This study examined how ethnic identity relates to large-scale brain networks implicated in social interactions, social cognition, self-definition, and cognitive control. Group Iterative Multiple Model Estimation (GIMME) was used to create sparse, person-specific networks among the default mode and frontoparietal resting-state networks in a diverse sample of 104 youths aged 17–21. Links between neural density (i.e., number of connections within and between these networks) and ethnic identity exploration and resolution were evaluated in the full sample. Ethnic identity resolution was positively related to frontoparietal network density, suggesting that having clarity about one’s ethnic group membership is associated with brain network organization reflecting cognitive control. These findings help fill a critical knowledge gap about the neural underpinnings of ethnic identity.

中文翻译：

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个性化神经网络是种族认同探索和解决中个体差异的基础

本研究调查了种族认同如何与涉及社会互动、社会认知、自我定义和认知控制的大规模大脑网络相关。组迭代多模型估计 (GIMME) 用于在 104 名 17-21 岁青年的不同样本中，在默认模式和额顶叶静息状态网络之间创建稀疏的、特定于人的网络。在整个样本中评估了神经密度（即这些网络内部和之间的连接数量）与种族认同探索和解决之间的联系。种族认同感与额顶叶网络密度呈正相关，这表明清楚地了解一个人的种族群体成员身份与反映认知控制的大脑网络组织有关。