Societal background influences social learning in cooperative decision making

Humans owe their ecological success to their great capacities for social learning and cooperation: learning from others helps individuals adjust to their environment and can promote cooperation in groups. Classic and recent studies indicate that the cultural organization of societies shapes the influence of social information on decision making and suggest that collectivist values (prioritizing the group relative to the individual) increase tendencies to conform to the majority. However, it is unknown whether and how societal background impacts social learning in cooperative interactions. Here we show that social learning in cooperative decision making systematically varies across two societies. We experimentally compare people's basic propensities for social learning in samples from a collectivist (China) and an individualist society (United Kingdom; total n?=?540) in a social dilemma and a coordination game. We demonstrate that Chinese participants base their cooperation decisions on information about their peers much more frequently than their British counterparts. Moreover, our results reveal remarkable societal differences in the type of peer information people consider. In contrast to the consensus view, Chinese participants tend to be substantially less majority-oriented than the British. While Chinese participants are inclined to adopt peer behavior that leads to higher payoffs, British participants tend to cooperate only if sufficiently many peers do so too. These results indicate that the basic processes underlying social transmission are not universal; rather, they vary with cultural conditions. As success-based learning is associated with selfish behavior and majority-based learning can help foster cooperation, our study suggests that in different societies social learning can play diverging roles in the emergence and maintenance of cooperation.     

Processing of social and monetary rewards in the human striatum

Despite an increasing focus on the neural basis of human decision making in neuroscience, relatively little attention has been paid to decision making in social settings. Moreover, although human social decision making has been explored in a social psychology context, few neural explanations for the observed findings have been considered. To bridge this gap and improve models of human social decision making, we investigated whether acquiring a good reputation, which is an important incentive in human social behaviors, activates the same reward circuitry as monetary rewards. In total, 19 subjects participated in functional magnetic resonance imaging (fMRI) experiments involving monetary and social rewards. The acquisition of one's good reputation robustly activated reward-related brain areas, notably the striatum, and these overlapped with the areas activated by monetary rewards. Our findings support the idea of a "common neural currency" for rewards and represent an important first step toward a neural explanation for complex human social behaviors.     

How does Behavior Change the Brain? Multiple Methods to Answer Old Questions

Clearly the brain controls behavior but can behavior also "control" the brain? On an evolutionary time scale, selective ecological pressures shape the sensory and motor capacities as well as the body and behavior. Correspondingly, in development, behavior acts in concert with the environment to cause structural changes in the brain lasting a lifetime. Surprisingly, in "real time" social behavior can also cause changes, typically reversible, in the brain in adult animals. Changes caused by behavioral interactions can be dramatic, and in many instances, these interactions are directly related to reproductive behavior. Understanding how behavior sculpts the brain in the course of behavioral interactions is a major challenge. Analyzing such changes requires a model system allowing control of the biological and behavioral environment of many animals simultaneously yet allowing access to physiological, cellular and molecular processes being regulated. The mouthbrooding cichlid Haplochromis (Astatotilapia) burtoni (Günther) from Lake Tanganyika lends itself to the study of social influences on the brain. It has complex, though easily observable individual and social behaviors regulated by two distinct classes of males, those with territories and those without. Many features of the animals are shaped by social encounters including the maturation of juveniles, the hypothalamic-pituitary-gonadal axis, the growth rate, the basal stress level among others. How does social information effect change in the brain and body? Animals must attend to the social scene to identify their chances. Learning how social information is transduced into cellular changes in this species should help understand how this happens in other social animals.     

Monkeys pay per view: adaptive valuation of social images by rhesus macaques

Individuals value information that improves decision making. When social interactions complicate the decision process, acquiring information about others should be particularly valuable. In primate societies, kinship, dominance, and reproductive status regulate social interactions and should therefore systematically influence the value of social information, but this has never been demonstrated. Here, we show that monkeys differentially value the opportunity to acquire visual information about particular classes of social images. Male rhesus macaques sacrificed fluid for the opportunity to view female perinea and the faces of high-status monkeys but required fluid overpayment to view the faces of low-status monkeys. Social value was highly consistent across subjects, independent of particular images displayed, and only partially predictive of how long subjects chose to view each image. These data demonstrate that visual orienting decisions reflect the specific social content of visual information and provide the first experimental evidence that monkeys spontaneously discriminate images of others based on social status.     

