A synthesis of evidence for policy from behavioural science during COVID-19.

Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations ('claims') detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms 'physical distancing' and 'social distancing'. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization.

The human hypothalamus coordinates switching between different survival actions.

Comparative research suggests that the hypothalamus is critical in switching between survival behaviors, yet it is unclear if this is the case in humans. Here, we investigate the role of the human hypothalamus in survival switching by introducing a paradigm where volunteers switch between hunting and escape in response to encounters with a virtual predator or prey. Given the small size and low tissue contrast of the hypothalamus, we used deep learning-based segmentation to identify the individual-specific hypothalamus and its subnuclei as well as an imaging sequence optimized for hypothalamic signal acquisition. Across 2 experiments, we employed computational models with identical structures to explain internal movement generation processes associated with hunting and escaping. Despite the shared structure, the models exhibited significantly different parameter values where escaping or hunting were accurately decodable just by computing the parameters of internal movement generation processes. In experiment 2, multi-voxel pattern analyses (MVPA) showed that the hypothalamus, hippocampus, and periaqueductal gray encode switching of survival behaviors while not encoding simple motor switching outside of the survival context. Furthermore, multi-voxel connectivity analyses revealed a network including the hypothalamus as encoding survival switching and how the hypothalamus is connected to other regions in this network. Finally, model-based fMRI analyses showed that a strong hypothalamic multi-voxel pattern of switching is predictive of optimal behavioral coordination after switching, especially when this signal was synchronized with the multi-voxel pattern of switching in the amygdala. Our study is the first to identify the role of the human hypothalamus in switching between survival behaviors and action organization after switching.

The Role of the Medial Prefrontal Cortex in Spatial Margin of Safety Calculations.

Naturalistic observations show that animals pre-empt danger by moving to locations that increase their success in avoiding future threats. To test this in humans, we created a spatial margin of safety (MOS) decision task that quantifies pre-emptive avoidance by measuring the distance subjects place themselves to safety when facing different threats whose attack locations vary in predictability. Behavioral results show that human participants place themselves closer to safe locations when facing threats that attack in spatial locations with more outliers. Using both univariate and multivariate pattern analysis (MVPA) on fMRI data collected during a 2 h session on participants of both sexes, we demonstrate a dissociable role for the vmPFC in MOS-related decision-making. MVPA results revealed that the posterior vmPFC encoded for more unpredictable threats with univariate analyses showing a functional coupling with the amygdala and hippocampus. Conversely, the anterior vmPFC was more active for the more predictable attacks and showed coupling with the striatum. Our findings converge in showing that during pre-emptive danger, the anterior vmPFC may provide a safety signal, possibly via foreseeable outcomes, while the posterior vmPFC drives unpredictable danger signals.

Foraging for foundations in decision neuroscience: insights from ethology.

Modern decision neuroscience offers a powerful and broad account of human behaviour using computational techniques that link psychological and neuroscientific approaches to the ways that individuals can generate near-optimal choices in complex controlled environments. However, until recently, relatively little attention has been paid to the extent to which the structure of experimental environments relates to natural scenarios, and the survival problems that individuals have evolved to solve. This situation not only risks leaving decision-theoretic accounts ungrounded but also makes various aspects of the solutions, such as hard-wired or Pavlovian policies, difficult to interpret in the natural world. Here, we suggest importing concepts, paradigms and approaches from the fields of ethology and behavioural ecology, which concentrate on the contextual and functional correlates of decisions made about foraging and escape and address these lacunae.

Model-based prioritization for acquiring protection.

Protection often involves the capacity to prospectively plan the actions needed to mitigate harm. The computational architecture of decisions involving protection remains unclear, as well as whether these decisions differ from other beneficial prospective actions such as reward acquisition. Here we compare protection acquisition to reward acquisition and punishment avoidance to examine overlapping and distinct features across the three action types. Protection acquisition is positively valenced similar to reward. For both protection and reward, the more the actor gains, the more benefit. However, reward and protection occur in different contexts, with protection existing in aversive contexts. Punishment avoidance also occurs in aversive contexts, but differs from protection because punishment is negatively valenced and motivates avoidance. Across three independent studies (Total N = 600) we applied computational modeling to examine model-based reinforcement learning for protection, reward, and punishment in humans. Decisions motivated by acquiring protection evoked a higher degree of model-based control than acquiring reward or avoiding punishment, with no significant differences in learning rate. The context-valence asymmetry characteristic of protection increased deployment of flexible decision strategies, suggesting model-based control depends on the context in which outcomes are encountered as well as the valence of the outcome.

Ambiguity drives higher-order Pavlovian learning.

