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Functional Connectome from Phase Synchrony at Resting State is a Neural Fingerprint.
Brain Connectivity ( IF 3.4 ) Pub Date : 2019-06-28 , DOI: 10.1089/brain.2018.0657
Ruibin Zhang 1, 2, 3, 4, 5 , Georg S Kranz 1, 6, 7 , Tatia M C Lee 1, 2, 8
Affiliation  

Coherent oscillatory activity across brain regions provides a variety of individual-specific characteristics, sometimes referred to as a neural fingerprint. This information, however, may not be directly retrieved from raw functional magnetic resonance imaging (fMRI) time series. In this study, we examined the data of 205 participants who completed two resting-state fMRI scanning sessions, separated by an average of 2.63 years. In the first step, we tested the long-term reliability of functional connectomes derived from amplitude-based functional connectivity (the conventional method) and found that they remained accurate markers (>85%, p < 0.001, permutation test) for identifying individuals, even after a period longer than 800 days. Using the same data set, we further expanded our exploration of the extent to which two analytic components of oscillatory activity (amplitude envelope and instantaneous phase) may function as reliable fingerprints. Both analytic signals-in particular, the instantaneous phase-were identified as useful indices in shaping functional connectivity fingerprints (86%, p < 0.001, permutation test). Connectivity profiles derived from the ventral attention, frontoparietal, and default mode networks were the largest contributing factors to identification. The current results suggest that neural synchronization tapped by analytical signal from a low-frequency resting-state fMRI blood oxygen level-dependent oscillation could be a reliable and useful fingerprint for identifying individuals and might provide an alternative method for characterizing dynamic functional connectivity profiles.

中文翻译:

静止状态下来自相位同步的功能性连接体是一种神经指纹。

跨大脑区域的相干振荡活动提供了各种特定于个体的特征,有时称为神经指纹。但是,可能无法直接从原始功能磁共振成像(fMRI)时间序列中检索此信息。在这项研究中,我们检查了205位参与者的数据,他们完成了两次静息状态fMRI扫描,平均间隔了2.63年。第一步,我们测试了基于振幅的功能连接性(传统方法)得出的功能连接体的长期可靠性,发现它们仍然是用于识别个体的准确标记(> 85%,p <0.001,置换测试),即使超过800天之后也是如此。使用相同的数据集 我们进一步扩展了对振荡活动的两个分析成分(幅度包络和瞬时相位)可以用作可靠指纹的程度的探索。两种分析信号(尤其是瞬时相位)均被确定为塑造功能连接指纹的有用指标(86%,p <0.001,置换测试)。来自腹侧注意力,额叶额叶和默认模式网络的连接配置文件是识别的最大因素。
更新日期:2019-11-01
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