How does the human brain sleep: analysis of scalp-intracerebral correlates to better understand the region-specific neurophysiology of sleep

睡眠通常被认为是一种全球性的大脑现象。睡眠期间振荡活动的区域性变化尚不清楚。颅内脑电(IEEG)在癫痫术前评估中应用于少数三级中枢，为高时空分辨率的原位研究人类大脑皮层提供了独特且唯一的可能性。该程序利用这种方法来产生关于人类大脑睡眠神经生理学的区域变异性的知识，并调查大脑深层结构对睡眠活动的非侵入性信号的贡献。目标1：睡眠中标准化区域特异性iEEG活动图谱。通过在每个患者中选择位于健康大脑中的少数联系人，并积累大量患者以覆盖整个皮质，我们开创了第一个人类清醒期间正常iEEG图谱(Frauscher等人，Brain 2018)。在一个子集中，我们可以访问有睡眠的片段。最初的数据显示，iEEG在所有睡眠阶段都有尾尖频率梯度。此外，深层结构显示出与头皮脑电不同的光谱峰值。这种方法将被用于一个更雄心勃勃的项目，在所有大脑区域建立一个睡眠不同阶段和周期的图谱。目的#2：分析脑内睡眠微结构和动力学的相关性。虽然人们对睡眠纺锤体及其脑内相关性有广泛的了解(例如，Frauscher等人，NeuroImage 2015)，但关于其他睡眠特有的瞬间或睡眠动力学变化的知识很少或根本不存在。这是因为在iEEG的设置中很少执行组合睡眠记录。目标1的大数据池将能够阐明区域睡眠的微结构和动态变化。目的#3：大脑深层结构对睡眠活动的非侵入性神经生理信号的贡献。非侵入性信源定位方法的缺点是我们无法知道信源模型在什么条件下是正确的和可信的。我们提出了一种独特的方法，它将使我们能够使用非侵入性测绘程序，如高密度脑电和脑磁图，直接验证以iEEG记录的深部来源的可探测性。这将决定哪些睡眠模式可以非侵入性地研究。这一计划将(I)产生关于不同皮质区域和网络在睡眠局部调节中的不同参与的知识，(Ii)展示在睡眠振荡或睡眠动态变化时具体涉及哪些大脑区域，以及(Iii)利用非侵入性大脑标测技术确定在深层结构中可以检测到哪种类型的睡眠活动。它将增加我们对睡眠神经生理学相关性的了解，并为更好地解释大脑活动的非侵入性测量的相关性开辟新的途径。数据集将是开放访问的。

Sleep is typically considered a global brain phenomenon. Regional variations in oscillatory activity during sleep remain unknown. Intracranial electroencephalography (iEEG), as used in few tertiary centers during presurgical epilepsy evaluation, offers the unique and only possibility to study in situ the human cortex with high spatio-temporal resolution. This program exploits this method to generate knowledge on the regional variability of sleep neurophysiology in the human brain and to investigate the contribution of deep brain structures to the non-invasive signal of sleep activity. Objective #1: atlas of normative region-specific iEEG activity during sleep. We have pioneered the first human atlas of the normal iEEG during wakefulness by selecting in each patient the few contacts located in healthy brain and accumulating a large number of patients to cover the whole cortex (Frauscher et al., Brain 2018). In a subset, we had access to segments with sleep. First data show that the iEEG has a caudo-rostral frequency gradient across all sleep stages. Moreover, deep-seated structures show spectral peaks differing from the scalp EEG. This approach will be used in a more ambitious project, building an atlas during the different stages and cycles of sleep, in all brain regions. Objective #2: analysis of the intracerebral correlates of sleep microstructure and dynamics. Whereas there is extensive knowledge on sleep spindles and their intracerebral correlates (e.g. Frauscher et al., NeuroImage 2015), knowledge on other sleep-specific transients or changes in sleep dynamics are scarce or non-existing. This is because combined sleep recording is rarely performed in the set-up of iEEG. The large datapool of objective 1 will enable to elucidate regional sleep microstructural and dynamic changes. Objective #3: contribution of deep brain structures to the non-invasive neurophysiological signal of sleep activity. Non-invasive source localization methods suffer from our inability to know in what conditions a source model is correct and can be trusted. We propose a unique approach, which will enable us to validate directly, using non-invasive mapping procedures such as high-density EEG and magnetoencephalography, the detectability of deep sources as recorded with iEEG as ground truth. This will determine which sleep patterns can be studied non-invasively. This program will (i) generate knowledge on the distinct participation of various cortical regions and networks in the local regulation of sleep, (ii) demonstrate which brain regions are specifically involved at the time of sleep oscillations or changes in sleep dynamics, and (iii) establish which type of sleep activity in deep structures is detectable using non-invasive brain mapping techniques. It will increase our knowledge on neurophysiological correlates of sleep and open new avenues for better interpreting the correlates of non-invasive measures of brain activity. The dataset will be open-access.