Neural basis of quasi-rational decision making

Standard economic theories conceive homo economicus as a rational decision maker capable of maximizing utility. In reality, however, people tend to approximate optimal decision-making strategies through a collection of heuristic routines. Some of these routines are driven by emotional processes, and others are adjusted iteratively through experience. In addition, routines specialized for social decision making, such as inference about the mental states of other decision makers, might share their origins and neural mechanisms with the ability to simulate or imagine outcomes expected from alternative actions that an individual can take. A recent surge of collaborations across economics, psychology and neuroscience has provided new insights into how such multiple elements of decision making interact in the brain.     

Integration of sensory and motor processing underlying social behaviour in túngara frogs

Social decision making involves the perception and processing of social stimuli, the subsequent evaluation of that information in the context of the individual's internal and external milieus to produce a decision, and then culminates in behavioural output informed by that decision. We examined brain networks in an anuran communication system that relies on acoustic signals to guide simple, stereotyped motor output. We used egr-1 mRNA expression to measure neural activation in male túngara frogs, Physalaemus pustulosus, following exposure to conspecific and heterospecific calls that evoke competitive or aggressive behaviour. We found that acoustically driven activation in auditory brainstem nuclei is transformed into activation related to sensory-motor interactions in the diencephalon, followed by motor-related activation in the telencephalon. Furthermore, under baseline conditions, brain nuclei typically have correlated egr-1 mRNA levels within brain divisions. Hearing conspecific advertisement calls increases correlations between anatomically distant brain divisions; no such effect was observed in response to calls that elicit aggressive behaviour. Neural correlates of social decision making thus take multiple forms: (i) a progressive shift from sensory to motor encoding from lower to higher stages of neural processing and (ii) the emergence of correlated activation patterns among sensory and motor regions in response to behaviourally relevant social cues.     

The role of social cognition in decision making

Successful decision making in a social setting depends on our ability to understand the intentions, emotions and beliefs of others. The mirror system allows us to understand other people's motor actions and action intentions. 'Empathy' allows us to understand and share emotions and sensations with others. 'Theory of mind' allows us to understand more abstract concepts such as beliefs or wishes in others. In all these cases, evidence has accumulated that we use the specific neural networks engaged in processing mental states in ourselves to understand the same mental states in others. However, the magnitude of the brain activity in these shared networks is modulated by contextual appraisal of the situation or the other person. An important feature of decision making in a social setting concerns the interaction of reason and emotion. We consider four domains where such interactions occur: our sense of fairness, altruistic punishment, trust and framing effects. In these cases, social motivations and emotions compete with each other, while higher-level control processes modulate the interactions of these low-level biases.     

The neurobiology of social decision-making

Humans live in highly complex social environments and some of our most important decisions are made in the context of social interactions. Research that probes the neural basis of decision-making in the context of social interactions combines behavioral paradigms from game theory with a variety of methods from neuroscience. The neural correlates of decision making in reciprocal exchange and bargaining games have been probed with functional neuroimaging, transcranial magnetic stimulation, and pharmacological manipulations. These studies have begun to elucidate a set of brain regions and neurotransmitter systems involved in decision-making in social interactions.     

The evolutionary basis of human social learning

Humans are characterized by an extreme dependence on culturally transmitted information. Such dependence requires the complex integration of social and asocial information to generate effective learning and decision making. Recent formal theory predicts that natural selection should favour adaptive learning strategies, but relevant empirical work is scarce and rarely examines multiple strategies or tasks. We tested nine hypotheses derived from theoretical models, running a series of experiments investigating factors affecting when and how humans use social information, and whether such behaviour is adaptive, across several computer-based tasks. The number of demonstrators, consensus among demonstrators, confidence of subjects, task difficulty, number of sessions, cost of asocial learning, subject performance and demonstrator performance all influenced subjects' use of social information, and did so adaptively. Our analysis provides strong support for the hypothesis that human social learning is regulated by adaptive learning rules.     

