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神经元爆发在清醒到深度睡眠期间存在差异——来自人类颅内深度记录的证据。

Neuronal avalanches differ from wakefulness to deep sleep--evidence from intracranial depth recordings in humans.

机构信息

Department of Neural Systems and Coding, Max Planck Institute for Brain Research, Frankfurt, Germany.

出版信息

PLoS Comput Biol. 2013;9(3):e1002985. doi: 10.1371/journal.pcbi.1002985. Epub 2013 Mar 21.

Abstract

Neuronal activity differs between wakefulness and sleep states. In contrast, an attractor state, called self-organized critical (SOC), was proposed to govern brain dynamics because it allows for optimal information coding. But is the human brain SOC for each vigilance state despite the variations in neuronal dynamics? We characterized neuronal avalanches--spatiotemporal waves of enhanced activity--from dense intracranial depth recordings in humans. We showed that avalanche distributions closely follow a power law--the hallmark feature of SOC--for each vigilance state. However, avalanches clearly differ with vigilance states: slow wave sleep (SWS) shows large avalanches, wakefulness intermediate, and rapid eye movement (REM) sleep small ones. Our SOC model, together with the data, suggested first that the differences are mediated by global but tiny changes in synaptic strength, and second, that the changes with vigilance states reflect small deviations from criticality to the subcritical regime, implying that the human brain does not operate at criticality proper but close to SOC. Independent of criticality, the analysis confirms that SWS shows increased correlations between cortical areas, and reveals that REM sleep shows more fragmented cortical dynamics.

摘要

神经元活动在觉醒和睡眠状态之间存在差异。相比之下,有人提出了一种吸引子状态,称为自组织临界(SOC),它可以控制大脑的动力学,因为它允许对信息进行最佳编码。但是,尽管神经元动力学存在差异,人类大脑在每个警觉状态下是否都处于 SOC 状态?我们从人类的密集颅内深度记录中对神经元爆发进行了特征描述,神经元爆发是增强活动的时空波。我们发现,对于每个警觉状态,爆发分布都非常接近幂律分布——SOC 的标志性特征。然而,爆发明显因警觉状态而异:慢波睡眠(SWS)的爆发较大,觉醒时中等,快速眼动(REM)睡眠的爆发较小。我们的 SOC 模型与数据一起表明,首先,差异是由突触强度的全局但微小变化介导的,其次,与警觉状态的变化反映了从临界到亚临界状态的微小偏差,这意味着人类大脑并非处于适当的临界状态,而是接近 SOC。无论是否处于临界状态,该分析都证实了 SWS 会增加皮质区域之间的相关性,并揭示了 REM 睡眠的皮质动力学更加碎片化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3405/3605058/26bd5cb946ac/pcbi.1002985.g001.jpg

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