Early Development of Spatial Patterns of Power-Law Frequency Scaling in fMRI Resting-State and EEG Data in the Newborn Brain

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.