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Linking visual gamma to task-related brain networks-a simultaneous EEG-fMRI study

机译:将视觉伽马与任务相关的脑网络 - 同时eeg-fmri学习联系起来

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There is a growing interest in human gamma-band oscillatory activity due to its direct link to neuronal populations, its associations with many cognitive processes, and its positive relationship with fMRI BOLD signal. Visual gamma has been successfully detected using concurrent EEG-fMRI recordings and linked to activity in the visual cortex using voxel-wise regression analysis. As gamma-band oscillations reflect predominantly feedforward projections between brain regions, its inclusion in functional connectivity analysis is highly recommended; however, very few studies have investigated this line of research. In the current study, we aimed to explore this gap by asking which fMRI brain network is related to gamma activity induced by the color discrimination task. Advanced denoising strategies and multitaper spectral decomposition were applied to EEG data to detect gamma oscillations, and group independent component analysis was performed on fMRI data to identify task-related neural networks. Despite using only trials without motor response (50% of the trials), the two neural measures were successfully coupled. One of the six task-related networks, the occipito-parietal network, exhibited significant trial-by-trial covariations with gamma oscillations. In addition to the expected extrastriate visual cortex, the network encompasses extensive brain activations in the precuneus, bilateral intraparietal, and anterior insular cortices. We argue that the visual cortex is the source of gamma, whereas the remaining brain regions exhibit feedforward and feedback connections related to this oscillatory activity. Our findings provide evidence for the electrophysiological basis of the connectivity revealed by BOLD signal and impart novel insights into the neural mechanism of color discrimination.
机译:由于其与神经元群体的直接链接,其与许多认知过程的关联以及与FMRI粗体信号的正相关关系,对人类伽马带宽振荡活动产生了日益增长的兴趣。使用并发EEG-FMRI录制成功检测到Visual Gamma,并使用Voxel-Wise回归分析与Visual Cortex中的活动相关联。由于伽马带振荡反映了大脑区域之间主要的前馈投影,强烈建议使用其在功能连接分析中;然而,很少有研究已经调查了这一研究线。在目前的研究中,我们旨在通过询问哪个FMRI脑网络与由颜色辨别任务引起的伽马活动相关的爆裂来探讨这种差距。先进的去噪策略和多兆谱分解应用于EEG数据以检测伽马振荡,并对FMRI数据进行组独立分量分析,以识别与任务相关的神经网络。尽管仅使用没有运动响应的试验(50%的试验),但两种神经措施成功耦合。六个任务相关的网络之一,咽题间网络,呈现出与伽马振荡的显着试验协变量。除了预期的套管视觉皮层外,网络还包括前守止的大脑激活,双侧内侧和前缘脑皮。我们认为Visual Cortex是伽玛的来源,而剩余的脑区域表现出与该振荡活动相关的前馈和反馈连接。我们的研究结果提供了粗体信号显示的连接性的电生理学基础,并将新颖的洞察力赋予色彩辨别的神经机制。

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