语义整合需要调节大脑中的大规模网络交互。

IF 3.5 2区 医学 Q1 NEUROIMAGING Human Brain Mapping Pub Date : 2024-12-26 DOI:10.1002/hbm.70113
Laura Nieberlein, Sandra Martin, Kathleen A. Williams, Alexander Gussew, Sophia D. Cyriaks, Maximilian Scheer, Stefan Rampp, Julian Prell, Gesa Hartwigsen
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引用次数: 0

摘要

将语义信息整合到句子上下文中的能力对于人类的交流是必不可少的。一些研究表明,基于句子语境的最终关键词的可预测性在行为、神经生理和神经层面影响语义整合。然而,跨生命周期语义集成的底层网络交互的体系结构仍然不清楚。在这项研究中,32名健康的参与者(30-75岁)在功能性磁共振成像(fMRI)期间完成了一个听觉完形概率任务,要求他们对句子的最后一个词做出词汇判断。语义整合需求通过呈现预期、意外、异常或假词结尾的句子来隐式调节。为了阐明支持语义整合的网络交互,我们将基于单变量任务的fMRI分析与基于种子的连通性和网络间连通性分析相结合。行为数据显示了典型的语义整合效应,增加的整合需求与更长的响应延迟和降低的准确性相关。单变量结果表明,对于整合要求较高的句子,左额叶和颞叶脑活动增加。网络间交互强调了任务积极网络和默认模式网络在语义整合需求增加的句子处理中的作用。此外,不断增加的整合需求导致了更多与行为相关的网络交互,这表明随着整合需求的增加,网络间耦合的增加与成功的任务绩效更加相关。我们的研究结果阐明了跨越衰老连续体的复杂网络相互作用。不同的任务正态网络和默认模式网络之间的交互作用越强,语义整合要求越高,句子加工效率越高。这些结果可能为未来对健康老年人和临床人群的研究提供信息。
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Semantic Integration Demands Modulate Large-Scale Network Interactions in the Brain

The ability to integrate semantic information into the context of a sentence is essential for human communication. Several studies have shown that the predictability of a final keyword based on the sentence context influences semantic integration on the behavioral, neurophysiological, and neural level. However, the architecture of the underlying network interactions for semantic integration across the lifespan remains unclear. In this study, 32 healthy participants (30–75 years) performed an auditory cloze probability task during functional magnetic resonance imaging (fMRI), requiring lexical decisions on the sentence's final words. Semantic integration demands were implicitly modulated by presenting sentences with expected, unexpected, anomalous, or pseudoword endings. To elucidate network interactions supporting semantic integration, we combined univariate task-based fMRI analyses with seed-based connectivity and between-network connectivity analyses. Behavioral data revealed typical semantic integration effects, with increased integration demands being associated with longer response latencies and reduced accuracy. Univariate results demonstrated increased left frontal and temporal brain activity for sentences with higher integration demands. Between-network interactions highlighted the role of task-positive and default mode networks for sentence processing with increased semantic integration demands. Furthermore, increasing integration demands led to a higher number of behaviorally relevant network interactions, suggesting that the increased between-network coupling becomes more relevant for successful task performance as integration demands increase. Our findings elucidate the complex network interactions underlying semantic integration across the aging continuum. Stronger interactions between various task-positive and default mode networks correlated with more efficient processing of sentences with increased semantic integration demands. These results may inform future studies with healthy old and clinical populations.

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来源期刊
Human Brain Mapping
Human Brain Mapping 医学-核医学
CiteScore
8.30
自引率
6.20%
发文量
401
审稿时长
3-6 weeks
期刊介绍: Human Brain Mapping publishes peer-reviewed basic, clinical, technical, and theoretical research in the interdisciplinary and rapidly expanding field of human brain mapping. The journal features research derived from non-invasive brain imaging modalities used to explore the spatial and temporal organization of the neural systems supporting human behavior. Imaging modalities of interest include positron emission tomography, event-related potentials, electro-and magnetoencephalography, magnetic resonance imaging, and single-photon emission tomography. Brain mapping research in both normal and clinical populations is encouraged. Article formats include Research Articles, Review Articles, Clinical Case Studies, and Technique, as well as Technological Developments, Theoretical Articles, and Synthetic Reviews. Technical advances, such as novel brain imaging methods, analyses for detecting or localizing neural activity, synergistic uses of multiple imaging modalities, and strategies for the design of behavioral paradigms and neural-systems modeling are of particular interest. The journal endorses the propagation of methodological standards and encourages database development in the field of human brain mapping.
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