Amplitude differences in high-frequency fMRI signals between eyes open and eyes closed resting states

Abstract

Recent studies employing rapid sampling techniques have demonstrated that the resting state fMRI (rs-fMRI) signal exhibits synchronized activities at frequencies much higher than the conventional frequency range (<0.1 Hz). However, little work has investigated the changes in the high-frequency fluctuations between different resting states. Here, we acquired rs-fMRI data at a high sampling rate (TR = 400 ms) from subjects with both eyes open (EO) and eyes closed (EC), and compared the amplitude of fluctuation (AF) between EO and EC for both the low- and high-frequency components. In addition to robust AF differences in the conventional low frequency band (<0.1 Hz) in visual cortex, primary auditory cortex and primary sensorimotor cortex (PSMC), we also detected high-frequency (primarily in 0.1–0.35 Hz) differences. The high-frequency results without covariates regression exhibited noisy patterns. For the data with nuisance covariates regression, we found a significant and reproducible reduction in high-frequency AF between EO and EC in the bilateral PSMC and the supplementary motor area (SMA), and an increase in high-frequency AF in the left middle occipital gyrus (MOG). Furthermore, we investigated the effect of sampling rate by down-sampling the data to effective TR = 2 s. Briefly, by using the rapid sampling rate, we were able to detect more regions with significant differences while identifying fewer artifactual differences in the high-frequency bands as compared to the down-sampled dataset. We concluded that (1) high-frequency fluctuations of rs-fMRI signals can be modulated by different resting states and thus may be of physiological importance; and (2) the regression of covariates and the use of fast sampling rates are superior for revealing high-frequency differences in rs-fMRI signals.

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

“…In addition, we observed higher long-term reliability of CBF-ALFF in the lateral prefrontal cortex in the EO state, which might be induced by larger inter-subject difference in neuronal activity or by artifacts resulting from eye movement such as blinks. An shown in a previous study, the amplitude of high-frequency (N 0.1 Hz) fluctuation in the lateral prefrontal cortex was higher in the EO state (Yuan et al, 2014). The temporal resolution of CBF time series was restricted to the low-frequency range (b0.1 Hz).…”

“…Taglizucchi and colleagues showed that instructing subjects to keep their eyes open with/without fixation during the experiment resulted in a decreased amount of sleep than eyes closed (Tagliazucchi and Laufs, 2014 It would be relatively difficult to ask patients to maintain their gaze on a fixation for quite a few minutes. As did in some previous studies (Liu et al, 2013;Yang et al, 2007;Yuan et al, 2014;Zou et al, 2009;Zou et al, 2015), the current study also only focused on the comparisons of the eyes closed state and eyes open without fixation state and hopefully this study would be more helpful to clinical studies. Future comprehensive test-retest reliability studies including EC and EO with/without fixation are warranted.…”

“…For example, there was a trend that short-term ICC of BOLD-ALFF in EO was lower in the motor and auditory cortices than in EC; these regions were frequently reported to feature lower BOLD-ALFF in EO than EC, where EO and EC data were acquired within an hour (Liu et al, 2013;Yuan et al, 2014). However, for the long-term observation, reliability of BOLD-ALFF in the motor areas was changed to be higher in EO, consistent with the findings in the visual system.…”

“…It was observed almost one century ago by Berger (Berger, 1929(Berger, , 1930) that the EEG alpha rhythm disappeared when the eyes were open, as compared to the case when the eyes were closed. BOLD fMRI studies have shown brain activity differences between the EO and EC states in the visual cortex (Jao et al, 2013;Liu et al, 2013;Yang et al, 2007;Zou et al, 2009;Zou et al, 2015), motor and auditory cortices (Jao et al, 2013;Liu et al, 2013;Yuan et al, 2014;Zou et al, 2015), and the default mode network (Jao et al, 2013;Liu et al, 2013;Yan et al, 2009). Using the ASL technique, significant CBF increases in the primary and secondary visual areas (Brodmann area (BA) 17, 18) for EO compared with EC state (Hermes et al, 2007;Zou et al, 2015) have been reported.…”

The Whole-Brain “Global” Signal from Resting State fMRI as a Potential Biomarker of Quantitative State Changes in Glucose Metabolism

“…However, unlike this study, those studies were interested in local differences so justifiably discarded the mean of each R-fMRI metric with each conditions through performing statistical parametric mapping using the general linear model (Bianciardi et al, 2009;Brandt, 2006;Gonzalez-Hernandez et al, 2005;Marx et al, 2004;Qin et al, 2012;Riedl et al, 2014;Wicker et al, 2003), performing global signal regression to find local significance (Xu et al, 2014;Yuan et al, 2014;Zou et al, 2009), or using paired T-tests on a per voxel basis (which can hypothetically detect a global change if region-to-region variation is small, but will not necessarily as it only compares per-voxel changes and global means are never calculated) (Patriat et al, 2013). All of these methods will amplify local region to region, voxel to voxel variation, but obscure the relations to the global change observed in FDG (Fig.…”