) within the FPN and greater density between DMN-FPN associated with CU traits. DISCUSSION: Findings indicate heterogeneous person-specific connections and some subgroup connections amongst adolescents associate with CU traits. Higher CU traits associate with lower density in the FPN, which has been associated with attention and inhibition, and higher density between the DMN-FPN, which have been linked with cognitive control, social working memory, and empathy. Our findings suggest less efficiency in FPN function which, when considered mechanistically, could result in difficulty suppressing DMN when task positive networks are engaged. This is an area for further exploration but could explain cognitive and socio-affective impairments in CU traits.

No group differences in Traditional Economics Measures of loss aversion and framing effects in bipolar I disorder.

Bipolar disorder (BD) is associated with impaired decision making, yet few studies have adopted paradigms from behavioral economics to decompose which, if any, aspects of decision making may be impacted. This may be particularly relevant for decision-making processes relevant to known difficulties with emotive dysfunction and corresponding reward dysregulation in BD. Participants with bipolar I disorder (BD; n = 44) and non-psychiatric healthy controls (CTL; n = 28) completed three well-validated behavioral economics decision making tasks via a remote-based survey, including loss aversion and framing effects, that examined sensitivity to probabilities and potential gains and losses in monetary and non-monetary domains. Consistent with past work, we found evidence of moderate loss aversion and framing effects across all participants. No group differences were found in any of the measures of loss aversion or framing effects. We report no group differences between bipolar and non-psychiatric groups with respect to loss aversion and framing effects using a remote-based survey approach. These results provide a framework future studies to explore similar tasks in clinical populations and suggest the context and degree to which decision making is altered in BD may be rooted in a more complex cognitive mechanism that warrants future research.

A Nexus Model of Restricted Interests in Autism Spectrum Disorder.

Restricted interests (RIs) in autism spectrum disorder (ASD) are clinically impairing interests of unusual focus or intensity. They are a subtype of restricted and repetitive behaviors which are one of two diagnostic criteria for the disorder. Despite the near ubiquity of RIs in ASD, the neural basis for their development is not well understood. However, recent cognitive neuroscience findings from nonclinical samples and from individuals with ASD shed light on neural mechanisms that may explain the emergence of RIs. We propose the nexus model of RIs in ASD, a novel conceptualization of this symptom domain that suggests that RIs may reflect a co-opting of brain systems that typically serve to integrate complex attention, memory, semantic, and social communication functions during development. The nexus model of RIs hypothesizes that when social communicative development is compromised, brain functions typically located within the lateral surface of cortex may expand into social processing brain systems and alter cortical representations of various cognitive functions during development. These changes, in turn, promote the development of RIs as an alternative process mediated by these brain networks. The nexus model of RIs makes testable predictions about reciprocal relations between the impaired development of social communication and the emergence of RIs in ASD and suggests novel avenues for treatment development.

Identifying brain network topology changes in task processes and psychiatric disorders.

A central goal in neuroscience is to understand how dynamic networks of neural activity produce effective representations of the world. Advances in the theory of graph measures raise the possibility of elucidating network topologies central to the construction of these representations. We leverage a result from the description of lollipop graphs to identify an iconic network topology in functional magnetic resonance imaging data and characterize changes to those networks during task performance and in populations diagnosed with psychiatric disorders. During task performance, we find that task-relevant subnetworks change topology, becoming more integrated by increasing connectivity throughout cortex. Analysis of resting state connectivity in clinical populations shows a similar pattern of subnetwork topology changes; resting scans becoming less default-like with more integrated sensory paths. The study of brain network topologies and their relationship to cognitive models of information processing raises new opportunities for understanding brain function and its disorders.

Neural Mechanisms of Reward Prediction Error in Autism Spectrum Disorder.

Few studies have explored neural mechanisms of reward learning in ASD despite evidence of behavioral impairments of predictive abilities in ASD. To investigate the neural correlates of reward prediction errors in ASD, 16 adults with ASD and 14 typically developing controls performed a prediction error task during fMRI scanning. Results revealed greater activation in the ASD group in the left paracingulate gyrus during signed prediction errors and the left insula and right frontal pole during thresholded unsigned prediction errors. Findings support atypical neural processing of reward prediction errors in ASD in frontostriatal regions critical for prediction coding and reward learning. Results provide a neural basis for impairments in reward learning that may contribute to traits common in ASD (e.g., intolerance of unpredictability).

Modelling the effects of crime type and evidence on judgments about guilt.

Concerns over wrongful convictions have spurred an increased focus on understanding criminal justice decision-making. This study describes an experimental approach that complements conventional mock-juror experiments and case studies by providing a rapid, high-throughput screen for identifying preconceptions and biases that can influence how jurors and lawyers evaluate evidence in criminal cases. The approach combines an experimental decision task derived from marketing research with statistical modeling to explore how subjects evaluate the strength of the case against a defendant. The results show that, in the absence of explicit information about potential error rates or objective reliability, subjects tend to overweight widely used types of forensic evidence, but give much less weight than expected to a defendant's criminal history. Notably, for mock jurors, the type of crime also biases their confidence in guilt independent of the evidence. This bias is positively correlated with the seriousness of the crime. For practicing prosecutors and other lawyers, the crime-type bias is much smaller, yet still correlates with the seriousness of the crime.

Reason's Enemy Is Not Emotion: Engagement of Cognitive Control Networks Explains Biases in Gain/Loss Framing.

