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Investigating time-varying functional connectivity derived from the Jackknife Correlation method for distinguishing between emotions in fMRI data.
Cognitive Neurodynamics ( IF 3.7 ) Pub Date : 2020-03-29 , DOI: 10.1007/s11571-020-09579-5
Shabnam Ghahari 1 , Naemeh Farahani 1 , Emad Fatemizadeh 2 , Ali Motie Nasrabadi 3
Affiliation  

Investigating human brain activity during expressing emotional states provides deep insight into complex cognitive functions and neurological correlations inside the brain. To be able to resemble the brain function in the best manner, a complex and natural stimulus should be applied as well, the method used for data analysis should have fewer assumptions, simplifications, and parameter adjustment. In this study, we examined a functional magnetic resonance imaging dataset obtained during an emotional audio-movie stimulus associated with human life. We used Jackknife Correlation (JC) method to derive a representation of time-varying functional connectivity. We applied different binary measures and thoroughly investigated two weighted measures to study different properties of binary and weighted temporal networks. Using this approach, we indicated different aspects of human brain function during expressing different emotions. The findings of global and nodal measures could demonstrate a significant difference between emotions and significant regions in each emotion, respectively. Also, the temporal centrality properties of nodes were different in emotional states. Ultimately, we showed that the resulting measures of temporal snapshots created by JC method can distinguish between different emotions.

中文翻译:

调查源自 Jackknife 相关方法的时变功能连通性,用于区分 fMRI 数据中的情绪。

在表达情绪状态期间调查人类大脑活动可以深入了解大脑内部复杂的认知功能和神经系统相关性。为了能够以最佳方式模拟大脑功能,还应该应用复杂而自然的刺激,用于数据分析的方法应该具有较少的假设、简化和参数调整。在这项研究中,我们检查了在与人类生活相关的情感音频电影刺激过程中获得的功能磁共振成像数据集。我们使用 Jackknife Correlation (JC) 方法来推导时变功能连接的表示。我们应用了不同的二元度量并彻底研究了两个加权度量来研究二元和加权时间网络的不同属性。使用这种方法,我们在表达不同情绪的过程中指出了人脑功能的不同方面。全局和节点测量的结果可以分别证明情绪和每种情绪中的重要区域之间存在显着差异。此外,节点的时间中心性属性在情绪状态下是不同的。最终,我们证明了 JC 方法创建的时间快照的结果测量可以区分不同的情绪。
更新日期:2020-03-29
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