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Ongoing Activity in Temporally Coherent Networks Predicts Intra-Subject Fluctuation of Response Time to Sporadic Executive Control Demands

机译:临时相干网络中正在进行的活动可预测对零星执行控制要求的响应时间在受试者内部的波动

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摘要

Can ongoing fMRI BOLD signals predict fluctuations in swiftness of a person’s response to sporadic cognitive demands? This is an important issue because it clarifies whether intrinsic brain dynamics, for which spatio-temporal patterns are expressed as temporally coherent networks (TCNs), have effects not only on sensory or motor processes, but also on cognitive processes. Predictivity has been affirmed, although to a limited extent. Expecting a predictive effect on executive performance for a wider range of TCNs constituting the cingulo-opercular, fronto-parietal, and default mode networks, we conducted an fMRI study using a version of the color–word Stroop task that was specifically designed to put a higher load on executive control, with the aim of making its fluctuations more detectable. We explored the relationships between the fluctuations in ongoing pre-trial activity in TCNs and the task response time (RT). The results revealed the existence of TCNs in which fluctuations in activity several seconds before the onset of the trial predicted RT fluctuations for the subsequent trial. These TCNs were distributed in the cingulo-opercular and fronto-parietal networks, as well as in perceptual and motor networks. Our results suggest that intrinsic brain dynamics in these networks constitute “cognitive readiness,” which plays an active role especially in situations where information for anticipatory attention control is unavailable. Fluctuations in these networks lead to fluctuations in executive control performance.
机译:持续进行的fMRI BOLD信号能否预测一个人对零星的认知需求做出反应的敏捷性波动?这是一个重要的问题,因为它阐明了将时空模式表示为时间相干网络(TCN)的内在大脑动力学是否不仅对感觉或运动过程产生影响,而且对认知过程产生影响。尽管在一定程度上可以肯定预测性。预期对构成扣带-舌状,额顶和默认模式网络的更广泛的TCN的执行性能会有预测性影响,我们进行了功能磁共振成像研究,使用了专门设计的颜色-单词Stroop任务版本。更高的执行控制负担,目的是使其波动更易于检测。我们探讨了TCN中正在进行的审前活动的波动与任务响应时间(RT)之间的关系。结果揭示了TCN的存在,其中在试验开始前几秒钟的活性波动预测了后续试验的RT波动。这些TCN分布在扣带-耳膜和额顶网络中,以及知觉和运动网络中。我们的研究结果表明,这些网络中固有的大脑动力学构成了“认知准备状态”,尤其是在无法获得预期注意力控制信息的情况下,它发挥着积极作用。这些网络的波动导致执行控制性能的波动。

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