Dynamic cycles between brain states during creative storytelling

IF 4.7 2区 医学 Q1 NEUROIMAGING NeuroImage Pub Date : 2025-01-24 DOI:10.1016/j.neuroimage.2025.121053
Xitong Liang , Mingnan Cai , Gaohan Jing , Chengming Zhang , Emily Sophia Nichols , Li Liu
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引用次数: 0

Abstract

Many theories suggest that creative thinking involves a dynamic transition between different mental states, yet empirical evidence supporting this notion remains scarce. The dual process model proposes that spontaneous thinking and deliberate thinking drive the dwell in and the transitions between different mental states during creative thinking, but there is a debate over whether the two types of thinking operate in parallel or in sequence. To address these gaps, we conducted a functional magnetic resonance imaging (fMRI) study in 41 college students during a creative storytelling task. We then compared the dynamic brain states in creative versus uncreative storytelling to identify key brain states associated with creative thinking. And we further performed correlation analysis between these key brain states with performance of various creative tasks, trying to link the key brain states with different cognitive processes. The results showed that two key brain states are associated with creative thinking, with one involving whole-brain synchronization and the other involving the synchronization of four networks, including the default mode network and the control network. The transition patterns between the key brain states provide tentative evidence for dynamic circulation between different mental states during creative storytelling. Using a deep learning approach, we demonstrate an alternating interaction between spontaneous and deliberate thinking, driving dwelling in and the transitions between different brain states. These findings deepen our understanding of the cognitive and neural mechanisms underlying creative thinking.
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来源期刊
NeuroImage
NeuroImage 医学-核医学
CiteScore
11.30
自引率
10.50%
发文量
809
审稿时长
63 days
期刊介绍: NeuroImage, a Journal of Brain Function provides a vehicle for communicating important advances in acquiring, analyzing, and modelling neuroimaging data and in applying these techniques to the study of structure-function and brain-behavior relationships. Though the emphasis is on the macroscopic level of human brain organization, meso-and microscopic neuroimaging across all species will be considered if informative for understanding the aforementioned relationships.
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