Brain Spontaneous Functional Connectivity above Conventional 0.1 Hz
Abstract： Our brain circuits are always active, even when we simply rest quietly, devoid of systematic thinking. There exist persistent levels of background activities that account for the major energy cost of our cerebral metabolism.
Our brain circuits are always active, even when we simply rest quietly, devoid of systematic thinking. There exist persistent levels of background activities that account for the major energy cost of our cerebral metabolism. With functional Magnetic Resonance Imaging (fMRI), researchers have observed that, during resting state (RS, or the task-free state), these spontaneous activities are organized into different functional networks, typically characterized by slow fluctuations - lower than 0.1 Hz [1,2].
With faster sampling rates permitted by recent advances in MR techniques, there is emerging evidence that these spontaneous activities persist in higher frequency bands [3,4], even up to 1 Hz and beyond. Linking the speculation that resting state functional connectivity (RSFC) below 0.1 Hz is confounded by the maintenance of basic hemodynamic stasis controlled by the parasympathetic nerve system, it is thus possible that the higher frequency FC can offer a more direct and precise characterization of neural metabolism. However, fMRI is based on Blood Oxygen-Level Dependent (BOLD) contrast, which is an indirect measure of neural activity resulting from hemodynamic response to up-regulated metabolism increases. As a result, BOLD signals are inherently smoothed by a sluggish hemodynamic process that at first glance would not permit observations of signals above ~0.3 Hz. It is therefore of great interest to query whether the reported higher-frequency signals derive from a different mechanism than BOLD contrasts, and whether such signals constitute a more fundamental representation of neural processes.
Based on the fact that the BOLD contrast should be linearly dependent on echo time (TE) due to R2 (transverse relaxation rate) decay , we collected RS data at multiple TEs to examine the TE-dependence of RSFC across different frequency bands. We observed persisted levels of BOLD-like signals up to 0.5 Hz (the highest frequency can be resolved by repetition time 1s), suggesting that the conventional BOLD hemodynamic model must be modified to describe the elevated higher frequency components of the resting brain. We further heuristically proposed a new RS model that predicts an inherently faster response. More importantly, we demonstrated that the existence of an as yet un-identified non-BOLD-like mechanism whose contribution to the overall observed signal surprisingly increases as frequency increases. This work has recently been published in NeuroImage .
Given the fast growing interest in higher frequency RSFC, it is of fundamental importance to query whether the observed spontaneous activities have a neural origin. To identify the non-BOLD-like components, candidate neural-related mechanisms such as blood inflow 7 and signal enhancement by extravascular water protons 8 should be examined in future studies. If the non-BOLD-like component indeed reflects neural metabolisms, ensuing questions include what is the functional specificity, or functional signal to noise ratio associated with the new mechanism; how to integrate information from richer spectrum bands (more fundamentally distinct mechanisms) to obtain a synthetic understanding of brain activity, etc.
Collectively, further endeavors are needed to illuminate the nature of these previously unsuspected high frequency fluctuations, and how they can inform our observations of cognitive behavior with greater precision than conventionally observed.
 Biswal, B., Yetkin, F.Z., Haughton, V.M., Hyde, J.S., 1995. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 34, 537-541.
 Raichle, M.E., 2011. The restless brain. Brain Connect 1, 3-12.
 Lee, H.L., Zahneisen, B., Hugger, T., LeVan, P., Hennig, J., 2013. Tracking dynamic resting-state networks at higher frequencies using MR-encephalography. NeuroImage 65, 216-222.
 Gohel, S.R., Biswal, B.B., 2014. Functional Integration Between Brain Regions at Rest Occurs in Multiple-Frequency Bands. Brain Connect.
 Kundu, P., Inati, S.J., Evans, J.W., Luh, W.M., Bandettini, P.A., 2012. Differentiating BOLD and non-BOLD signals in fMRI time series using multi-echo EPI. NeuroImage 60, 1759-1770.
 Chen JE, Glover GH., 2015. BOLD Fractional Contribution to Resting-state Functional Connectivity above 0.1 Hz." NeuroImage 107:207-218.
 Gao, J.H., Liu, H.L., 2012. Inflow effects on functional MRI. NeuroImage 62, 1035-1039.
 Figley, C.R., Leitch, J.K., Stroman, P.W., 2010. In contrast to BOLD: signal enhancement by extravascular water protons as an alternative mechanism of endogenous fMRI signal change. Magn Reson Imaging 28, 1234-1243.
Jingyuan E. Chen
She received her B.S. in Biomedical Engineering from Tsinghua University in 2011, where she worked with Dr. Karen Ying and embarked the wonderful journey of fMRI research. Upon graduation, she continued to pursue a Ph.D degree in Electrical Engineering at Stanford University, under the supervision of Dr. Gary Glover and Dr. Michael Greicius. She is interested in the modeling and analysis of the brain’s spontaneous activities. Her PhD work mainly focuses on: (1) investigating the temporospatial behaviors and biophysics of resting state functional connectivity above conventional 0.1 Hz; (2) developing quantification metrics to facilitate routine analysis of static and dynamic aspects of brain spontaneous activity based on the recently proposed point process idea.