In the classic gain/loss framing effect, describing a gamble as a potential gain or loss biases people to make risk-averse or risk-seeking decisions, respectively. The canonical explanation for this effect is that frames differentially modulate emotional processes, which in turn leads to irrational choice behavior. Here, we evaluate the source of framing biases by integrating functional magnetic resonance imaging data from 143 human participants performing a gain/loss framing task with meta-analytic data from >8000 neuroimaging studies. We found that activation during choices consistent with the framing effect were most correlated with activation associated with the resting or default brain, while activation during choices inconsistent with the framing effect was most correlated with the task-engaged brain. Our findings argue against the common interpretation of gain/loss framing as a competition between emotion and control. Instead, our study indicates that this effect results from differential cognitive engagement across decision frames.SIGNIFICANCE STATEMENT The biases frequently exhibited by human decision makers have often been attributed to the presence of emotion. Using a large fMRI sample and analysis of whole-brain networks defined with the meta-analytic tool Neurosynth, we find that neural activity during frame-biased decisions was more significantly associated with default behaviors (and the absence of executive control) than with emotion. These findings point to a role for neuroscience in shaping long-standing psychological theories in decision science.

Two Distinct Moral Mechanisms for Ascribing and Denying Intentionality.

Philosophers and legal scholars have long theorized about how intentionality serves as a critical input for morality and culpability, but the emerging field of experimental philosophy has revealed a puzzling asymmetry. People judge actions leading to negative consequences as being more intentional than those leading to positive ones. The implications of this asymmetry remain unclear because there is no consensus regarding the underlying mechanism. Based on converging behavioral and neural evidence, we demonstrate that there is no single underlying mechanism. Instead, two distinct mechanisms together generate the asymmetry. Emotion drives ascriptions of intentionality for negative consequences, while the consideration of statistical norms leads to the denial of intentionality for positive consequences. We employ this novel two-mechanism model to illustrate that morality can paradoxically shape judgments of intentionality. This is consequential for mens rea in legal practice and arguments in moral philosophy pertaining to terror bombing, abortion, and euthanasia among others.

Resting state networks distinguish human ventral tegmental area from substantia nigra.

Dopaminergic networks modulate neural processing across a spectrum of function from perception to learning to action. Multiple organizational schemes based on anatomy and function have been proposed for dopaminergic nuclei in the midbrain. One schema originating in rodent models delineated ventral tegmental area (VTA), implicated in complex behaviors like addiction, from more lateral substantia nigra (SN), preferentially implicated in movement. However, because anatomy and function in rodent midbrain differs from the primate midbrain in important ways, the utility of this distinction for human neuroscience has been questioned. We asked whether functional definition of networks within the human dopaminergic midbrain would recapitulate this traditional anatomical topology. We first developed a method for reliably defining SN and VTA in humans at conventional MRI resolution. Hand-drawn VTA and SN regions-of-interest (ROIs) were constructed for 50 participants, using individually-localized anatomical landmarks and signal intensity. Individual segmentation was used in seed-based functional connectivity analysis of resting-state functional MRI data; results of this analysis recapitulated traditional anatomical targets of the VTA versus SN. Next, we constructed a probabilistic atlas of the VTA, SN, and the dopaminergic midbrain region (comprised of SN plus VTA) from individual hand-drawn ROIs. The combined probabilistic (SN plus VTA) ROI was then used for connectivity-based dual-regression analysis in two independent resting-state datasets (n = 69 and n = 79). Results of the connectivity-based, dual-regression functional segmentation recapitulated results of the anatomical segmentation, validating the utility of this probabilistic atlas for future research.

Ventromedial prefrontal cortex encodes emotional value.

The ventromedial prefrontal cortex (vmPFC) plays a critical role in processing appetitive stimuli. Recent investigations have shown that reward value signals in the vmPFC can be altered by emotion regulation processes; however, to what extent the processing of positive emotion relies on neural regions implicated in reward processing is unclear. Here, we investigated the effects of emotion regulation on the valuation of emotionally evocative images. Two independent experimental samples of human participants performed a cognitive reappraisal task while undergoing fMRI. The experience of positive emotions activated the vmPFC, whereas the regulation of positive emotions led to relative decreases in vmPFC activation. During the experience of positive emotions, vmPFC activation tracked participants' own subjective ratings of the valence of stimuli. Furthermore, vmPFC activation also tracked normative valence ratings of the stimuli when participants were asked to experience their emotions, but not when asked to regulate them. A separate analysis of the predictive power of vmPFC on behavior indicated that even after accounting for normative stimulus ratings and condition, increased signal in the vmPFC was associated with more positive valence ratings. These results suggest that the vmPFC encodes a domain-general value signal that tracks the value of not only external rewards, but also emotional stimuli.

A nexus model of the temporal-parietal junction.

The temporal-parietal junction (TPJ) has been proposed to support either specifically social functions or non-specific processes of cognition such as memory and attention. To account for diverse prior findings, we propose a nexus model for TPJ function: overlap of basic processes produces novel secondary functions at their convergence. We present meta-analytic evidence that is consistent with the anatomical convergence of attention, memory, language, and social processing in the TPJ, leading to a higher-order role in the creation of a social context for behavior. The nexus model accounts for recent examples of TPJ contributions specifically to decision making in a social context and provides a potential reconciliation for competing claims about TPJ function.