Resting-state fMRI

Resting-state fMRI (rsfMRI) is a method of functional brain imaging that can be used to evaluate regional interactions that occur when a subject is not performing an explicit task. This resting brain activity is observed through changes in blood flow in the brain which creates what is referred to as a Blood Oxygen Level Dependent (BOLD) signal that can be measured using functional Magnetic Resonance Imaging (fMRI).

Because brain activity is present even in the absence of an externally prompted task, any brain region will have spontaneous fluctuations in BOLD signal. Resting-state functional connectivity research has revealed a number of networks which are consistently found in healthy subjects and represent specific patterns of synchronous activity. However, the mechanisms governing the temporally coherent spontaneous fluctuations in BOLD signal remain unclear. Exploration of these mechanisms is one of the research interests in BISP Lab.

One of our projects, entitled “Brain resting-state functional MRI connectivity: Morphological foundation and plasticity”, directly demonstrates that axonal connections are the indispensable foundation for rsfMRI connectivity and that such functional connectivity can be plastic and dynamically reorganized atop the morphological connections.

In this study, well-controlled models of complete and partial corpus callosotomy were examined longitudinally with rsfMRI. The figure shows functional connectivity maps from animal groups with complete, posterior partial callosotomy and sham surgery at post-surgery day 7 **(a)** and day 28 **(b)**. The color bars display z-scores, with a higher z-score representing a stronger correlation between the time courses of that region. The figure illustrates four cortical areas ranging from the anterior to posterior part of the brain, secondary somatosensory cortex (S2), primary somatosensory cortex (S1), auditory cortex (AC) and visual cortex (VC), respectively.

Another representative study investigated feasibility of passband balanced steady-state free precession (bSSFP) imaging for distortion-free and high-resolution rsfMRI.

Resting-state networks (RSNs) of human are derived from bSSFP and GE-EPI images. RSNs identified representing dorsal attention, primary motor cortex, posterior part of default mode network, occipital visual cortex (VC), medial VC, lateral VC and auditory cortex (A–G) using independent component analysis. bSSFP and GE-EPI images were acquired from the same subject with identical temporal resolution, spatial geometry and resting-state paradigm. Power spectra, converted from time courses of corresponding independent components using Fast Fourier Transform, clearly indicate low frequency dominance. Z-maps were thresholded using histogram mixture modeling at an alternative hypothesis threshold P>0.5.