Defecting or not defecting: how to "read" human behavior during cooperative games by EEG measurements

Understanding the neural mechanisms responsible for human social interactions is difficult, since the brain activities of two or more individuals have to be examined simultaneously and correlated with the observed social patterns. We introduce the concept of hyper-brain network, a connectivity pattern representing at once the information flow among the cortical regions of a single brain as well as the relations among the areas of two distinct brains. Graph analysis of hyper-brain networks constructed from the EEG scanning of 26 couples of individuals playing the Iterated Prisoner's Dilemma reveals the possibility to predict non-cooperative interactions during the decision-making phase. The hyper-brain networks of two-defector couples have significantly less inter-brain links and overall higher modularity--i.e., the tendency to form two separate subgraphs--than couples playing cooperative or tit-for-tat strategies. The decision to defect can be "read" in advance by evaluating the changes of connectivity pattern in the hyper-brain network.     

Spatial learning and action planning in a prefrontal cortical network model

The interplay between hippocampus and prefrontal cortex (PFC) is fundamental to spatial cognition. Complementing hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive "insight" capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial planning, including prospective coding and distance-to-goal correlates.     

Information,behaviour and population dynamics

Animals must make decisions such as where and when to forage based on imperfect information about their variable world. A growing number of authors have addressed the information problem and its relation to behaviour, learning, cognition and evolution. Few studies, however, have analyzed how the quality of information available for decision making affects population growth and dynamics. Here I utilize stochastic dynamic models, statistical decision theory, and projection matrices to show how information affects patch choice and how these choices in turn affect fitness and population growth. The value of information, in terms of its impact on ?tness, depends on an organism's state and changes during the organism's life span. The relationship between a population's rate of increase and uncertainty about optimal patch choice amongst its members is concave with the positive effects of reduced uncertainty diminishing rapidly as individuals become more knowledgeable about their environment. The implications of these results for understanding populations and communities of interacting species are discussed.     

大脑中的抉择神经元

近年来神经科学领域的进展表明,大脑中不仅存在如位置神经元之类的特异性编码感觉信息的神经元,也存在能够特异性地反映动物思考过程的神经元。在一系列以侧内顶叶(LIP)为目标的猕猴电生理实验中,人们发现LIP神经元的动作电位发放率可以反映抉择思考的过程。抉择的研究为我们打开了一个研究大脑高级认知功能的窗口。抉择神经元的发现表明了大脑的高级认知功能是基于与感觉信息处理类似的神经计算原理。     

Applying evolutionary models to the laboratory study of social learning

Cultural evolution is driven, in part, by the strategies that individuals employ to acquire behavior from others. These strategies themselves are partly products of natural selection, making the study of social learning an inherently Darwinian project. Formal models of the evolution of social learning suggest that reliance on social learning should increase with task difficulty and decrease with the probability of environmental change. These models also make predictions about how individuals integrate information from multiple peers. We present the results of microsociety experiments designed to evaluate these predictions. The first experiment measures baseline individual learning strategy in a two-armed bandit environment with variation in task difficulty and temporal fluctuation in the payoffs of the options. Our second experiment addresses how people in the same environment use minimal social information from a single peer. Our third experiment expands on the second by allowing access to the behavior of several other individuals, permitting frequency-dependent strategies like conformity. In each of these experiments, we vary task difficulty and environmental fluctuation. We present several candidate strategies and compute the expected payoffs to each in our experimental environment. We then fit to the data the different models of the use of social information and identify the best-fitting model via model comparison techniques. We find substantial evidence of both conformist and nonconformist social learning and compare our results to theoretical expectations.     

Explicit neural signals reflecting reward uncertainty

The acknowledged importance of uncertainty in economic decision making has stimulated the search for neural signals that could influence learning and inform decision mechanisms. Current views distinguish two forms of uncertainty, namely risk and ambiguity, depending on whether the probability distributions of outcomes are known or unknown. Behavioural neurophysiological studies on dopamine neurons revealed a risk signal, which covaried with the standard deviation or variance of the magnitude of juice rewards and occurred separately from reward value coding. Human imaging studies identified similarly distinct risk signals for monetary rewards in the striatum and orbitofrontal cortex (OFC), thus fulfilling a requirement for the mean variance approach of economic decision theory. The orbitofrontal risk signal covaried with individual risk attitudes, possibly explaining individual differences in risk perception and risky decision making. Ambiguous gambles with incomplete probabilistic information induced stronger brain signals than risky gambles in OFC and amygdala, suggesting that the brain's reward system signals the partial lack of information. The brain can use the uncertainty signals to assess the uncertainty of rewards, influence learning, modulate the value of uncertain rewards and make appropriate behavioural choices between only partly known options.     

