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首页> 外文期刊>Neuron >Decoding Wakefulness Levels from Typical fMRI Resting-State Data Reveals Reliable Drifts between Wakefulness and Sleep
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Decoding Wakefulness Levels from Typical fMRI Resting-State Data Reveals Reliable Drifts between Wakefulness and Sleep

机译：从典型的功能磁共振成像静息状态数据解码觉醒水平揭示了觉醒与睡眠之间的可靠漂移

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The mining of huge databases of resting-state brain activity recordings represents state of the art in the assessment of endogenous neuronal activity-and may be a promising tool in the search for functional biomarkers. However, the resting state is an uncontrolled condition and its heterogeneity is neither sufficiently understood nor accounted for. We test the hypothesis that subjects exhibit unstable wakefulness, i.e., drift into sleep during typical resting-state experiments. Analyzing 1,147 resting-state functional magnetic resonance data sets, we revealed a reliable loss of wakefulness in a third of subjects within 3min and demonstrated the dynamic nature of the resting state, with fundamental changes in the associated functional neuroanatomy. Implications include the necessity of wakefulness monitoring and modeling, taking measures to maintain a state of wakefulness, acknowledging the possibility of sleep and exploring its consequences, and especially the critical assessment of possible false-positive or false-negative results.
机译：庞大的静止状态脑活动记录数据库的挖掘代表了内源性神经元活动评估的最新技术，并且可能是寻找功能性生物标志物的有前途的工具。但是，静止状态是不受控制的状态，其异质性既未被充分理解，也无法得到解释。我们测试了这样的假设，即受试者表现出不稳定的清醒状态，即在典型的静息状态实验中进入睡眠状态。分析了1,147个静止状态功能磁共振数据集，我们揭示了3分钟内三分之一受试者的可靠觉醒丧失，并证明了静止状态的动态性质以及相关功能神经解剖学的根本变化。这意味着需要进行唤醒监测和建模，采取措施保持唤醒状态，承认睡眠的可能性并探讨其后果，尤其是对可能的假阳性或假阴性结果进行严格评估。

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