Wang Ting, Wilkes D Mitchell, Li Muwei, Wu Xi, Gore John C, Ding Zhaohua
Department of Computer Science, Chengdu University of Information Technology, Chengdu, Sichuan 610225, China.
Department of Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN 37232, USA.
Cereb Cortex Commun. 2020;1(1):tgaa056. doi: 10.1093/texcom/tgaa056. Epub 2020 Aug 28.
The hemodynamic response function (HRF) characterizes temporal variations of blood oxygenation level-dependent (BOLD) signals. Although a variety of HRF models have been proposed for gray matter responses to functional demands, few studies have investigated HRF profiles in white matter particularly under resting conditions. In the present work we quantified the nature of the HRFs that are embedded in resting state BOLD signals in white matter, and which modulate the temporal fluctuations of baseline signals. We demonstrate that resting state HRFs in white matter could be derived by referencing to intrinsic avalanches in gray matter activities, and the derived white matter HRFs had reduced peak amplitudes and delayed peak times as compared with those in gray matter. Distributions of the time delays and correlation profiles in white matter depend on gray matter activities as well as white matter tract distributions, indicating that resting state BOLD signals in white matter encode neural activities associated with those of gray matter. This is the first investigation of derivations and characterizations of resting state HRFs in white matter and their relations to gray matter activities. Findings from this work have important implications for analysis of BOLD signals in the brain.
血流动力学响应函数(HRF)表征了血氧水平依赖(BOLD)信号的时间变化。尽管已经提出了多种用于灰质对功能需求响应的HRF模型,但很少有研究探讨白质中的HRF特征,特别是在静息状态下。在本研究中,我们量化了嵌入白质静息态BOLD信号中的HRF的性质,以及其对基线信号时间波动的调节作用。我们证明,白质静息态HRF可以通过参考灰质活动中的内在雪崩来推导,并且与灰质中的HRF相比,推导得到的白质HRF具有降低的峰值幅度和延迟的峰值时间。白质中时间延迟和相关性分布取决于灰质活动以及白质束的分布,这表明白质静息态BOLD信号编码了与灰质相关的神经活动。这是对白质静息态HRF的推导、特征及其与灰质活动关系的首次研究。本研究结果对大脑BOLD信号分析具有重要意义。