Functional role of the ventrolateral prefrontal cortex in decision making

To make deliberate decisions, we have to utilize detailed information about the environment and our internal states. The ventral visual pathway provides detailed information on object identity, including color and shape, to the ventrolateral prefrontal cortex (VLPFC). The VLPFC also receives motivational and emotional information from the orbitofrontal cortex and subcortical areas, and computes the behavioral significance of external events; this information can be used for elaborate decision making or design of goal-directed behavior. In this review, we discuss recent advances that are revealing the neural mechanisms that underlie the coding of behavioral significance in the VLPFC, and the functional roles of these mechanisms in decision making and action programming in the brain.     

Evolution of social learning does not explain the origin of human cumulative culture

Because culture requires transmission of information between individuals, thinking about the origin of culture has mainly focused on the genetic evolution of abilities for social learning. Current theory considers how social learning affects the adaptiveness of a single cultural trait, yet human culture consists of the accumulation of very many traits. Here we introduce a new modeling strategy that tracks the adaptive value of many cultural traits, showing that genetic evolution favors only limited social learning owing to the accumulation of maladaptive as well as adaptive culture. We further show that culture can be adaptive, and refined social learning can evolve, if individuals can identify and discard maladaptive culture. This suggests that the evolution of such "adaptive filtering" mechanisms may have been crucial for the birth of human culture.     

内侧前额叶与社会认知

早期的研究表明杏仁核、前额叶、颞上沟、前扣带回等与人类的社会认知活动有关;随着多种新技术的应用。越来越多的研究发现其它一些脑区结构(如岛叶、基底节、白质等)也与社会认知和行为有关。本文综述了内侧前额叶在社会认知中的作用,重点介绍了内侧前额叶在心灵理论、情绪认知、社会推理与决策、道德判断、自我认知等社会认知活动中的作用。未来研究希望能从整体和动态上认识内侧前额叶在社会认知活动中的作用。     

Relative timing: from behaviour to neurons

Processing of temporal information is critical to behaviour. Here, we review the phenomenology and mechanism of relative timing, ordinal comparisons between the timing of occurrence of events. Relative timing can be an implicit component of particular brain computations or can be an explicit, conscious judgement. Psychophysical measurements of explicit relative timing have revealed clues about the interaction of sensory signals in the brain as well as in the influence of internal states, such as attention, on those interactions. Evidence from human neurophysiological and functional imaging studies, neuropsychological examination in brain-lesioned patients, and temporary disruptive interventions such as transcranial magnetic stimulation (TMS), point to a role of the parietal cortex in relative timing. Relative timing has traditionally been modelled as a ‘race’ between competing neural signals. We propose an updated race process based on the integration of sensory evidence towards a decision threshold rather than simple signal propagation. The model suggests a general approach for identifying brain regions involved in relative timing, based on looking for trial-by-trial correlations between neural activity and temporal order judgements (TOJs). Finally, we show how the paradigm can be used to reveal signals related to TOJs in parietal cortex of monkeys trained in a TOJ task.     

Counterfactual choice and learning in a neural network centered on human lateral frontopolar cortex

Decision making and learning in a real-world context require organisms to track not only the choices they make and the outcomes that follow but also other untaken, or counterfactual, choices and their outcomes. Although the neural system responsible for tracking the value of choices actually taken is increasingly well understood, whether a neural system tracks counterfactual information is currently unclear. Using a three-alternative decision-making task, a Bayesian reinforcement-learning algorithm, and fMRI, we investigated the coding of counterfactual choices and prediction errors in the human brain. Rather than representing evidence favoring multiple counterfactual choices, lateral frontal polar cortex (lFPC), dorsomedial frontal cortex (DMFC), and posteromedial cortex (PMC) encode the reward-based evidence favoring the best counterfactual option at future decisions. In addition to encoding counterfactual reward expectations, the network carries a signal for learning about counterfactual options when feedback is available-a counterfactual prediction error. Unlike other brain regions that have been associated with the processing of counterfactual outcomes, counterfactual prediction errors within the identified network cannot be related to regret theory. Furthermore, individual variation in counterfactual choice-related activity and prediction error-related activity, respectively, predicts variation in the propensity to switch to profitable choices in the future and the ability to learn from hypothetical feedback. Taken together, these data provide both neural and behavioral evidence to support the existence of a previously unidentified neural system responsible for tracking both counterfactual choice options and their outcomes.