Abstract：
OBJECTIVE: Measures of functional connectivity (FC) can elucidate which cortical regions work together in order to complete a variety of behavioral tasks. This study\'s primary objective was to expand a previously published model of measuring FC to include multiple subjects and several regions of interest. While FC has been more extensively investigated in vision and other sensorimotor tasks, it is not as well understood in audition. The secondary objective of this study was to investigate how auditory regions are functionally connected to other cortical regions when attention is directed to different distinct auditory stimuli.
Approach. This study implements a linear dynamic system (LDS) to measure the structured time-lagged dependence across several cortical regions in order to estimate their FC during a dual-stream auditory attention task.
Results. The model\'s output shows consistent functionally connected regions across different listening conditions, indicative of an auditory attention network that engages regardless of endogenous switching of attention or different auditory cues being attended.
Significance. The LDS implemented in this study implements a multivariate autoregression to infer FC across cortical regions during an auditory attention task. This study shows how a first-order autoregressive function can reliably measure functional connectivity from M/EEG data. Additionally, the study shows how auditory regions engage with the supramodal attention network outlined in the visual attention literature.
摘要：
目的：功能连通性（FC）的度量可以阐明哪些皮质区域协同工作以完成各种行为任务。这项研究的主要目的是扩大以前发表的测量FC的模型，以包括多个受试者和几个感兴趣的区域。虽然FC在视觉和其他感觉运动任务中得到了更广泛的研究，这在试镜中没有得到很好的理解。这项研究的次要目的是研究当注意力针对不同的听觉刺激时，听觉区域如何在功能上与其他皮质区域相连。
方法。这项研究实现了一个线性动态系统（LDS）来测量多个皮层区域的结构化时滞依赖性，以便在双流听觉注意力任务中估计其FC。
结果。模型的输出显示了在不同的监听条件下功能上一致的连接区域，指示听觉注意力网络，该网络参与而不管注意力的内源性切换或被关注的不同听觉线索。
意义。本研究中实施的LDS实施了多变量自回归，以在听觉注意力任务期间推断皮层区域的FC。这项研究显示了一阶自回归函数如何可靠地从M/EEG数据中测量功能连通性。此外,该研究显示了听觉区域如何与视觉注意力文献中概述的超模式注意力网络互动。
