Early Development of Spatial Patterns of Power-Law Frequency Scaling in fMRI Resting-State and EEG Data in the Newborn Brain
Early Development of Spatial Patterns of Power-Law Frequency Scaling in fMRI Resting-State and EEG Data in the Newborn Brain
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DOI：
10.1093/cercor/bhs047
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发表时间：
2013-03-01
期刊：
影响因子：
3.7
通讯作者：
Vanhatalo, Sampsa
中科院分区：
文献类型：
--
作者：
Fransson, Peter;Metsaranta, Marjo;Vanhatalo, Sampsa
最近的研究揭示了空间和功能的关系，在休息状态功能磁共振成像（rs-fMRI）或脑电图（EEG）信号记录在成人大脑的时间动态。通过用与1/f α成比例的幂律函数O（f）对静息态脑信号的频率功率谱进行建模，幂律指数α已被证明与自发脑活动的连接模式有关，自发脑活动在人类成年大脑中形成所谓的rs-fMRI网络。在这里，我们提出了一个rs-fMRI和EEG信号在新生儿和成人大脑中获得的动态特性的分析，我们证明了一个幂律的频率缩放的数量级的血液动力学（0.01-0.15 Hz）和电气（0.2-30 Hz）域。我们发现，内在的功能磁共振成像信号的幂律指数α的静息态动力学的空间隔离是密切相关的，以前划定的静息态神经元的架构，包括初级感觉皮层和相关的皮层新生儿。此外，在新生儿大脑的EEG测量中也可以观察到rs-fMRI信号的时间动态差异的空间分布，尽管是在一个较粗的空间尺度上，枕叶和顶叶皮质的幂律指数大于额叶的信号。
Recent studies have revealed spatial and functional relations in the temporal dynamics of resting-state functional magnetic resonance imaging (rs-fMRI) or electroencephalography (EEG) signals recorded in the adult brain. By modeling the frequency power spectrum of resting-state brain signals with a power-law function O(f) proportional to 1/f alpha, the power-law exponent alpha has been shown to relate to the connectivity patterns of spontaneous brain activity that forms so-called rs-fMRI networks in the human adult brain. Here, we present an analysis of the dynamic properties of rs-fMRI and EEG signals acquired both in the newborn and adult brain, and we demonstrate frequency scaling of a power-law kind for orders of magnitude in the hemodynamic (0.01-0.15 Hz) and the electrical (0.2-30 Hz) domain. We show that the spatial segregation of resting-state dynamics of intrinsic fMRI signals in terms of the power-law exponent alpha is closely related to previously delineated resting-state neuronal architecture that encompasses primary sensory cortices and associate cortex in newborns. Moreover, the spatial profiles of differences in temporal dynamics for rs-fMRI signals could also be observed in EEG measurements in the newborn brain, albeit at a coarser spatial scale, with larger power-law exponents in occipital and parietal cortices compared with signals from the frontal brain.