Increased complexity of social category markers leads to diverse rule-based categorizations and reduced intergroup bias.

Social categories are key to human social life, often leading to intergroup bias and stereotypes. While traditional studies use binary social markers, real-world markers are more complex. This study explored whether such complexity results in complex social categories or less cognitively demanding binary rules.

Computational markers show specific deficits for dyslexia and ADHD in complex learning settings.

The current study examined how individuals with neurodevelopmental disorders navigate the complexities of learning within multidimensional environments marked by uncertain dimension values and without explicit guidance. Participants engaged in a game-like complex reinforcement learning task in which the stimuli dimension determining reward remained undisclosed, necessitating that participants discover which dimension should be prioritized for detecting the maximum reward. For comparison, a control condition featuring a simple reinforcement learning task was included in which the predictive dimension was explicitly revealed.

Experience and advice consequences shape information sharing strategies.

Individuals often rely on the advice of more experienced peers to minimise uncertainty and increase success likelihood. In most domains where knowledge is acquired through experience, advisers are themselves continuously learning. Here we examine the way advising behaviour changes throughout the learning process, and the way individual traits and costs and benefits of giving advice shape this behaviour.

Adaptive empathic response selection is sensitive to multiple dimensions of social interaction.

During empathic response selection, individuals draw from both past experiences and social cues, including the distressed person's identity, their emotional state, and the cause of distress. To study how these social dimensions influence empathic-response learning we integrated a multidimensional learning paradigm, computational modelling, and adaptive empathy framework. Participants identified effective empathic responses across two blocks of distress scenarios, with one social dimension altered between blocks.

Beyond the matrix: Experimental approaches to studying cognitive agents in social-ecological systems.

Studying social-ecological systems, in which agents interact with each other and their environment are important both for sustainability applications and for understanding how human cognition functions in context. In such systems, the environment shapes the agents' experience and actions, and in turn collective action of agents changes social and physical aspects of the environment. Here we review current investigation approaches, which rely on a lean design, with discrete actions and outcomes and little scope for varying environmental parameters and cognitive demands.

A cognitive approach to learning, monitoring, and shifting social norms.

Social norms govern and prescribe how group members behave. Since norms manifest in individuals' behavior, it is important to consider the cognitive demands associated with detecting and monitoring norm behaviors. Here I describe three types of norms that differ in the behavior they prescribe, the cognitive processes of behavior detection and monitoring they require, and the compliance and cooperative patterns they entail.

Asymmetric cognitive learning mechanisms underlying the persistence of intergroup bias.

Intergroup bias, the tendency to favor ingroups and be hostile towards outgroups, underlies many societal problems and persists even when intergroup members interact and share experiences. Here we study the way cognitive learning processes contribute to the persistence of intergroup bias. Participants played a game with ingroup and outgroup bot-players that entailed collecting stars and could sacrifice a move to zap another player.

Changing attachment orientation: Uncovering the role of shifting the emotion regulation tendency.

Changes in the individual's attachment orientation toward greater security are considered an important clinical goal. One promising underlying process of change in attachment orientation is shifting the emotion regulation tendency, in which the individual progresses from overreliance on the self or on the other to regulate emotional arousal. The present study utilized a computational approach to study shifts in the emotion regulation tendency as these manifest in the patient's and therapist's vocally encoded emotional arousal.

Comparing experience- and description-based economic preferences across 11 countries.

Recent evidence indicates that reward value encoding in humans is highly context dependent, leading to suboptimal decisions in some cases, but whether this computational constraint on valuation is a shared feature of human cognition remains unknown. Here we studied the behaviour of n = 561 individuals from 11 countries of markedly different socioeconomic and cultural makeup. Our findings show that context sensitivity was present in all 11 countries.

Disentangling the contribution of individual and social learning processes in human advice-taking behavior.

The study of social learning examines how individuals learn from others by means of observation, imitation, or compliance with advice. However, it still remains largely unknown whether social learning processes have a distinct contribution to behavior, independent from non-social trial-and-error learning that often occurs simultaneously. 153 participants completed a reinforcement learning task, where they were asked to make choices to gain rewards.

The spread of affective and semantic valence representations across states.

In many decision problems, outcomes are not reached after a single action but rather after a series of events or states. To optimize decisions over multiple states, representations of how good or bad the outcomes are, that is, the outcomes' valence, should spread across states. One mechanism for valence spreading is a temporal, state-independent process in which a single valence representation is updated when an outcome is experienced and fades away afterwards.

Moral judgement and decision-making: theoretical predictions and null results.

The study of moral judgement and decision making examines the way predictions made by moral and ethical theories fare in real world settings. Such investigations are carried out using a variety of approaches and methods, such as experiments, modeling, and observational and field studies, in a variety of populations. The current Collection on moral judgments and decision making includes works that represent this variety, while focusing on some common themes, including group morality and the role of affect in moral judgment.

Distinct reinforcement learning profiles distinguish between language and attentional neurodevelopmental disorders.

