Social conformity is due to biased stimulus processing: electrophysiological and diffusion analyses

Social influence and social identity: A diffusion model analysis

Building on the seminal studies of Solomon Asch and Muzafer Sherif, recent research has advanced our understanding of the mechanisms underlying social influence by applying a diffusion model analysis. Here, we combined the social identity approach to social influence with a diffusion model analysis to unravel the mechanisms underlying social influence. In particular, we aimed to disentangle whether the difference between in-group and out-group influence on perceptual decision-making is driven by a judgmental bias (i.e., changes in decision criteria) or a perceptual bias (i.e., changes in the uptake of sensory information). Preregistered analyses indicated that in-groups exerted stronger social influence than out-groups because in-groups induced a stronger perceptual bias than out-groups. This finding is in line with the single process assumption of the social identity approach because it implicates that the single process driving social influence (i.e., self-categorisation) translates into a change in a single subprocess of decision-making (i.e., biased information uptake). In conclusion, our results highlight that our theoretical understanding of social influence can be expanded by integrating the social identity approach with a diffusion model analysis.

Adopting the visual perspective of a group member is influenced by implicit group averaging

As social entities, individuals' perception and behaviors are susceptible to the influence of their social groups. Previous research has consistently shown that the group context in which individuals are situated significantly influences their perceptual processing. We aim to investigate whether the group context in which another individual is situated alters our understanding of their visual perception, which holds profound implications for interpersonal interactions. To address this inquiry, we conducted three experiments. In Experiment 1, participants were presented with a visual scene depicting multiple avatars seated around a table, all facing an arrow positioned at the center of the table. They were instructed to adopt the visual perspective of a specific avatar within the group to perceive the arrow's orientation, and then reproduce its orientation from their own perspectives. We found that participants exhibited a bias towards the group's average perspective when reproducing the arrow's orientation. Experiment 2 further demonstrated that reinforced group processing could elicit an earlier appearance of this bias. In Experiment 3, we investigated an alternative explanation positing that the aforementioned bias originated from visual ensemble perception rather than group influence by instructing participants to reproduce the target avatar's position relative to the arrow's orientation. If the bias indeed originated from ensemble perception, it should also manifest in this task. However, the absence of any reproduction bias refuted this possibility. Through these experiments, we demonstrate that our understanding of an individual's perceptual experiences is influenced by the social context in which they are situated, which manifests as a convergence phenomenon.

Kurvers RHJ. A Cognitive Computational Approach to Social and Collective Decision-Making

Collective dynamics play a key role in everyday decision-making. Whether social influence promotes the spread of accurate information and ultimately results in adaptive behavior or leads to false information cascades and maladaptive social contagion strongly depends on the cognitive mechanisms underlying social interactions. Here we argue that cognitive modeling, in tandem with experiments that allow collective dynamics to emerge, can mechanistically link cognitive processes at the individual and collective levels. We illustrate the strength of this cognitive computational approach with two highly successful cognitive models that have been applied to interactive group experiments: evidence-accumulation and reinforcement-learning models. We show how these approaches make it possible to simultaneously study (a) how individual cognition drives social systems, (b) how social systems drive individual cognition, and (c) the dynamic feedback processes between the two layers.

Verbal Aggressions Against Major League Baseball Umpires Affect Their Decision Making

Excessively criticizing a perceived unfair decision is considered to be common behavior among people seeking to restore fairness. However, the effectiveness of this strategy remains unclear. Using an ecological environment where excessive criticism is rampant-Major League Baseball-we assess the impact of verbal aggression on subsequent home-plate umpire decision making during the 2010 to 2019 seasons (N = 153,255 pitches). Results suggest a two-sided benefit of resorting to verbal abuse. After being excessively criticized, home-plate umpires (N = 110 adults, employed in the United States) were less likely to call strikes to batters from the complaining team and more prone to call strikes to batters on the opposing team. A series of additional analyses lead us to reject an alternative hypothesis, namely that umpires, after ejecting the aggressor, seek to compensate for the negative consequences brought on by the loss of a teammate. Rather, our findings support the hypothesis that, under certain conditions, verbal aggression may offer an advantage to complainants.

