Wu Changwei W, Gu Hong, Lu Hanbing, Stein Elliot A, Chen Jyh-Horng, Yang Yihong
Neuroimaging Research Branch, National Institute on Drug Abuse, NIH, Baltimore, MD 21224, USA.
Neuroimage. 2009 Apr 15;45(3):694-701. doi: 10.1016/j.neuroimage.2008.12.066.
Synchronized low-frequency fluctuations in the resting state functional MRI (fMRI) signal have been suggested to be associated with functional connectivity in brain networks. However, the underlying mechanism of this connectivity is still poorly understood, with the synchronized fluctuations could either originate from hemodynamic oscillations or represent true neuronal signaling. To better interpret the resting signal, in the current work, we examined spontaneous fluctuations at the level of cerebral metabolic rate of oxygenation (CMRO2), an index reflecting regional oxygen consumption and metabolism, and thus less sensitive to vascular dynamics. The CMRO2 signal was obtained based on a biophysical model with data acquired from simultaneous blood oxygenation level dependent (BOLD) and perfusion signals. CMRO2-based functional connectivity maps were generated in three brain networks: visual, default-mode, and hippocampus. Experiments were performed on twelve healthy participants during 'resting state' and as a comparison, with a visual task. CMRO2 signals in each of the above mentioned brain networks showed significant correlations. Functional connectivity maps from the CMRO2 signal are, in general, similar to those from BOLD and perfusion. In addition, we demonstrated that the three parameters (M, alpha and beta) in the biophysical model for calculating CMRO2 have negligible effects on the determination of the CMRO2-based connectivity strength. This study provides evidence that the spontaneous fluctuations in fMRI at rest likely originate from dynamic changes of cerebral metabolism reflecting neuronal activity.
静息态功能磁共振成像(fMRI)信号中的同步低频波动被认为与脑网络中的功能连接有关。然而,这种连接的潜在机制仍知之甚少,同步波动可能源于血液动力学振荡,也可能代表真正的神经元信号。为了更好地解释静息信号,在当前工作中,我们研究了脑氧代谢率(CMRO2)水平的自发波动,CMRO2是反映局部氧消耗和代谢的指标,因此对血管动力学不太敏感。CMRO2信号是基于一个生物物理模型获得的,该模型的数据来自同时采集的血氧水平依赖(BOLD)信号和灌注信号。在三个脑网络中生成了基于CMRO2的功能连接图:视觉网络、默认模式网络和海马体。对12名健康参与者在“静息态”期间进行了实验,并作为对照,进行了一项视觉任务。上述每个脑网络中的CMRO2信号都显示出显著的相关性。基于CMRO2信号的功能连接图总体上与基于BOLD信号和灌注信号的功能连接图相似。此外,我们证明了用于计算CMRO2的生物物理模型中的三个参数(M、α和β)对基于CMRO2的连接强度的测定影响可忽略不计。这项研究提供了证据,表明静息时fMRI中的自发波动可能源于反映神经元活动的脑代谢动态变化。