Sato Wataru, Kochiyama Takanori, Uono Shota, Usui Naotaka, Kondo Akihiko, Matsuda Kazumi, Usui Keiko, Toichi Motomi, Inoue Yushi
Kokoro Research Center, Kyoto University;
Brain Activity Imaging Center, Advanced Telecommunications Research Institute International.
J Vis Exp. 2018 Oct 30(140). doi: 10.3791/58187.
Measuring neural activity and connectivity associated with cognitive functions at high spatial and temporal resolutions is an important goal in cognitive neuroscience. Intracranial electroencephalography (EEG) can directly record electrical neural activity and has the unique potential to accomplish this goal. Traditionally, averaging analysis has been applied to analyze intracranial EEG data; however, several new techniques are available for depicting neural activity and intra- and inter-regional connectivity. Here, we introduce two analytical protocols we recently applied to analyze intracranial EEG data using the Statistical Parametric Mapping (SPM) software: time-frequency SPM analysis for neural activity and dynamic causal modeling of induced responses for intra- and inter-regional connectivity. We report our analysis of intracranial EEG data during the observation of faces as representative results. The results revealed that the inferior occipital gyrus (IOG) showed gamma-band activity at very early stages (110 ms) in response to faces, and both the IOG and amygdala showed rapid intra- and inter-regional connectivity using various types of oscillations. These analytical protocols have the potential to identify the neural mechanisms underlying cognitive functions with high spatial and temporal profiles.
在高空间和时间分辨率下测量与认知功能相关的神经活动和连通性是认知神经科学的一个重要目标。颅内脑电图（EEG）可以直接记录神经电活动，并且具有实现这一目标的独特潜力。传统上，平均分析已被用于分析颅内EEG数据；然而，现在有几种新技术可用于描绘神经活动以及区域内和区域间的连通性。在这里，我们介绍两种我们最近应用统计参数映射（SPM）软件来分析颅内EEG数据的分析方案：用于神经活动的时频SPM分析以及用于区域内和区域间连通性的诱发反应的动态因果建模。我们报告我们对面部观察期间颅内EEG数据的分析作为代表性结果。结果显示，枕下回（IOG）在非常早期阶段（110毫秒）就对面部刺激表现出伽马波段活动，并且IOG和杏仁核都利用各种类型的振荡表现出快速的区域内和区域间连通性。这些分析方案有潜力以高空间和时间分辨率识别认知功能背后的神经机制。
