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Connecting Openness and the Resting-State Brain Network: A Discover-Validate Approach

机译:连接开放性与静息状态的大脑网络:发现验证方法

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摘要

In personality neuroscience, the openness-brain association has been a topic of interest. Previous studies usually started from difference in openness trait and used it to infer brain functional activity characteristics, but no study has used a “brain-first” research strategy to explore that association based on more objective brain imaging data. In this study, we used a fully data-driven approach to discover and validate the association between openness and the resting-state brain network. We collected data of 120 subjects as a discovery sample and 56 subjects as a validation sample. The Neuroticism Extraversion Openness Five-Factor Inventory (NEO-FFI) was used to measure the personality characteristics of all the subjects. Using an exploratory approach based on independent component analysis of resting-state functional magnetic resonance imaging (fMRI) data, we identified a parietal network that consisted of the precuneus and inferior parietal lobe. The inter-subject similarity of the parietal memory network exhibited significant associations with openness trait, and this association was validated using the 56-subject independent sample. This finding connects the openness trait to the characteristics of a neural network and helps to understand the underlying biology of the openness trait.
机译:在人格神经科学中,开放性大脑关联一直是一个有趣的话题。以前的研究通常从开放性特征的差异开始,并用它来推断脑功能活动特征,但是没有研究使用“脑优先”研究策略来基于更客观的脑成像数据来探索这种关联。在这项研究中,我们使用了一种完全由数据驱动的方法来发现和验证开放性与静止状态大脑网络之间的关联。我们收集了120个受试者的数据作为发现样本,并收集了56个受试者的数据作为验证样本。神经质外向性开放性五因素量表(NEO-FFI)用于测量所有受试者的人格特征。使用基于静止状态功能磁共振成像(fMRI)数据的独立成分分析的探索性方法,我们确定了由前胎和下顶叶组成的顶叶网络。顶叶记忆网络的受试者间相似性与开放性具有显着的关联,这种关联已使用56个受试者的独立样本进行了验证。这一发现将开放性与神经网络的特征联系起来,有助于理解开放性的内在生物学。

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