Earlier social information has a stronger influence on judgments

People's decisions are often informed by the choices of others. Evidence accumulation models provide a mechanistic account of how such social information enters the choice process. Previous research taking this approach has suggested two fundamentally different cognitive mechanisms by which people incorporate social information. On the one hand, individuals may update their evidence level instantaneously when observing social information. On the other hand, they may gradually integrate social information over time. These accounts make different predictions on how the timing of social information impacts its influence. The former predicts that timing has no impact on social information uptake. The latter predicts that social information which arrives earlier has a stronger impact because its impact increases over time. We tested both predictions in two studies in which participants first observed a perceptual stimulus. They then entered a deliberation phase in which social information arrived either early or late before reporting their judgment. In Experiment 1, early social information remained visible until the end and was thus displayed for longer than late social information. In Experiment 2, which was preregistered, early and late social information were displayed for an equal duration. In both studies, early social information had a larger impact on individuals' judgments. Further, an evidence accumulation analysis found that social information integration was best explained by both an immediate update of evidence and continuous integration over time. Because in social systems, timing plays a key role (e.g., propagation of information in social networks), our findings inform theories explaining the temporal evolution of social impact and the emergent social dynamics.

Situational social influence leading to non-compliance with conservation rules

It is well established that the decisions that we make can be strongly influenced by the behaviour of others. However, testing how social influence can lead to non-compliance with conservation rules during an individual's decision-making process has received little research attention. We synthesise advances in understanding of conformity and rule-breaking in individuals and in groups, and take a situational approach to studying the social dynamics and ensuing social identity changes that can lead to non-compliant decision-making. We focus on situational social influence contagion that are copresent (i.e., same space and same time) or trace-based (i.e., behavioural traces in the same space). We then suggest approaches for testing how situational social influence can lead to certain behaviours in non-compliance with conservation rules.

Social norms shape visual appearance: Taking a closer look at the link between social norm learning and perceptual decision-making

One of the most fundamental questions in social psychology is whether norms can change individuals' minds by shaping the visual appearance of stimuli. This question was first raised by Muzafer Sherif (1935). Drawing on the extended social reinforcement account (Germar and Mojzisch, 2019), we aimed to provide a rigorous test of the hypothesis that norm learning leads to a persistent perceptual bias and, hence, to a change in the visual appearance of stimuli. From a methodological perspective, we used both a diffusion model approach and the method of adjustment, a well-established technique from psychophysics and vision research. The results of Experiments 1-3 show that norm effects on perceptual decision-making are robustly replicable, and are due to genuine social influence, that is, they cannot be explained by non-social priming, contingency learning effects (Experiments 1 and 2) or anchoring effects (Experiment 3). Most importantly, by using a psychophysical approach, Experiment 4 shows, for the first time, that social norm learning alters individuals' point of subjective equality and, hence, the visual appearance of stimuli.

Neural correlates of evaluations of non-binary social feedback: An EEG study

PURPOSE

In complex and diverse social circumstances, decision making is affected by social feedback. Although previous studies have examined the electrophysiological correlates of social feedback with a binary valence, those related to non-binary feedback, or the magnitude of social feedback, remain unclear. This study investigated the electrophysiological correlates of non-binary social feedback and subsequent action selection processing.

METHODS

Participants were asked to complete a Gabor patch direction judgment task in which they were required to make judgments before and after receiving social feedback. They were informed that the feedback stimuli represented the degree to which other participants made the same choice.

RESULTS & CONCLUSION

The results revealed that feedback that was highly concordant with the participant's judgments elicited greater P300 activity, which was associated with the fulfillment of expectations regarding social reward. Moreover, moderately concordant feedback induced stronger theta band power, which may indicate monitoring of subjective conflict. Temporal changes in theta power during feedback phase may also relate to adjustments in prediction error. Additionally, when an initial judgment was maintained following social feedback, we observed a stronger increase in beta power, indicating an association with post-social-feedback action processing.

Social norm learning from non-human agents can induce a persistent perceptual bias: A diffusion model approach

Seminal studies on social influence (Asch, 1956; Sherif, 1935) were based on face-to-face interactions between humans. Nowadays, computer-mediated communication is steadily becoming ubiquitous, and we are increasingly influenced by non-human agents, such as algorithms, robots, and chatbots. The present research aimed to answer two important questions: Can non-human agents exert social influence in a persistent manner and, thus, contribute to the emergence of social norms? And if this is the case, is social influence exerted by non-human agents mediated by the same or by different cognitive mechanisms as social influence exerted by human agents? To answer these questions, we used an online version of an established paradigm in research on social norm learning. To examine the cognitive underpinnings of social influence, we used a diffusion model approach. Our results provide strong evidence for the notion that non-human agents can induce persistent social influence outside an immediate group context and, hence, can contribute to the emergence of social norms. Furthermore, results from our diffusion model analyses support the notion that social influence exerted by non-human agents is mainly mediated by the same cognitive mechanisms as social influence exerted by human agents.

