Department of Health Sciences, Università degli Studi di Milano, Italy; Sleep Center, Neurocenter of Southern Switzerland, Regional Civic Hospital of Lugano, Switzerland; University of Southern Switzerland, Lugano, Switzerland.
Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy.
Schizophr Res. 2020 Jul;221:37-43. doi: 10.1016/j.schres.2020.03.025. Epub 2020 Mar 24.
Abnormal sleep oscillations have recently been proposed as endophenotypes of schizophrenia. However, optimization of methodological approaches is still necessary to standardize analyses of their microstructural characteristics. Additionally, some relevant features of these oscillations remain unexplored in pathological conditions. Among others, slow wave traveling is a promising proxy for diurnal processes of brain connectivity and excitability. The study of slow oscillations propagation appears particularly relevant when schizophrenia is conceptualized as a dys-connectivity syndrome. Given the rising knowledge on the neurobiological mechanisms underlying slow wave traveling, this measure might offer substantial advantages over other approaches in investigating brain connectivity. Herein we: 1) confirm the stability of our previous findings on slow waves and sleep spindles in FDRs using different automated algorithms, and 2) report the dynamics of slow wave traveling in FDRs of Schizophrenia patients. A 256-channel, high-density EEG system was employed to record a whole night of sleep of 16 FDRs and 16 age- and gender-matched control subjects. A recently developed, open source toolbox was used for slow wave visualization and detection. Slow waves were confirmed to be significantly smaller in FDRs compared to the control group. Additionally, several traveling parameters were analyzed. Traveled distances were found to be significantly reduced in FDRs, whereas origins showed a different topographical pattern of distribution from control subjects. In contrast, local speed did not differ between groups. Overall, these results suggest that slow wave traveling might be a viable method to study pathological conditions interfering with brain connectivity.
异常睡眠振荡最近被提议为精神分裂症的内表型。然而，为了标准化分析其微观结构特征，仍需要优化方法学方法。此外，这些振荡的一些相关特征在病理条件下仍未得到探索。在其他特征中，慢波传播是大脑连通性和兴奋性的昼夜过程的一个很有前途的替代指标。当将精神分裂症概念化为连通障碍综合征时，慢波传播的研究显得尤为重要。鉴于对慢波传播的神经生物学机制的不断深入了解，与其他方法相比，该措施在研究大脑连通性方面可能具有更大的优势。在此，我们：1）使用不同的自动算法确认我们之前在 FDR 中慢波和睡眠纺锤波的发现的稳定性，2）报告精神分裂症患者 FDR 中慢波传播的动力学。使用 256 通道高密度 EEG 系统记录 16 名 FDR 和 16 名年龄和性别匹配的对照受试者的一整晚睡眠。使用最近开发的开源工具箱进行慢波可视化和检测。与对照组相比，FDR 中的慢波明显更小。此外，还分析了几个旅行参数。发现 FDR 中的旅行距离明显减小，而起源显示出与对照受试者不同的分布拓扑模式。相比之下，组间的局部速度没有差异。总的来说，这些结果表明，慢波传播可能是一种可行的方法来研究干扰大脑连通性的病理状况。
