论文标题
混合效应光谱矢量自回旋模型：应用于大脑连接性
Mixed Effects Spectral Vector Autoregressive Model: With Application to Brain Connectivity
论文作者
论文摘要
本文的主要目标是开发一种量化一个大脑区域活动如何解释另一个区域中的活动的方法。在这里，我们提出了混合效应光谱载体 - 自动回旋（ME-Specvar）模型，以研究健康儿童与被诊断为ADHD的人之间脑网络依赖动力学的差异。具体而言，ME-Specvar模型将用于正式测试使用Delta，Theta，Alpha，Beta和Gamma频率带中过滤的EEG信号获得的显着连通性结构。建议的模型允许一阶段的程序来得出共同组结构中的Granger因果关系，并在不同频率振荡下特定的随机效应变化。该模型揭示了新的结果，并显示了所有频段，尤其是对照组的慢波中的更显着连接。相比之下，患有多动症的儿童具有随机效应的连通性和可变性降低的模式。结果与先前关于ADHD儿童前后连通性降低的发现是一致的。此外，新颖的发现是，健康儿童中最多样化的特定有效连通性参数属于枕骨区域，与有意识的视觉关注有关。
The primary goal of this paper is to develop a method that quantifies how activity in one brain region can explain future activity in another region. Here, we propose the mixed effects spectral vector-autoregressive (ME-SpecVar) model to investigate differences in dynamics of dependence in a brain network between healthy children and those who are diagnosed with ADHD. Specifically, ME-SpecVar model will be used to formally test for significant connectivity structure obtained using filtered EEG signals in delta, theta, alpha, beta, and gamma frequency bands. The suggested model allows one-stage procedure for deriving Granger causality in common group structure and variation of subject specific random effects in different frequency oscillations. The model revealed novel results and showed more significant connections in all frequency bands and especially in slow waves in control group. In contrast, children with ADHD shared a pattern of diminished connectivity and variability of random effects. The results are consistent with previous findings about decreased anterior-posterior connectivity in children with ADHD. Moreover, the novel finding is that the most diverse subject specific effective connectivity parameters in healthy children belong to parietal-occipital region that is associated with conscious visual attention.