Background: Theoretical models posit abnormalities in cortico-striatal pathways in two of the most common neurodevelopmental disorders (Developmental dyslexia, DD, and Attention deficit hyperactive disorder, ADHD), but it is still unclear what distinct cortico-striatal dysfunction might distinguish language disorders from others that exhibit very different symptomatology. Although impairments in tasks that depend on the cortico-striatal network, including reinforcement learning (RL), have been implicated in both disorders, there has been little attempt to dissociate between different types of RL or to compare learning processes in these two types of disorders. The present study builds upon prior research indicating the existence of two learning manifestations of RL and evaluates whether these processes can be differentiated in language and attention deficit disorders.

Temporal dynamics of the semantic versus affective representations of valence during reversal learning.

Valence, the representation of a stimulus in terms of good or bad, plays a central role in models of affect, value-based learning theories, and value-based decision-making models. Previous work used Unconditioned Stimulus (US) to support a theoretical division between two different types of valence representations for a stimulus: the semantic representation of valence, i.e.

Outcome context-dependence is not WEIRD: Comparing reinforcement- and description-based economic preferences worldwide.

Recent evidence indicates that reward value encoding in humans is highly context-dependent, leading to suboptimal decisions in some cases. But whether this computational constraint on valuation is a shared feature of human cognition remains unknown. To address this question, we studied the behavior of individuals from across 11 countries of markedly different socioeconomic and cultural makeup using an experimental approach that reliably captures context effects in reinforcement learning.

Resting-state heart rate variability (HRV) mediates the association between perceived chronic stress and ambiguity avoidance.

Chronic stress is associated with profound behavioral and physiological alterations, including intolerance to uncertainty and reduced resting-state heart-rate-variability (HRV). Critically, uncertainty may arise in situations with known probabilities (risk) or unknown probabilities (ambiguity). Whether associations between chronic stress and decision-making under uncertainty are dependent on the specific type of uncertain decisions, and whether physiological alterations play a role in these putative associations is not yet clear.

Using clustering algorithms to examine the association between working memory training trajectories and therapeutic outcomes among psychiatric and healthy populations.

Working memory (WM) training has gained interest due to its potential to enhance cognitive functioning and reduce symptoms of mental disorders. Nevertheless, inconsistent results suggest that individual differences may have an impact on training efficacy. This study examined whether individual differences in training performance can predict therapeutic outcomes of WM training, measured as changes in anxiety and depression symptoms in sub-clinical and healthy populations.

Cost-benefit considerations have limited effect on the decision to exert cognitive effort in real-world computer-programming tasks.

Recent research shows that people usually try to avoid exerting cognitive effort yet they are willing to exert effort to gain rewards. This cost-benefit framework provides predictions for behaviour outside the laboratory. Nevertheless, the extent to which such considerations affect real-life decisions is not clear.

Blend in or stand out: social anxiety levels shape information-sharing strategies.

Although living in social groups provides many benefits for group members, such groups also serve as a setting for social competition over rank and influence. Evolutionary accounts suggest that social anxiety plays a role in regulating in-group conflict, as individuals who are concerned about social threat may choose to defer to others to maintain the hierarchical status quo. Here, we examine how social anxiety levels are related to the advice-giving style an individual adopts: a competitive influence-seeking strategy or a defensive blend-in strategy.

The devil is in the task structure.

Conflicting evidence about how the brain processes social and individual learning stems from which type of information is presented as the primary source of knowledge during experiments.

Using deep learning to predict human decisions and using cognitive models to explain deep learning models.

Deep neural networks (DNNs) models have the potential to provide new insights in the study of cognitive processes, such as human decision making, due to their high capacity and data-driven design. While these models may be able to go beyond theory-driven models in predicting human behaviour, their opaque nature limits their ability to explain how an operation is carried out, undermining their usefulness as a scientific tool. Here we suggest the use of a DNN model as an exploratory tool to identify predictable and consistent human behaviour, and using explicit, theory-driven models, to characterise the high-capacity model.

To shoot or not to shoot: experiments on moral injury in the context of West Bank checkpoints and COVID-19 restrictions enforcement.

Background: Does exposure to events that transgress accepted norms, such as killing innocent civilians, prompt the psychological and emotional consequences of moral injury among soldiers? Moral injury is associated with negative emotions such as guilt, shame and anger, and a sense of betrayal and is identified among veterans following exposure to potentially morally injurious events (PMIE).

Objective: We experimentally investigate how PMIE characteristics affect the intensity of MI and related negative moral emotions in participants with varied military experience.

Method: We conducted three controlled, randomized experiments.

Adaptive Empathy: A Model for Learning Empathic Responses in Response to Feedback.

Empathy is usually deployed in social interactions. Nevertheless, common measures and examinations of empathy study this construct in isolation from the person in distress. In this article we seek to extend the field of examination to include both empathizer and target to determine whether and how empathic responses are affected by feedback and learned through interaction.

Strategic disinformation outperforms honesty in competition for social influence.

Competition for social influence is a major force shaping societies, from baboons guiding their troop in different directions, to politicians competing for voters, to influencers competing for attention on social media. Social influence is invariably a competitive exercise with multiple influencers competing for it. We study which strategy maximizes social influence under competition.