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脑网络动力学可预测不同情境下的意外时刻。

Brain network dynamics predict moments of surprise across contexts.

作者信息

Zhang Ziwei, Rosenberg Monica D

机构信息

Department of Psychology, The University of Chicago, Chicago, IL, USA.

Institute for Mind and Biology, The University of Chicago, Chicago, IL, USA.

出版信息

Nat Hum Behav. 2025 Mar;9(3):554-568. doi: 10.1038/s41562-024-02017-0. Epub 2024 Dec 23.

Abstract

We experience surprise when reality conflicts with our expectations. When we encounter such expectation violations in psychological tasks and daily life, are we experiencing completely different forms of surprise? Or is surprise a fundamental psychological process with shared neural bases across contexts? To address this question, we identified a brain network model, the surprise edge-fluctuation-based predictive model (EFPM), whose regional interaction dynamics measured with functional magnetic resonance imaging (fMRI) predicted surprise in an adaptive learning task. The same model generalized to predict surprise as a separate group of individuals watched suspenseful basketball games and as a third group watched videos violating psychological expectations. The surprise EFPM also uniquely predicts surprise, capturing expectation violations better than models built from other brain networks, fMRI measures and behavioural metrics. These results suggest that shared neurocognitive processes underlie surprise across contexts and that distinct experiences can be translated into the common space of brain dynamics.

摘要

当现实与我们的期望相冲突时,我们会感到惊讶。当我们在心理任务和日常生活中遇到这种期望违背的情况时,我们所经历的是完全不同形式的惊讶吗?还是说惊讶是一种基本的心理过程,在不同情境下具有共同的神经基础?为了解决这个问题,我们确定了一种脑网络模型,即基于惊讶边缘波动的预测模型(EFPM),其通过功能磁共振成像(fMRI)测量的区域相互作用动态能够预测适应性学习任务中的惊讶程度。同一模型还能够推广应用,在另一组个体观看悬疑篮球比赛以及第三组个体观看违背心理预期的视频时预测惊讶程度。惊讶EFPM还能独特地预测惊讶,比基于其他脑网络、fMRI测量和行为指标构建的模型更能捕捉到期望违背的情况。这些结果表明,不同情境下的惊讶背后存在共同的神经认知过程,并且不同的体验可以转化为脑动态的共同空间。

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