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静息状态下的即兴创作:通过静息态功能连接区分爵士和古典音乐训练。

Improvising at rest: Differentiating jazz and classical music training with resting state functional connectivity.

机构信息

Northeastern University, USA; Wesleyan University, USA.

Wesleyan University, USA; University of Pennsylvania, USA.

出版信息

Neuroimage. 2020 Feb 15;207:116384. doi: 10.1016/j.neuroimage.2019.116384. Epub 2019 Nov 21.

Abstract

Jazz improvisation offers a model for creative cognition, as it involves the real-time creation of a novel, information-rich product. Previous research has shown that when musicians improvise, they recruit regions in the Default Mode Network (DMN) and Executive Control Network (ECN). Here, we ask whether these findings from task-fMRI studies might extend to intrinsic differences in resting state functional connectivity. We compared Improvising musicians, Classical musicians, and Minimally Musically Trained (MMT) controls in seed-based functional connectivity and network analyses in resting state functional MRI. We also examined the functional correlates of behavioral performance in musical improvisation and divergent thinking. Seed-based analysis consistently showed higher connectivity in ventral DMN (vDMN) and bilateral ECN in both groups of musically trained individuals as compared to MMT controls, with additional group differences in primary visual network. In particular, primary visual network connectivity to DMN and ECN was highest in Improvisational musicians, as was connectivity between ECN and DMN; in contrast, connectivity between vDMN and frontal pole was highest in Classical musicians. Furthermore, graph-theoretical analysis indicated heightened network measures in both musician groups, with betweenness centrality, clustering, and local efficiency showing highest levels in Classical musicians, and degrees and strengths showing highest levels in Improvisational musicians. Taken together, results suggest that heightened functional connectivity among musicians can be explained by higher within-network connectivity (more tight-knit cortical networks) in Classical musicians, as opposed to more disperse, globally-connected cortical networks in Improvisational musicians.

摘要

爵士乐即兴创作提供了一种创造性认知的模型,因为它涉及到实时创作新颖的、信息丰富的产品。先前的研究表明,当音乐家即兴创作时,他们会招募默认模式网络(DMN)和执行控制网络(ECN)中的区域。在这里,我们想知道这些来自任务 fMRI 研究的发现是否可以扩展到静息态功能连接的内在差异。我们比较了即兴演奏音乐家、古典音乐家和最小音乐训练(MMT)对照组在静息态功能磁共振成像中的基于种子的功能连接和网络分析。我们还检查了音乐即兴创作和发散思维中行为表现的功能相关性。基于种子的分析一致表明,在两个音乐训练组中,腹侧 DMN(vDMN)和双侧 ECN 的连接性高于 MMT 对照组,而初级视觉网络则存在额外的组间差异。特别是,初级视觉网络与 DMN 和 ECN 的连接性在即兴演奏音乐家中最高,而 ECN 和 DMN 之间的连接性也最高;相比之下,在古典音乐家中,vDMN 和额极之间的连接性最高。此外,图论分析表明,两个音乐家组的网络指标都有所提高,其中,古典音乐家的介数中心度、聚类系数和局部效率最高,而即兴演奏音乐家的度数和强度最高。总之,结果表明,音乐家之间功能连接的增强可以用古典音乐家中更高的网络内连接性(更紧密的皮质网络)来解释,而不是即兴演奏音乐家中更分散的、全局连接的皮质网络。

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