个体差异在P3网络空间配置中的功能意义

Pub Date : 2022-02-24 DOI:10.1027/0269-8803/a000295
A. J. Privitera, A. Tang
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引用次数: 1

摘要

摘要脑电图(EEG)事件相关电位(ERPs)中P3成分的振幅和潜伏期是用于正常和异常大脑功能个体差异的最广泛使用的标志物之一。相反,时间定义的P3分量的空间地形的个体变化相对未被充分探索。基于EEG的源成像的发展开辟了一种可能性,即在时间定义的P3分量基础上的神经网络的个体特定空间配置承载了一种新的信息源,用于标记行为和认知功能的个体差异。在验证这一假设时,将盲源分离(BSS)、等效电流偶极子(ECD)建模和基于hits向量的分析组成的混合方法应用于从13名执行视觉颜色古怪任务的健康人类参与者收集的连续未划时代EEG数据。通过分析时间定义的P3分量(以下称为P3N)下的网络的空间配置,我们发现P3N内的每个组成结构的贡献是不均匀的。相反,额叶结构比其他组成结构有更多的参与,其定量特征是跨个体可靠性和个体内对P3N的贡献。对命中向量数据的因子分析显示,尽管P3潜伏期和幅度与行为结果的测量没有显示出显著的相关性,但从命中向量得出的两个因子的得分选择性地预测了行为反应时间和反应正确性。这些结果支持这样一种假设,即P3空间配置的变化不仅反映了噪声,而且反映了具有功能意义的个体特定特征。
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Functional Significance of Individual Differences in P3 Network Spatial Configuration
Abstract. The amplitude and latency of the P3 component in the electroencephalogram (EEG) event-related potentials (ERPs) are among the most extensively used markers for individual differences in normal and abnormal brain functions. In contrast, individual variations in spatial topography of the temporally-defined P3 component are relatively under-explored. Development in EEG-based source imaging opened up the possibility that individual-specific spatial configuration of the neural network underlying the temporally-defined P3 component bear a novel source of information for marking an individual difference in behavioral and cognitive function. In testing this hypothesis, a hybrid method consisting of blind source separation (BSS), equivalent current dipole (ECD) modeling, and hits-vector-based analysis was applied to continuous un-epoched EEG data collected from 13 healthy human participants performing a visual color oddball task. By analyzing the spatial configuration of the network underlying the temporally-defined P3 component, hereafter referred to as the P3N, we discovered that the contribution of each constituent structure within the P3N is not uniform. Instead, frontal lobe structures have significantly more involvement than other constituent structures, as quantitatively characterized by cross-individual reliability and a within-individual contribution to the P3N. A factor analysis of the hits vector data revealed that although P3 latency and amplitude did not show significant correlations with measures of the behavioral outcomes, scores of two factors derived from the hits vectors selectively predict behavioral reaction time and response correctness. These results support the hypothesis that variations in P3 spatial configuration reflect not merely noise but individual-specific features with functional significance.
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