Tradition–invention dichotomy and optimization in the field of science

The central idea of the bifocal stance theory (BST) by Jagiello et al. has substantial relevance to scientific research. Both tradition-following and exploration-innovation are important in science and researchers subconsciously try to optimize their strategies. We outline three important dimensions of this optimization and argue that attempts to understand this complex process can help us design better science education, research training, investigation, and science publication.

Characterization of the Core Determinants of Social Influence From a Computational and Cognitive Perspective

Most human decisions are made among social others, and in what social context the choices are made is known to influence individuals' decisions. Social influence has been noted as an important factor that may nudge individuals to take more risks (e.g., initiation of substance use), but ironically also help individuals to take safer actions (e.g., successful abstinence). Such bi-directional impacts of social influence hint at the complexity of social information processing. Here, we first review the recent computational approaches that shed light on neural and behavioral mechanisms underlying social influence following basic computations involved in decision-making: valuation, action selection, and learning. We next review the studies on social influence from various fields including neuroeconomics, developmental psychology, social psychology, and cognitive neuroscience, and highlight three dimensions of determinants-who are the recipients, how the social contexts are presented, and to what domains and processes of decisions the influence is applied-that modulate the extent to which individuals are influenced by others. Throughout the review, we also introduce the brain regions that were suggested as neural instantiations of social influence from a large body of functional neuroimaging studies. Finally, we outline the remaining questions to be addressed in the translational application of computational and cognitive theories of social influence to psychopathology and health.

Collective rule-breaking

Rules form an important part of our everyday lives. Here we explore the role of social influence in rule-breaking. In particular, we identify some of the cognitive mechanisms underlying rule-breaking and propose approaches for how they can be scaled up to the level of groups or crowds to better understand the emergence of collective rule-breaking. Social contagion plays an important role in such processes and different dynamics such as linear or rapid nonlinear spreading can have important consequences for interventions in rule-breaking. A closer integration of cognitive psychology, microsociology and mathematical modelling will be key to a deeper understanding of collective rule-breaking to turn this field of research into a predictive science.

The hierarchical sensitivity to social misalignment during decision-making under uncertainty

Social misalignment occurs when a person’s attitudes and opinions deviate from those of others. We investigated how individuals react to social misalignment in risky (outcome probabilities are known) or ambiguous (outcome probabilities are unknown) decision contexts. During each trial, participants played a forced-choice gamble, and they observed the decisions of four other players after they made a tentative decision, followed by an opportunity to keep or change their initial decision. Behavioral and event-related potential data were collected. Behaviorally, the stronger the participants’ initial preference, the less likely they were to switch their decisions, whereas the more their decisions were misaligned with the majority, the more likely they were to switch. Electrophysiological results showed a hierarchical processing pattern of social misalignment. Misalignment was first detected binarily (i.e. match/mismatch) at an early stage, as indexed by the N1 component. During the second stage, participants became sensitive to low levels of misalignment, which were indexed by the feedback-related negativity. The degree of social misalignment was processed in greater detail, as indexed by the P3 component. Moreover, such hierarchical neural sensitivity is generalizable across different decision contexts (i.e. risky and ambiguous). These findings demonstrate a fine-grained neural sensitivity to social misalignment during decision-making under uncertainty.

Developmental trajectory of social influence integration into perceptual decisions in children

The opinions of others have a profound influence on decision making in adults. The impact of social influence appears to change during childhood, but the underlying mechanisms and their development remain unclear. We tested 125 neurotypical children between the ages of 6 and 14 years on a perceptual decision task about 3D-motion figures under informational social influence. In these children, a systematic bias in favor of the response of another person emerged at around 12 years of age, regardless of whether the other person was an age-matched peer or an adult. Drift diffusion modeling indicated that this social influence effect in neurotypical children was due to changes in the integration of sensory information, rather than solely a change in decision behavior. When we tested a smaller cohort of 30 age- and IQ-matched autistic children on the same task, we found some early decision bias to social influence, but no evidence for the development of systematic integration of social influence into sensory processing for any age group. Our results suggest that by the early teens, typical neurodevelopment allows social influence to systematically bias perceptual processes in a visual task previously linked to the dorsal visual stream. That the same bias did not appear to emerge in autistic adolescents in this study may explain some of their difficulties in social interactions.

