The expression of decision and learning variables in movement patterns related to decision actions.

Decisions are not necessarily easy to separate into a planning and an execution phase and the decision-making process can often be reflected in the movement associated with the decision. Here, we used formalized definitions of concepts relevant in decision-making and learning to explore if and how these concepts correlate with decision-related movement paths, both during and after a choice is made. To this end, we let 120 participants (46 males, mean age = 24.5 years) undergo a repeated probabilistic two-choice task with changing probabilities where we used mouse-tracking, a simple non-invasive technique, to study the movements related to decisions. The decisions of the participants were modelled using Bayesian inference which enabled the computation of variables related to decision-making and learning. Analyses of the movement during the decision showed effects of relevant decision variables, such as confidence, on aspects related to, for instance, timing and pausing, range of movement and deviation from the shortest distance. For the movements after a decision there were some effects of relevant learning variables, mainly related to timing and speed. We believe our findings can be of interest for researchers within several fields, spanning from social learning to experimental methods and human-machine/robot interaction.

Social learning and the adaptiveness of expressing and perceiving fearfulness.

The fearful ape hypothesis revolves around our ability to express and perceive fearfulness. Here, we address these abilities from a social learning perspective which casts fearfulness in a slightly different light. Our commentary argues that any theory that characterizes a (human) social signal as being adaptive, needs to address the role of social learning as an alternative candidate explanation.

Anxious behaviour in a demonstrator affects observational learning.

Humans can acquire fear through the observation of others' (learning models') threat responses. These responses can be direct responses to aversive stimuli, or anticipatory responses to threats. Most research focuses on learning from observation of direct responses only. Here, we investigated how observational fear conditioning is influenced by a learning model's typically anxious anticipatory responses. High anxiety individuals often display typically anxious anticipatory behaviour, such as worsened discrimination between safe and unsafe stimuli, characterized by increased threat responses to safe stimuli. We hypothesized that observation of an anxiously behaving model would worsen discriminatory learning. To this end, we developed an observational conditioning paradigm where a learning model was exposed to one safe and one unsafe stimuli. The learning model displayed anticipatory aversion to either to the unsafe stimulus only (Non-Anxious Model group) or to both the safe and unsafe stimuli (Anxious Model group) in addition to reacting directly to an aversive stimulus paired with the unsafe stimulus. Contrary to expectations, discriminatory learning was not worsened in the Anxious Model group compared to the Non-Anxious Model group. Rather, we saw more robust discriminatory learning in the Anxious Model group. The study provides a first step towards understanding the effect of other's anticipatory responses in general and typically anxious anticipatory responses in particular, on observational fear learning.

The role of a "common is moral" heuristic in the stability and change of moral norms.

Moral norms are fundamental for virtually all social interactions, including cooperation. Moral norms develop and change, but the mechanisms underlying when, and how, such changes occur are not well-described by theories of moral psychology. We tested, and confirmed, the hypothesis that the commonness of an observed behavior consistently influences its moral status, which we refer to as the common is moral (CIM) heuristic. In 9 experiments, we used an experimental model of dynamic social interaction that manipulated the commonness of altruistic and selfish behaviors to examine the change of peoples' moral judgments. We found that both altruistic and selfish behaviors were judged as more moral, and less deserving of punishment, when common than when rare, which could be explained by a classical formal model (social impact theory) of behavioral conformity. Furthermore, judgments of common versus rare behaviors were faster, indicating that they were computationally more efficient. Finally, we used agent-based computer simulations to investigate the endogenous population dynamics predicted to emerge if individuals use the CIM heuristic, and found that the CIM heuristic is sufficient for producing 2 hallmarks of real moral norms; stability and sudden changes. Our results demonstrate that commonness shapes our moral psychology through mechanisms similar to behavioral conformity with wide implications for understanding the stability and change of moral norms. (PsycINFO Database Record

Beliefs about Others' Abilities Alter Learning from Observation.

