Suppr超能文献

通过切换采样间隔功能磁共振成像扫描将生理极低频波动与混叠分离。

Separation of physiological very low frequency fluctuation from aliasing by switched sampling interval fMRI scans.

作者信息

Kiviniemi Vesa, Ruohonen Jyrki, Tervonen Osmo

机构信息

Department of Diagnostic Radiology, University of Oulu, OYS 90029, Finland.

出版信息

Magn Reson Imaging. 2005 Jan;23(1):41-6. doi: 10.1016/j.mri.2004.09.005.

Abstract

Anesthetized children have dominant blood-oxygen-level-dependent (BOLD) signal sources presenting high-power fluctuations at very low frequencies (VLF <0.05 Hz). Aliasing of frequencies higher than critically sampled has been regarded as one probable origin of the VLF fluctuations. Aliased signal frequencies change when the sampling rate of the data is altered. In this study, the aliasing of VLF BOLD signal fluctuation was analysed by switching the repetition time (TR) of magnetic resonance (MR) images. Eleven anesthetized children were imaged at 1.5 T using TRs of 500 and 1200 ms. The BOLD signal sources were separated with independent component analysis (ICA). Occipital cortex signal sources had nonaliased VLF fluctuation ( approximately 0.03 Hz) in 9 of 11 subjects. Arterial signal sources failed to present stable power peaks at frequencies lower than 0.42 Hz presumably due to aliasing. Cerebrospinal fluid (CSF)-related signal sources showed nonaliased VLF in four subjects. In conclusion, the VLF BOLD signal fluctuation in the occipital cortex is a true physiological fluctuation, not a result of signal aliasing.

摘要

麻醉状态下的儿童具有占主导地位的血氧水平依赖(BOLD)信号源,在极低频(VLF<0.05Hz)时呈现高功率波动。高于临界采样频率的频率混叠被认为是VLF波动的一个可能来源。当数据采样率改变时,混叠信号频率会发生变化。在本研究中,通过切换磁共振(MR)图像的重复时间(TR)来分析VLF BOLD信号波动的混叠情况。11名麻醉状态下的儿童在1.5T磁场下成像,使用的TR分别为500和1200ms。采用独立成分分析(ICA)分离BOLD信号源。11名受试者中有9名的枕叶皮质信号源具有非混叠的VLF波动(约0.03Hz)。动脉信号源在低于0.42Hz的频率下未能呈现稳定的功率峰值,可能是由于混叠所致。脑脊液(CSF)相关信号源在4名受试者中显示出非混叠的VLF。总之,枕叶皮质中的VLF BOLD信号波动是一种真正的生理波动,而非信号混叠的结果。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验