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Changes of Effective Connectivity in the Alpha Band Characterize Differential Processing of Audiovisual Information in Cross-Modal Selective Attention.
Neuroscience Bulletin ( IF 5.9 ) Pub Date : 2020-07-26 , DOI: 10.1007/s12264-020-00550-2
Weikun Niu 1, 2, 3 , Yuying Jiang 1, 2, 3 , Xin Zhang 1, 2 , Tianzi Jiang 1, 2, 3, 4 , Yujin Zhang 1, 2 , Shan Yu 1, 2, 3, 4
Affiliation  

Cross-modal selective attention enhances the processing of sensory inputs that are most relevant to the task at hand. Such differential processing could be mediated by a swift network reconfiguration on the macroscopic level, but this remains a poorly understood process. To tackle this issue, we used a behavioral paradigm to introduce a shift of selective attention between the visual and auditory domains, and recorded scalp electroencephalographic signals from eight healthy participants. The changes in effective connectivity caused by the cross-modal attentional shift were delineated by analyzing spectral Granger Causality (GC), a metric of frequency-specific effective connectivity. Using data-driven methods of pattern-classification and feature-analysis, we found that a change in the α band (12 Hz–15 Hz) of GC is a stable feature across different individuals that can be used to decode the attentional shift. Specifically, auditory attention induces more pronounced information flow in the α band, especially from the parietal–occipital areas to the temporal–parietal areas, compared to the case of visual attention, reflecting a reconfiguration of interaction in the macroscopic brain network accompanying different processing. Our results support the role of α oscillation in organizing the information flow across spatially-separated brain areas and, thereby, mediating cross-modal selective attention.

中文翻译:

Alpha 波段中有效连接的变化表征了跨模式选择性注意中视听信息的差异处理。

跨模式选择性注意增强了与手头任务最相关的感官输入的处理。这种差异化处理可以通过宏观层面上的快速网络重构来调节,但这仍然是一个知之甚少的过程。为了解决这个问题,我们使用行为范式在视觉和听觉域之间引入选择性注意力的转移,并记录了来自八名健康参与者的头皮脑电图信号。通过分析频谱格兰杰因果关系 (GC) 来描述由跨模式注意力转移引起的有效连通性的变化,GC 是一种频率特定的有效连通性指标。使用数据驱动的模式分类和特征分析方法,我们发现 GC 的 α 波段(12 Hz–15 Hz)的变化是不同个体之间的稳定特征,可用于解码注意力转移。具体而言,与视觉注意的情况相比,听觉注意在 α 波段引起更明显的信息流,尤其是从顶叶 - 枕叶区到颞顶叶区,反映了伴随不同处理的宏观大脑网络中交互的重新配置。我们的结果支持 α 振荡在组织跨空间分离的大脑区域的信息流中的作用,从而介导跨模式选择性注意。尤其是从顶叶-枕叶区域到颞-顶叶区域,与视觉注意的情况相比,反映了伴随不同处理的宏观大脑网络中相互作用的重新配置。我们的结果支持 α 振荡在组织跨空间分离的大脑区域的信息流中的作用,从而介导跨模式选择性注意。尤其是从顶叶-枕叶区域到颞-顶叶区域,与视觉注意的情况相比,反映了伴随不同处理的宏观大脑网络中相互作用的重新配置。我们的结果支持 α 振荡在组织跨空间分离的大脑区域的信息流中的作用,从而介导跨模式选择性注意。
更新日期:2020-07-26
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