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Identification of traits and functional connectivity-based neurotraits of chronic pain

机译:慢性疼痛的特征和基于功能连接的神经特征的识别

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摘要

Psychological and personality factors, socioeconomic status, and brain properties all contribute to chronic pain but have essentially been studied independently. Here, we administered a broad battery of questionnaires to patients with chronic back pain (CBP) and collected repeated sessions of resting-state functional magnetic resonance imaging (fMRI) brain scans. Clustering and network analyses applied on the questionnaire data revealed four orthogonal dimensions accounting for 56% of the variance and defining chronic pain traits. Two of these traits—Pain-trait and Emote-trait—were associated with back pain characteristics and could be related to distinct distributed functional networks in a cross-validation procedure, identifying neurotraits. These neurotraits showed good reliability across four fMRI sessions acquired over five weeks. Further, traits and neurotraits all related to the income, emphasizing the importance of socioeconomic status within the personality space of chronic pain. Our approach is a first step in providing metrics aimed at unifying the psychology and the neurophysiology of chronic pain applicable across diverse clinical conditions.
机译:心理和人格因素,社会经济地位和大脑特性均会导致慢性疼痛,但基本上已进行了独立研究。在这里,我们向患有慢性背痛(CBP)的患者进行了一系列问卷调查,并收集了重复的静息状态功能磁共振成像(fMRI)脑部扫描。对问卷数据进行的聚类和网络分析显示出四个正交维度,占差异的56%,并定义了慢性疼痛特征。这些特征中的两个(疼痛特征和表情特质)与背痛特征相关联,并且可能在交叉验证过程中与不同的分布式功能网络有关,以识别神经性状。在五周内进行的四次fMRI检查中,这些神经质表现出良好的可靠性。此外,性状和神经性状都与收入有关,强调了在慢性疼痛的人格空间内社会经济地位的重要性。我们的方法是提供旨在统一适用于各种临床条件的慢性疼痛的心理学和神经生理学指标的第一步。

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