In the natural world, stimulus-outcome associations are often ambiguous, and most associations are highly complex and situation-dependent. Learning to disambiguate these complex associations to identify which specific outcomes will occur in which situations is critical for survival. Pavlovian occasion setters are stimuli that determine whether other stimuli will result in a specific outcome. Occasion setting is a well-established phenomenon, but very little investigation has been conducted on how occasion setters are disambiguated when they themselves are ambiguous (i.e., when they do not consistently signal whether another stimulus will be reinforced). In two preregistered studies, we investigated the role of higher-order Pavlovian occasion setting in humans. We developed and tested the first computational model predicting direct associative learning, traditional occasion setting (i.e., 1st-order occasion setting), and 2nd-order occasion setting. This model operationalizes stimulus ambiguity as a mechanism to engage in higher-order Pavlovian learning. Both behavioral and computational modeling results suggest that 2nd-order occasion setting was learned, as evidenced by lack and presence of transfer of occasion setting properties when expected and the superior fit of our 2nd-order occasion setting model compared to the 1st-order occasion setting or direct associations models. These results provide a controlled investigation into highly complex associative learning and may ultimately lead to improvements in the treatment of Pavlovian-based mental health disorders (e.g., anxiety disorders, substance use).

Resting-state functional connectivity of social brain regions predicts motivated dishonesty.

Motivated dishonesty is a typical social behavior varying from person to person. Resting-state fMRI (rsfMRI) is capable of identifying unique patterns from functional connectivity (FC) between brain regions. Recent work has built a link between brain networks in resting state to dishonesty in Western participants. To determine and reproduce the relevant neural patterns and build an interpretable model to predict dishonesty, we analyzed two conceptually similar datasets containing rsfMRI data with different dishonesty tasks. Both tasks implemented the information-passing paradigm, in which monetary rewards were employed to induce dishonesty. We applied connectome-based predictive modeling (CPM) to build a model among FC within and between four social brain networks (reward, self-referential, moral, and cognitive control). The CPM analysis indicated that FCs of social brain networks are predictive of dishonesty rate, especially FCs within reward network, and between self-referential and cognitive control networks. Our study offers an conceptual replication with integrated model to predict dishonesty with rsfMRI, and the results suggest that frequent motivated dishonest decisions may require the higher engagement of social brain regions.

Physiological Responses to a Haunted-House Threat Experience: Distinct Tonic and Phasic Effects.

Threats elicit physiological responses, the frequency and intensity of which have implications for survival. Ethical and practical limitations on human laboratory manipulations present barriers to studying immersive threat. Furthermore, few investigations have examined group effects and concordance with subjective emotional experiences to threat. The current preregistered study measured electrodermal activity in 156 adults while they participated in small groups in a 30-min haunted-house experience involving various immersive threats. Results revealed positive associations between (a) friends and tonic arousal, (b) unexpected attacks and phasic activity (frequency and amplitude), (c) subjective fear and phasic frequency, and (d) dissociable sensitization effects linked to baseline orienting response. Findings demonstrate the relevance of (a) social dynamics (friends vs. strangers) for tonic arousal and (b) subjective fear and threat predictability for phasic arousal.

How cognitive and reactive fear circuits optimize escape decisions in humans.

Flight initiation distance (FID), the distance at which an organism flees from an approaching threat, is an ecological metric of cost-benefit functions of escape decisions. We adapted the FID paradigm to investigate how fast- or slow-attacking "virtual predators" constrain escape decisions. We show that rapid escape decisions rely on "reactive fear" circuits in the periaqueductal gray and midcingulate cortex (MCC), while protracted escape decisions, defined by larger buffer zones, were associated with "cognitive fear" circuits, which include posterior cingulate cortex, hippocampus, and the ventromedial prefrontal cortex, circuits implicated in more complex information processing, cognitive avoidance strategies, and behavioral flexibility. Using a Bayesian decision-making model, we further show that optimization of escape decisions under rapid flight were localized to the MCC, a region involved in adaptive motor control, while the hippocampus is implicated in optimizing decisions that update and control slower escape initiation. These results demonstrate an unexplored link between defensive survival circuits and their role in adaptive escape decisions.

A Collaborator's Reputation Can Bias Decisions and Anxiety under Uncertainty.

