首页> 美国卫生研究院文献>Frontiers in Human Neuroscience >Resting State Connectivity Between Medial Temporal Lobe Regions and Intrinsic Cortical Networks Predicts Performance in a Path Integration Task
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Resting State Connectivity Between Medial Temporal Lobe Regions and Intrinsic Cortical Networks Predicts Performance in a Path Integration Task

机译:内侧颞叶区域与内在皮层网络之间的静止状态连通性预测路径整合任务中的性能。

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摘要

Humans differ in their individual navigational performance, in part because successful navigation relies on several diverse abilities. One such navigational capability is path integration, the updating of position and orientation during movement, typically in a sparse, landmark-free environment. This study examined the relationship between path integration abilities and functional connectivity to several canonical intrinsic brain networks. Intrinsic networks within the brain reflect past inputs and communication as well as structural architecture. Individual differences in intrinsic connectivity have been observed for common networks, suggesting that these networks can inform our understanding of individual spatial abilities. Here, we examined individual differences in intrinsic connectivity using resting state magnetic resonance imaging (rsMRI). We tested path integration ability using a loop closure task, in which participants viewed a single video of movement in a circle trajectory in a sparse environment, and then indicated whether the video ended in the same location in which it started. To examine intrinsic brain networks, participants underwent a resting state scan. We found that better performance in the loop task was associated with increased connectivity during rest between the central executive network (CEN) and posterior hippocampus, parahippocampal cortex (PHC) and entorhinal cortex. We also found that connectivity between PHC and the default mode network (DMN) during rest was associated with better loop closure performance. The results indicate that interactions between medial temporal lobe (MTL) regions and intrinsic networks that involve prefrontal cortex (PFC) are important for path integration and navigation.
机译:人类的个人导航性能有所不同,部分原因是成功的导航取决于多种不同的能力。一种这样的导航功能是路径集成,通常在稀疏,无地标的环境中移动期间更新位置和方向。这项研究检查了路径整合能力与几个典型内在大脑网络的功能连通性之间的关系。大脑中的内在网络反映了过去的输入和交流以及结构体系。对于常见的网络,已经观察到内在连通性的个体差异,这表明这些网络可以帮助我们理解个体的空间能力。在这里,我们使用静止状态磁共振成像(rsMRI)检查了固有连接的个体差异。我们使用循环闭合任务测试了路径集成能力,其中,参与者在稀疏环境中观看了沿圆周轨迹运动的单个视频,然后指出该视频是否在开始的同一位置结束。为了检查内在的大脑网络,参与者进行了静息状态扫描。我们发现,在循环任务中更好的表现与中央执行网络(CEN)和海马后部,海马旁皮质(PHC)和内嗅皮层之间的休息期间连通性增加有关。我们还发现,在休息期间PHC和默认模式网络(DMN)之间的连接与更好的闭环性能有关。结果表明,内侧颞叶(MTL)区域和涉及前额叶皮层(PFC)的内在网络之间的相互作用对于路径整合和导航很重要。

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