基于奇异谱分析的BOLD自发振荡提取与同步

D. Menicucci, A. Gemignani, Andrea Piarulli, R. Bedini, C. Gentili, G. Handjaras, S. Danti, M. Guazzelli, M. Laurino, P. Piaggi, A. Landi
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引用次数: 0

摘要

自发性脑血氧水平依赖性(BOLD)波动引起了神经生理学界的兴趣。这些振荡在低频范围内表现突出,具有时空相关性。从一个健康个体,通过收集4个切片进行基础静息状态BOLD fMRI采集。考虑了来自七个选定区域的体素信号。我们假设了嵌入在“红噪声”中的振荡的复合零假设。为了从BOLD信号中提取振荡,我们应用了蒙特卡罗奇异谱分析(SSA)。在0.085-0.13Hz的低频范围内,也实现了振荡元件的相位同步。结果表明,噪声参数和体素之间的连接数的区域依赖分布都很明显。尽管对总体样本的进一步研究应证实结果的一致性,但结合相位同步分析的SSA技术似乎是提取低频BOLD自发振荡并发现大脑区域之间功能联系的可行方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extraction and Synchronization of BOLD Spontaneous Oscillations Using Singular Spectrum Analysis
Spontaneous cerebral blood oxygenation level-dependent (BOLD) fluctuations are gaining interest in the neurophysiology community. These oscillations are prominent in the low-frequency range with spatiotemporal correlations. From a healthy individual, a basal resting state BOLD fMRI acquisition has been performed by collecting 4 slices. Voxel signals from seven selected regions have been considered. We assumed a composite null-hypothesis of oscillations embedded in “red noise”. To extract oscillations from BOLD signals we applied the Monte Carlo Singular Spectrum Analysis (SSA). Phase-synchronization of the oscillatory components, in the low-frequency range 0.085-0.13Hz, have been also achieved. As results, region-dependent distributions were apparent both for the noise parameters and for the number of connections between voxels. Although further studies on population samples should confirm the result consistency, the SSA technique combined with a phase-synchronization analysis seems a feasible method to extract low frequency BOLD spontaneous oscillations and to find functional connections among cerebral areas.
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