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Noise during Rest Enables the Exploration of the Brains Dynamic Repertoire

机译:休息时发出的噪音使人们能够探索大脑的动态库

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摘要

Traditionally brain function is studied through measuring physiological responses in controlled sensory, motor, and cognitive paradigms. However, even at rest, in the absence of overt goal-directed behavior, collections of cortical regions consistently show temporally coherent activity. In humans, these resting state networks have been shown to greatly overlap with functional architectures present during consciously directed activity, which motivates the interpretation of rest activity as day dreaming, free association, stream of consciousness, and inner rehearsal. In monkeys, it has been shown though that similar coherent fluctuations are present during deep anesthesia when there is no consciousness. Here, we show that comparable resting state networks emerge from a stability analysis of the network dynamics using biologically realistic primate brain connectivity, although anatomical information alone does not identify the network. We specifically demonstrate that noise and time delays via propagation along connecting fibres are essential for the emergence of the coherent fluctuations of the default network. The spatiotemporal network dynamics evolves on multiple temporal scales and displays the intermittent neuroelectric oscillations in the fast frequency regimes, 1–100 Hz, commonly observed in electroencephalographic and magnetoencephalographic recordings, as well as the hemodynamic oscillations in the ultraslow regimes, <0.1 Hz, observed in functional magnetic resonance imaging. The combination of anatomical structure and time delays creates a space–time structure in which the neural noise enables the brain to explore various functional configurations representing its dynamic repertoire.
机译:传统上,大脑功能是通过在受控的感觉,运动和认知范式中测量生理反应来研究的。然而,即使在静止状态下,在没有明显的目标导向行为的情况下,皮层区域的集合也始终显示出时间上连贯的活动。在人类中,这些静止状态网络已显示出与有意识的定向活动中存在的功能体系结构有很大的重叠,从而促使人们将静止活动解释为白日梦,自由联想,意识流和内心排练。在猴子中,尽管没有意识,在深度麻醉过程中也会出现类似的连贯波动。在这里,我们显示了可比的静止状态网络,是通过使用生物学上逼真的灵长类动物大脑连通性对网络动力学进行稳定性分析而得出的,尽管仅解剖学信息不能识别该网络。我们特别证明,通过沿连接光纤传播的噪声和时间延迟对于默认网络相干波动的出现至关重要。时空网络动力学在多个时间尺度上演化,并显示在脑电图和脑磁图记录中通常观察到的频率为1–100 Hz的快速频率状态下的间歇性神经电振荡,以及在超慢状态下的<0.1 Hz的血液动力学振荡。在功能磁共振成像中。解剖结构和时间延迟的组合创建了一个时空结构,其中神经噪声使大脑能够探索代表其动态库的各种功能配置。

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