关键词: 群际偏差, 主观价值, 功能性磁共振脑成像技术, 合作, 催产素

Abstract: Intergroup bias, the tendency to favor the ingroup over the outgroup, is a pervasive feature of human social life and a major force shaping cooperation, exclusion, and conflict across group boundaries. Although prior research has documented robust ingroup favoritism and linked it to a range of psychological and neural processes, a core computational question remains unresolved: when people evaluate allocations, payoffs, or interests involving both ingroup and outgroup members, how do they subjectively weight these two sides, and how does this weighting shape intergroup behavior? Existing accounts have identified relevant motives, attitudes, and brain regions, but they have rarely specified the computational process by which ingroup and outgroup interests are differentially valued. The central idea is that intergroup bias arises, at least in part, because individuals do not assign equal subjective weight to ingroup and outgroup interests. Instead, the same or comparable payoffs may be valued differently depending on whether they benefit the ingroup or the outgroup. On this view, intergroup bias is not simply a descriptive tendency or a downstream behavioral pattern; it reflects a specific distortion in social value computation that may help explain why some individuals cooperate across group boundaries, whereas others shift toward parochial defense, exclusion, or aggression. Across five linked studies, the project will test whether individuals differ in how they weight ingroup and outgroup interests, formalize such variation in an Intergroup Reference Point Model, identify its neural basis, evaluate its predictive value for intergroup cooperation and conflict, and examine whether these computations can be modulated by intranasal oxytocin.
Study 1 will test the project's basic behavioral claim: that individuals assign systematically different subjective weights to ingroup and outgroup interests, and that the magnitude of this weighting bias varies reliably across individuals. Using a large-sample design, participants will be assigned to minimal groups and will complete parallel interpersonal and intergroup decision tasks, including social value orientation measures, an intergroup prisoner's dilemma-maximizing difference task, an intergroup public goods game, and trait assessments. A central goal is to determine whether intergroup valuation can be dissociated from general interpersonal prosociality rather than treated as a simple extension of it. If supported, this distinction will be used to identify theoretically informative profiles, particularly egalitarians and parochial altruists. These groups are expected to be comparable in interpersonal prosociality while differing substantially in the relative value they assign to ingroup versus outgroup interests, thereby providing a basis for the subsequent computational and neuroimaging studies.
Study 2 will develop the Intergroup Reference Point Model as an individualized computational account of intergroup valuation. Using participants drawn from the key valuation profiles identified in Study 1, followed by validation in a broader sample, the study will model subjective evaluations of ingroup-outgroup allocation options as a weighted combination of ingroup and outgroup interests. From this model, it will derive an angular reference-point parameter that captures each individual's preferred trade-off between ingroup and outgroup interests. The key question is whether intergroup bias can be formalized not simply as a categorical preference or observed choice tendency, but as a continuous and interpretable computational signature. By quantifying the relative weight assigned to ingroup and outgroup interests, the model will provide a continuous index of the degree to which a person privileges ingroup over outgroup interests, enable direct comparison between egalitarian and parochial-altruistic valuation under matched levels of interpersonal prosociality, and generate model-based parameters for the subsequent neural and behavioral analyses.
Study 3 will examine the neural implementation of intergroup subjective value computation by integrating model-derived parameters with functional MRI. Using valuation profile as a group factor and model parameters as continuous indices of individual difference, the study will test where and how the brain represents the subjective weighting of ingroup and outgroup interests, computes their integrated subjective value, and tracks the distance between a given allocation and an individual's preferred intergroup trade-off. Analyses will combine ROI-based and whole-brain parametric modulation within a first-level GLM, multivoxel pattern analysis, DCM-based effective connectivity analysis, and graph-theoretical characterization of whole-brain functional networks. The main issue is whether intergroup value computation relies on a common neural mechanism or diverges between egalitarians and parochial altruists despite comparable interpersonal prosociality. In particular, the study will contrast an amygdala-centered, fairness-sensitive route with an orbitofrontal, strategically weighted route for intergroup value computation. This work is expected to provide a mechanistic neural framework for understanding how subjective value is computed when social interests are divided along group boundaries.
Study 4 will test whether intergroup subjective value computation and its neural correlates predict behavior across intergroup contexts that vary in antagonistic intensity. If proposed intergroup valuation is a behaviorally meaningful computational process, then its parameters and neural signatures should predict which individuals cooperate across group boundaries and which shift toward parochial cooperation, punitive hostility, or aggression as conflict escalates. To test this, the study will use a set of interactive paradigms spanning lower- to higher-conflict contexts and examine whether individuals who assign more balanced subjective value to ingroup and outgroup interests show greater cross-group cooperation, whereas those who assign disproportionately greater weight to ingroup interests show stronger parochial cooperation, greater willingness to punish outgroup members, and more aggressive responding as antagonism increases. At the neural level, the study will ask whether these behavioral tendencies are supported by distinguishable processing routes: one relying more heavily on fairness-sensitive affective valuation and the other relying more heavily on strategically weighted intergroup value computation. In this way, the project will move from computational and neural characterization to behavioral prediction.
Study 5 will introduce a neurobiological manipulation by testing whether intranasal oxytocin can recalibrate intergroup subjective value and, through that route, alter cooperation and conflict across group boundaries. Building on the computational and neural framework established in the preceding studies, the study will examine three possibilities: whether oxytocin promotes a more balanced valuation of ingroup and outgroup interests, selectively attenuates biased valuation in parochial altruists, or instead amplifies defensive intergroup responding under threat. Crucially, the study will not assume that oxytocin exerts a uniform prosocial effect. Instead, it will test whether oxytocin's impact depends on pre-existing valuation style and social context. By treating oxytocin as a probe of the plasticity of the Intergroup Reference Point, the project will extend the framework from explanation and prediction to intervention.
Overall, this proposal seeks to establish an integrated account of intergroup bias by explaining how people assign subjective weight to ingroup and outgroup interests, how this value computation is implemented in the brain, how it shapes cooperation and conflict, and how it may be modulated through oxytocin-based intervention. Across five studies, the project will move from identifying individual differences in intergroup valuation, to formalizing them computationally, to specifying their neural mechanisms, behavioral consequences, and biological malleability. The proposed work is expected to provide a quantitative and neurally grounded framework for understanding, predicting, and potentially regulating cooperation and conflict across group boundaries.

Key words: intergroup bias, subjective value computation, functional magnetic resonance imaging (fMRI), cooperation, oxytocin