Learning what is dangerous by observing others can be safer and more efficient than individual learning. The efficiency of observational learning depends on how observational information is used, something we propose depends on our beliefs' about others. Here, we investigated how described and actual abilities of another individual (a demonstrator) influenced performance and psychophysiology during learning of an observational avoidance task. Participants were divided into two groups. In each group there were two demonstrators who were described as either high (Described-High group) or low (Described-Low group) in their ability to learn the task. In both groups, one demonstrator had a high ability (Actual-High) and the other had a low ability (Actual-Low) to learn. Participants performed worse in the Described-Low compared to the Described-High group. Pupil dilation, and behavioral data in combination with reinforcement learning modeling, suggested that the described ability influenced performance by affecting the level of attention towards the observational information. Skin conductance responses and pupil dilation provided us with a separate measure of learning in addition to choice behavior.

Assessment of social transmission of threats in humans using observational fear conditioning.

Across the human life span, fear is often acquired indirectly by observation of the emotional expressions of others. The observational fear conditioning protocol was previously developed as a laboratory model for investigating socially acquired threat responses. This protocol serves as a suitable alternative to the widely used Pavlovian fear conditioning, in which threat responses are acquired through direct experiences. In the observational fear conditioning protocol, the participant (observer) watches a demonstrator being presented with a conditioned stimulus (CS) paired with an aversive unconditioned stimulus (US). The expression of threat learning is measured as the conditioned response (CR) expressed by the observer in the absence of the demonstrator. CRs are commonly measured as skin conductance responses, but behavioral and neural measures have also been implemented. The experimental procedure is suitable for divergent populations, can be administered by a graduate student and takes ∼40 min. Similar protocols are used in animals, emphasizing its value as a translational tool for studying socioemotional learning.

Co-Evolution of Social Learning and Evolutionary Preparedness in Dangerous Environments.

Danger is a fundamental aspect of the lives of most animals. Adaptive behavior therefore requires avoiding actions, objects, and environments associated with danger. Previous research has shown that humans and non-human animals can avoid such dangers through two types of behavioral adaptions, (i) genetic preparedness to avoid certain stimuli or actions, and (ii) social learning. These adaptive mechanisms reduce the fitness costs associated with danger but still allow flexible behavior. Despite the empirical prevalence and importance of both these mechanisms, it is unclear when they evolve and how they interact. We used evolutionary agent-based simulations, incorporating empirically based learning mechanisms, to clarify if preparedness and social learning typically both evolve in dangerous environments, and if these mechanisms generally interact synergistically or antagonistically. Our simulations showed that preparedness and social learning often co-evolve because they provide complimentary benefits: genetic preparedness reduced foraging efficiency, but resulted in a higher rate of survival in dangerous environments, while social learning generally came to dominate the population, especially when the environment was stochastic. However, even in this case, genetic preparedness reliably evolved. Broadly, our results indicate that the relationship between preparedness and social learning is important as it can result in trade-offs between behavioral flexibility and safety, which can lead to seemingly suboptimal behavior if the evolutionary environment of the organism is not taken into account.

Neural signals of vicarious extinction learning.

Social transmission of both threat and safety is ubiquitous, but little is known about the neural circuitry underlying vicarious safety learning. This is surprising given that these processes are critical to flexibly adapt to a changeable environment. To address how the expression of previously learned fears can be modified by the transmission of social information, two conditioned stimuli (CS + s) were paired with shock and the third was not. During extinction, we held constant the amount of direct, non-reinforced, exposure to the CSs (i.e. direct extinction), and critically varied whether another individual-acting as a demonstrator-experienced safety (CS + vic safety) or aversive reinforcement (CS + vic reinf). During extinction, ventromedial prefrontal cortex (vmPFC) responses to the CS + vic reinf increased but decreased to the CS + vic safety This pattern of vmPFC activity was reversed during a subsequent fear reinstatement test, suggesting a temporal shift in the involvement of the vmPFC. Moreover, only the CS + vic reinf association recovered. Our data suggest that vicarious extinction prevents the return of conditioned fear responses, and that this efficacy is reflected by diminished vmPFC involvement during extinction learning. The present findings may have important implications for understanding how social information influences the persistence of fear memories in individuals suffering from emotional disorders.

