The oscillating brain: Complex and reliable

Abstract

The human brain is a complex dynamic system capable of generating a multitude of oscillatory waves in support of brain function. Using fMRI, we examined the amplitude of spontaneous low-frequency oscillations (LFO) observed in the human resting brain and the test-retest reliability of relevant amplitude measures. We confirmed prior reports that gray matter exhibits higher LFO amplitude than white matter. Within gray matter, the largest amplitudes appeared along mid-brain structures associated with the “default-mode” network. Additionally, we found that high amplitude LFO activity in specific brain regions was reliable across time. Further, parcellation-based results revealed significant and highly reliable ranking orders of LFO amplitudes among anatomical parcellation units. Detailed examination of individual low frequency bands showed distinct spatial profiles. Intriguingly, LFO amplitudes in the slow-4 (0.027 - 0.073 Hz) band as defined by Buzsáki et al. were most robust in the basal ganglia, as has been found in spontaneous electrophysiological recordings in the awake rat. These results suggest that amplitude measures of LFO can contribute to further between-group characterization of existing and future “resting-state” fMRI datasets.

Reliability comparison of spontaneous brain activities between BOLD and CBF contrasts in eyes-open and eyes-closed resting states

“…We calculated voxel-wise BOLD-ALFF over a frequency range of 0.01-0.083 Hz. The BOLD-ALFF maps were standardized by normalization with the mean BOLD-ALFF of the entire brain voxels (Zou et al, 2008;Zuo et al, 2010a). Prior to FC analysis, the residual BOLD time series were band-pass filtered (0.01-0.083 Hz) and a 10-mm diameter spherical seed located in the posterior cingulate cortex (PCC) was selected (Van Dijk et al, 2012;Yan et al, 2013b).…”

“…We calculated the Pearson's correlation coefficient between the seed time series and every other voxel in the brain and transformed the correlation coefficient values into z values using Fisher's r-to-z transformation. To evaluate the effect of data denoising, we calculated BOLD-ALFF with standard preprocessing, i.e., with neither ICA denoising nor regression of covariates of no interest (Zou et al, 2008;Zuo et al, 2010a); and BOLD-FC with standard preprocessing, i.e., without ICA denoising but with regression of covariates of no interest (Patriat et al, 2013).…”

“…Thus they are of crucial importance to evaluate the test-retest reliability of brain activity measures (Hodkinson et al, 2013;Jahng et al, 2005;Jann et al, 2014;Kublbock et al, 2014;Patriat et al, 2013;Shehzad et al, 2009;Zhu et al, 2014;Zuo et al, 2010aZuo et al, ,b,c, 2013Zuo and Xing, 2014). Resting-state fMRI, including blood oxygenation level dependent (BOLD) and arterial spin labeling (ASL), has become a powerful tool in mapping human brain functions (Biswal et al, 2010;Smith et al, 2013).…”

“…Resting-state fMRI, including blood oxygenation level dependent (BOLD) and arterial spin labeling (ASL), has become a powerful tool in mapping human brain functions (Biswal et al, 2010;Smith et al, 2013). Previous investigations on test-retest reliability of spontaneous BOLD signal oscillations (Kublbock et al, 2014;Zuo et al, 2010a) showed that regions with high reliability were mainly located in the gray matter. Similar results were observed by separate studies investigating test-retest reliability of average CBF (Hodkinson et al, 2013;Jahng et al, 2005;Jann et al, 2015).…”

Detailed view on slow sinusoidal, hemodynamic oscillations on the human brain cortex by Fourier transforming oxy/deoxy hyperspectral images

“…Instead of applying a relatively wide bandpass filter, where all oscillations are aggregated (Bumstead et al, 2016; Gratton et al, 1998; Zuo et al, 2010), or only looking at only one frequency of 0.1 Hz (Rayshubskiy et al, 2014), a more detailed view on a SSHO can be acquired using a very small bandwidth ( $\Delta f$ around 0.002 Hz) as with a Fourier transform. In this way, it becomes clear that different but also overlapping SSHO‐regions can be observed with slightly different SSHO frequencies.…”