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Altered Regional Brain Communities during High Order Cognitive Processes: Relation to Vigilance Decrement

机译:在高阶认知过程中改变了区域大脑社区:与警惕下降有关

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Understanding modular organization between brain regions can provide deeper insight into the complex neural mechanisms associated with processes like vigilance decrement. Distinct but interacting modules in brain connectivity networks have been known to support integration of specific mechanisms relevant in high-order cognitive processes. To investigate the neuronal mechanisms associated with vigilance decrement, we conducted an experiment where the participants performed a driving task. EEG graph metrics within communities, like clustering coefficient (Cintra), efficiency (Eintra), density (Dintra), and between communities, like intermodule density (Dinter), were computed from the source-localized surface brain signals. Further, we also calculated the nodal out degree to investigate the difference in information flow in the brain during vigilance decrement. Increase in the intermodule density, Dinter, was observed from the left fronto-parietal cluster to the right temporo-parietal cluster. Moreover, significant reduction in the intramodule metrics, Eintra and Cintra was observed in the right temporo- parietal cluster. Thus, our findings signify a flexible topographical architecture to compensate the hub disruption effect caused due to decline in vigilance.
机译:了解脑区之间的模块化组织可以深入了解与维护减少的过程相关的复杂神经机制。已知脑连接网络中的独特但​​交互模块支持集成在高阶认知过程中相关的特定机制。为了调查与警惕减少相关的神经元机制,我们进行了一个实验,参与者进行了驾驶任务。社区内的eeg图表度量,如聚类系数(c Intra ),效率(e Intra ),密度(d Intra ),并且社区之间,如间断密度(d Inter ),从源局部化的表面脑信号计算。此外,我们还计算了探讨了在警惕减少期间大脑中信息流量的差异的节点。增加细胞间密度,d Inter ,从左前景簇观察到正确的临时簇。此外,血内内度量的显着减少了 Intra 和C. Intra 在右侧簇中观察到。因此,我们的研究结果表示灵活的地形架构,以补偿由于警惕下降导致的集线器中断效应。

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