Spontaneous eye movements and trait empathy predict vicarious learning of fear.

Learning to predict dangerous outcomes is important to survival. In humans, this kind of learning is often transmitted through the observation of others' emotional responses. We analyzed eye movements during an observational/vicarious fear learning procedure, in which healthy participants (N=33) watched another individual ('learning model') receiving aversive treatment (shocks) paired with a predictive conditioned stimulus (CS+), but not a control stimulus (CS-). Participants' gaze pattern towards the model differentiated as a function of whether the CS was predictive or not of a shock to the model. Consistent with our hypothesis that the face of a conspecific in distress can act as an unconditioned stimulus (US), we found that the total fixation time at a learning model's face increased when the CS+ was shown. Furthermore, we found that the total fixation time at the CS+ during learning predicted participants' conditioned responses (CRs) at a later test in the absence of the model. We also demonstrated that trait empathy was associated with stronger CRs, and that autistic traits were positively related to autonomic reactions to watching the model receiving the aversive treatment. Our results have implications for both healthy and dysfunctional socio-emotional learning.

Demonstrator skill modulates observational aversive learning.

Learning to avoid danger by observing others can be relatively safe, because it does not incur the potential costs of individual trial and error. However, information gained through social observation might be less reliable than information gained through individual experiences, underscoring the need to apply observational learning critically. In order for observational learning to be adaptive it should be modulated by the skill of the observed person, the demonstrator. To address this issue, we used a probabilistic two-choice task where participants learned to minimize the number of electric shocks through individual learning and by observing a demonstrator performing the same task. By manipulating the demonstrator's skill we varied how useful the observable information was; the demonstrator either learned the task quickly or did not learn it at all (random choices). To investigate the modulatory effect in detail, the task was performed under three conditions of available observable information; no observable information, observation of choices only, and observation of both the choices and their consequences. As predicted, our results showed that observable information can improve performance compared to individual learning, both when the demonstrator is skilled and unskilled; observation of consequences improved performance for both groups while observation of choices only improved performance for the group observing the skilled demonstrator. Reinforcement learning modeling showed that demonstrator skill modulated observational learning from the demonstrator's choices, but not their consequences, by increasing the degree of imitation over time for the group that observed a fast learner. Our results show that humans can adaptively modulate observational learning in response to the usefulness of observable information.

Racial bias shapes social reinforcement learning.

Both emotional facial expressions and markers of racial-group belonging are ubiquitous signals in social interaction, but little is known about how these signals together affect future behavior through learning. To address this issue, we investigated how emotional (threatening or friendly) in-group and out-group faces reinforced behavior in a reinforcement-learning task. We asked whether reinforcement learning would be modulated by intergroup attitudes (i.e., racial bias). The results showed that individual differences in racial bias critically modulated reinforcement learning. As predicted, racial bias was associated with more efficiently learned avoidance of threatening out-group individuals. We used computational modeling analysis to quantitatively delimit the underlying processes affected by social reinforcement. These analyses showed that racial bias modulates the rate at which exposure to threatening out-group individuals is transformed into future avoidance behavior. In concert, these results shed new light on the learning processes underlying social interaction with racial-in-group and out-group individuals.

Other people as means to a safe end: vicarious extinction blocks the return of learned fear.

Information about what is dangerous and safe in the environment is often transferred from other individuals through social forms of learning, such as observation. Past research has focused on the observational, or vicarious, acquisition of fears, but little is known about how social information can promote safety learning. To address this issue, we studied the effects of vicarious-extinction learning on the recovery of conditioned fear. Compared with a standard extinction procedure, vicarious extinction promoted better extinction and effectively blocked the return of previously learned fear. We confirmed that these effects could not be attributed to the presence of a learning model per se but were specifically driven by the model's experience of safety. Our results confirm that vicarious and direct emotional learning share important characteristics but that social-safety information promotes superior down-regulation of learned fear. These findings have implications for emotional learning, social-affective processes, and clinical practice.