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Functional connectivity predicts the dispositional use of expressive suppression but not cognitive reappraisal

机译:功能性连接预测​​表征抑制但未认知的使用

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Introduction Previous research has identified specific brain regions associated with regulating emotion using common strategies such as expressive suppression and cognitive reappraisal. However, most research focuses on a priori regions and directs participants how to regulate, which may not reflect how people naturally regulate outside the laboratory. Method Here, we used a data‐driven approach to investigate how individual differences in distributed intrinsic functional brain connectivity predict emotion regulation tendency outside the laboratory. Specifically, we used connectome‐based predictive modeling to extract functional connections in the brain significantly related to the dispositional use of suppression and reappraisal. These edges were then used in a predictive model and cross‐validated in novel participants to identify a neural signature that reflects individual differences in the tendency to suppress and reappraise emotion. Results We found a significant neural signature for the dispositional use of suppression, but not reappraisal. Within this whole‐brain signature, the intrinsic connectivity of the default mode network was most informative of suppression tendency. In addition, the predictive performance of this model was significant in males, but not females. Conclusion These findings help inform how whole‐brain networks of functional connectivity characterize how people tend to regulate emotion outside the laboratory.
机译:简介以前的研究已经确定了使用常见策略(如表现性抑制和认知Reappraisal)的常见策略相关的特定大脑区域。然而,大多数研究侧重于先验地区,并指示参与者如何规范,这可能无法反映人们自然地监管在实验室之外。这里的方法,我们使用了数据驱动方法来研究分布式内在功能脑连接的个体差异如何预测实验室外的情绪调节趋势。具体而言,我们使用基于连接的预测模型来提取与抑制和重新评估的抑制和重新评估的拟议使用显着相关的脑中的功能连接。然后将这些边缘用于预测模型中,并在新的参与者中交叉验证,以识别内神经签名,以反映抑制和重新出现情绪的倾向的个体差异。结果我们发现了一个重要的神经签名,用于抑制的抑制,但没有重复。在这种全脑中签名中,默认模式网络的内在连接最为富有于抑制趋势。此外,这种模型的预测性能在雄性中显着,但不是女性。结论这些发现有助于告知全脑网络的功能连接方式是如何表征人们如何在实验室以外调节情感。

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