Norm compliance affects perceptual decisions through modulation of a starting point bias

Adaptive decisions in social contexts depend on both perceptual information and social expectations or norms. These are potentially in conflict when certain choices are beneficial for an individual, but societal rules mandate a different course of action. To resolve such a conflict, the reliability of information has to be balanced against potentially deleterious effects of non-compliance such as ostracism. In this study, we systematically investigated how interactions between perceptual and social influences affect decision-relevant cognitive processes. In a direction-of-motion discrimination task, participants received perceptual information alongside information on other players' choices. In addition, we created conflict scenarios where players' choices affected other participants' monetary rewards dependent on whether their choices were in line or against the opinion of the other players. Importantly, we altered the strength of this manipulation in two separate experiments by contrasting motivations of either preventing harm or providing a benefit to others. Behavioural analyses and computational models of perceptual decisions showed that participants successfully integrated perceptual with social information. Participants' reliance on social information was effectively modulated in conflict situations. Critically, these effects were augmented when the strength of social norms was increased, indexing conditions under which social norms effectively influence decisions. These results inform theories of social influence by providing an account of how higher order goals like social norm compliance affect perceptual decisions.

Experimental validation of the diffusion model based on a slow response time paradigm

The diffusion model (Ratcliff, Psychol Rev 85(2):59-108, 1978) is a stochastic model that is applied to response time (RT) data from binary decision tasks. The model is often used to disentangle different cognitive processes. The validity of the diffusion model parameters has, however, rarely been examined. Only few experimental paradigms have been analyzed with those being restricted to fast response time paradigms. This is attributable to a recommendation stated repeatedly in the diffusion model literature to restrict applications to fast RT paradigms (more specifically, to tasks with mean RTs below 1.5 s per trial). We conducted experimental validation studies in which we challenged the necessity of this restriction. We used a binary task that features RTs of several seconds per trial and experimentally examined the convergent and discriminant validity of the four main diffusion model parameters. More precisely, in three experiments, we selectively manipulated these parameters, using a difficulty manipulation (drift rate), speed-accuracy instructions (threshold separation), a more complex motoric task (non-decision time), and an asymmetric payoff matrix (starting point). The results were similar to the findings from experimental validation studies based on fast RT paradigms. Thus, our experiments support the validity of the parameters of the diffusion model and speak in favor of an extension of the model to paradigms based on slower RTs.

How Do You See Me? The Neural Basis of Motivated Meta-perception

We cannot see the minds of others, yet people often spontaneously interpret how they are viewed by other people (i.e., meta-perceptions) and often in a self-flattering manner. Very little is known about the neural associations of meta-perceptions, but a likely candidate is the ventromedial pFC (VMPFC). VMPFC has been associated with both self- and other-perception as well as motivated self-perception. Does this function extend to meta-perceptions? The current study examined neural activity while participants made meta-perceptive interpretations in various social scenarios. A drift-diffusion model was used to test whether the VMPFC is associated with two processes involved in interpreting meta-perceptions in a self-flattering manner: the extent to which the interpretation process involves the preferential accumulation of evidence in favor of a self-flattering interpretation versus the extent to which the interpretation process begins with an expectation that favors a self-flattering outcome. Increased VMPFC activity was associated with the extent to which people preferentially accumulate information when interpreting meta-perceptions under ambiguous conditions and marginally associated with self-flattering meta-perceptions. Together, the present findings illuminate the neural underpinnings of a social cognitive process that has received little attention to date: how we make meaning of others' minds when we think those minds are pointed at us.

Motivated malleability: Frontal cortical asymmetry predicts the susceptibility to social influence

Humans, just as many other animals, regulate their behavior in terms of approaching stimuli associated with pleasure and avoiding stimuli linked to harm. A person's current and chronic motivational direction - that is, approach versus avoidance orientation - is reliably reflected in the asymmetry of frontal cortical low-frequency oscillations. Using resting electroencephalography (EEG), we show that frontal asymmetry is predictive of the tendency to yield to social influence: Stronger right- than left-side frontolateral activation during a resting-state session prior to the experiment was robustly associated with a stronger inclination to adopt a peer group's judgments during perceptual decision-making (Study 1). We posit that this reflects the role of a person's chronic avoidance orientation in socially adjusted behavior. This claim was strongly supported by additional survey investigations (Studies 2a, 2b, 2c), all of which consistently revealed that trait avoidance was positively linked to the susceptibility to social influence. The present contribution thus stresses the relevance of chronic avoidance orientation in social conformity, refining (yet not contradicting) the longstanding view that socially influenced behavior is motivated by approach-related goals. Moreover, our findings valuably underscore and extend our knowledge on the association between frontal cortical asymmetry and a variety of psychological variables.