Informational social influence theory posits that under conditions of uncertainty, we are inclined to look to others for advice. This leaves us remarkably vulnerable to being influenced by others' opinions or advice. Rational agents, however, do not blindly seek and act on arbitrary information, but often consider the quality of its source before committing to a course of action. Here, we ask the question of whether a collaborator's reputation can increase their social influence and, in turn, bias perception and anxiety under changing levels of uncertainty. Human male and female participants were asked to provide estimations of dot direction using the random dot motion (RDM) perceptual discrimination task and were paired with transient collaborators of high or low reputation whom provided their own estimations. The RDM varied in degrees of uncertainty and joint performance accuracy was linked to risk of an electric shock. Despite providing identical information, we show that collaborating with a high reputation compared with a low reputation partner, led to significantly more conformity during the RDM task for uncertain perceptual decisions. Consequently, high reputation partners decreased the subjects' anxiety during the anticipatory shock periods. fMRI data showed that parametric changes in conformity resulted in increased activity in the ventromedial PFC, whereas dissent was associated with increased in activity in the dorsal anterior cingulate cortex (dACC). Furthermore, the dACC and insula, regions involved in anticipatory pain, were significantly more active when collaborating with a low reputation partner. These results suggest that information about reputation can influence both cognitive and affective processes and in turn alter the neural circuits that underlie decision-making and emotion.SIGNIFICANCE STATEMENT Humans look to others for advice when making decisions under uncertainty. Rational agents, however, do not blindly seek information, but often consider the quality of its source before committing to a course of action. Here, we ask the question of whether a collaborators' reputation can increase social influence and in turn bias perception and anxiety in the context of perceptual uncertainty. We show that when subjects are partnered with collaborators with a high reputation, this leads to increased conformity during uncertain perceptual decision-making and reduces anxiety when joint performance accuracy leads to an electric shock. Furthermore, our results show that information about reputation alters the neural circuits that underlie decision-making and emotion.

How the Brain Converts Negative Evaluation into Performance Facilitation.

Surpassing negative evaluation is a recurrent theme of success stories. Yet, there is little evidence supporting the counterintuitive idea that negative evaluation might not only motivate people, but also enhance performance. To address this question, we designed a task that required participants to decide whether taking up a risky challenge after receiving positive or negative evaluations from independent judges. Participants believed that these evaluations were based on their prior performance on a related task. Results showed that negative evaluation caused a facilitation in performance. Concurrent functional magnetic resonance imaging revealed that the motivating effect of negative evaluation was represented in the insula and striatum, while the performance boost was associated with functional positive connectivity between the insula and a set of brain regions involved in goal-directed behavior and the orienting of attention. These findings provide new insight into the neural representation of negative evaluation-induced facilitation.

Inferences of Others' Competence Reduces Anticipation of Pain When under Threat.

On a daily basis, we place our lives in the hands of strangers. From dentists to pilots, we make inferences about their competence to perform their jobs and consequently to keep us from harm. Here we explore whether the perceived competence of others can alter one's anticipation of pain. In two studies, participants (Receivers) believed their chances of experiencing an aversive stimulus were directly dependent on the performance of another person (Players). We predicted that perceiving the Players as highly competent would reduce Receivers' anxiety when anticipating the possibility of an electric shock. Results confirmed that high competence ratings consistently corresponded with lower reported anxiety, and complementary fMRI data showed that increased competence perception was further expressed as decreased activity in the bilateral posterior insula, a region localized to actual pain stimulation. These studies suggest that inferences of competence act as predictors of protection and reduce the expectation of negative outcomes.

Empathic concern drives costly altruism.

Why do we self-sacrifice to help others in distress? Two competing theories have emerged, one suggesting that prosocial behavior is primarily motivated by feelings of empathic other-oriented concern, the other that we help mainly because we are egoistically focused on reducing our own discomfort. Here we explore the relationship between costly altruism and these two sub-processes of empathy, specifically drawing on the caregiving model to test the theory that trait empathic concern (e.g. general tendency to have sympathy for another) and trait personal distress (e.g. predisposition to experiencing aversive arousal states) may differentially drive altruistic behavior. We find that trait empathic concern--and not trait personal distress--motivates costly altruism, and this relationship is supported by activity in the ventral tegmental area, caudate and subgenual anterior cingulate, key regions for promoting social attachment and caregiving. Together, this data helps identify the behavioral and neural mechanisms motivating costly altruism, while demonstrating that individual differences in empathic concern-related brain responses can predict real prosocial choice.

Training the emotional brain: improving affective control through emotional working memory training.

Affective cognitive control capacity (e.g., the ability to regulate emotions or manipulate emotional material in the service of task goals) is associated with professional and interpersonal success. Impoverished affective control, by contrast, characterizes many neuropsychiatric disorders. Insights from neuroscience indicate that affective cognitive control relies on the same frontoparietal neural circuitry as working memory (WM) tasks, which suggests that systematic WM training, performed in an emotional context, has the potential to augment affective control. Here we show, using behavioral and fMRI measures, that 20 d of training on a novel emotional WM protocol successfully enhanced the efficiency of this frontoparietal demand network. Critically, compared with placebo training, emotional WM training also accrued transfer benefits to a "gold standard" measure of affective cognitive control-emotion regulation. These emotion regulation gains were associated with greater activity in the targeted frontoparietal demand network along with other brain regions implicated in affective control, notably the subgenual anterior cingulate cortex. The results have important implications for the utility of WM training in clinical, prevention, and occupational settings.

