Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA; Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA.
Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA; Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA; Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University, New Haven, CT, USA.
Neuroimage. 2018 May 15;172:586-596. doi: 10.1016/j.neuroimage.2018.01.051. Epub 2018 Jan 31.
Fluctuations in spontaneous activity have been observed by many neuroimaging techniques, but because these resting-state changes are not evoked by stimuli, it is difficult to determine how they relate to task-evoked activations. We conducted multi-modal neuroimaging scans of the rat olfactory bulb, both with and without odor, to examine interaction between spontaneous and evoked activities. Independent component analysis of spontaneous fluctuations revealed resting-state networks, and odor-evoked changes revealed activation maps. We constructed simulated activation maps using resting-state networks that were highly correlated to evoked activation maps. Simulated activation maps derived by intrinsic optical signal (IOS), which covers the dorsal portion of the glomerular sheet, significantly differentiated one odor's evoked activation map from the other two. To test the hypothesis that spontaneous activity of the entire glomerular sheet is relevant for representing odor-evoked activations, we used functional magnetic resonance imaging (fMRI) to map the entire glomerular sheet. In contrast to the IOS results, the fMRI-derived simulated activation maps significantly differentiated all three odors' evoked activation maps. Importantly, no evoked activation maps could be significantly differentiated using simulated activation maps produced using phase-randomized resting-state networks. Given that some highly organized resting-state networks did not correlate with any odors' evoked activation maps, we posit that these resting-state networks may characterize evoked activation maps associated with odors not studied. These results emphasize that fluctuations in spontaneous activity form a foundation for active processing, signifying the relevance of resting-state mapping to functional neuroimaging.
自发活动的波动已经被许多神经影像学技术所观察到,但由于这些静息状态的变化不是由刺激引起的,因此很难确定它们与任务诱发的激活有何关系。我们对大鼠嗅球进行了多模态神经影像学扫描,既有气味也有无气味,以研究自发活动和诱发活动之间的相互作用。自发波动的独立成分分析揭示了静息状态网络,而气味诱发的变化揭示了激活图。我们使用与诱发激活图高度相关的静息状态网络构建了模拟激活图。源自固有光学信号 (IOS) 的模拟激活图,涵盖了肾小球片的背侧部分,可显著区分一种气味的诱发激活图与其他两种气味的激活图。为了测试整个肾小球片的自发活动对于代表气味诱发激活的假设,我们使用功能磁共振成像 (fMRI) 来绘制整个肾小球片的图谱。与 IOS 结果相反,fMRI 衍生的模拟激活图显著区分了所有三种气味的诱发激活图。重要的是,使用随机相位的静息状态网络产生的模拟激活图无法显著区分任何一种气味的诱发激活图。鉴于一些高度组织化的静息状态网络与任何气味的诱发激活图都没有相关性,我们假设这些静息状态网络可能描述了与未研究气味相关的诱发激活图。这些结果强调了自发活动的波动为主动处理形成了基础,表明静息状态映射对功能神经影像学的相关性。