Foraging under competition: the neural basis of input-matching in humans.

Input-matching is a key mechanism by which animals optimally distribute themselves across habitats to maximize net gains based on the changing input values of food supply rate and competition. To examine the neural systems that underlie this rule in humans, we created a continuous-input foraging task where subjects had to decide to stay or switch between two habitats presented on the left and right of the screen. The subject's decision to stay or switch was based on changing input values of reward-token supply rate and competition density. High density of competition or low-reward token rate was associated with decreased chance of winning. Therefore, subjects attempted to maximize their gains by switching to habitats that possessed low competition density and higher token rate. When it was increasingly disadvantageous to be in a habitat, we observed increased activity in brain regions that underlie preparatory motor actions, including the dorsal anterior cingulate cortex and the supplementary motor area, as well as the insula, which we speculate may be involved in the conscious urge to switch habitats. Conversely, being in an advantageous habitat is associated with activity in the reward systems, namely the striatum and medial prefrontal cortex. Moreover, amygdala and dorsal putamen activity steered interindividual preferences in competition avoidance and pursuing reward. Our results suggest that input-matching decisions are made as a net function of activity in a distributed set of neural systems. Furthermore, we speculate that switching behaviors are related to individual differences in competition avoidance and reward drive.

Overlapping and distinct representations of advantageous and disadvantageous inequality.

Advantageous inequality (AI) aversion, or paying at a personal cost to achieve equal reward distribution, represents a unique feature of human behavior. Here, we show that individuals have strong preferences for fairness in both disadvantageous (DI) and advantageous inequality (AI) situations, such that they alter others' payoff at a personal financial cost. At the neural level, we found that both types of inequality activated the putamen, orbitofrontal cortex, and insula, regions implicated in motivation. Individual difference analyses found that those who spent more money to increase others' payoff had stronger activity in putamen when they encountered AI and less functional connectivity between putamen and both orbitofrontal cortex and anterior insula. Conversely, those who spent more money to reduce others' payoff had stronger activity in amygdala in response to DI and less functional connectivity between amygdala and ventral anterior cingulate cortex. These dissociations suggest that both types of inequality are processed by similar brain areas, yet modulated by different neural pathways.

Three roots of online toxicity: disembodiment, accountability, and disinhibition.

Online communication is central to modern social life, yet it is often linked to toxic manifestations and reduced well-being. How and why online communication enables these toxic social effects remains unanswered. In this opinion, we propose three roots of online toxicity: disembodiment, limited accountability, and disinhibition. We suggest that virtual disembodiment results in a chain of psychological states primed for deleterious social interaction. Drawing from differences between face-to-face and online interactions, the framework highlights and addresses the fundamental problems that result in impaired communication between individuals and explicates its effects on social toxicity online.

Adaptive Safety Coding in the Prefrontal Cortex.

Pivotal to self-preservation is the ability to identify when we are safe and when we are in danger. Previous studies have focused on safety estimations based on the features of external threats and do not consider how the brain integrates other key factors, including estimates about our ability to protect ourselves. Here we examine the neural systems underlying the online dynamic encoding of safety. The current preregistered study used two novel tasks to test four facets of safety estimation: Safety Prediction, Meta-representation, Recognition, and Value Updating. We experimentally manipulated safety estimation changing both levels of external threats and self-protection. Data were collected in two independent samples (behavioral N=100; fMRI N=30). We found consistent evidence of subjective changes in the sensitivity to safety conferred through protection. Neural responses in the ventromedial prefrontal cortex (vmPFC) tracked increases in safety during all safety estimation facets, with specific tuning to protection. Further, informational connectivity analyses revealed distinct hubs of safety coding in the posterior and anterior vmPFC for external threats and protection, respectively. These findings reveal a central role of the vmPFC for coding safety.

Neural activity associated with monitoring the oscillating threat value of a tarantula.

Phylogenetic threats such as spiders evoke our deepest primitive fears. When close or looming, such threats engage evolutionarily conserved monitoring systems and defense reactions that promote self-preservation. With the use of a modified behavioral approach task within functional MRI, we show that, as a tarantula was placed closer to a subject's foot, increased experiences of fear coincided with augmented activity in a cascade of fear-related brain networks including the periaqueductal gray, amygdala, and bed nucleus of the stria terminalis. Activity in the amygdala was also associated with underprediction of the tarantula's threat value and, in addition to the bed nucleus of the stria terminalis, with monitoring the tarantula's threat value as indexed by its direction of movement. Conversely, the orbitofrontal cortex was engaged as the tarantula grew more distant, suggesting that this region emits safety signals or expels fear. Our findings fractionate the neurobiological mechanisms associated with basic fear and potentially illuminate the perturbed reactions that characterize clinical phobias.