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Comparing correlation between BOLD and susceptibility changes during Resting state and Task-based experiments1Centre for Functional and Metabolic Mapping, Western University, London, ON, Canada, 2Medical Biophysics, Western University, London, ON, Canada
Synopsis
Quantitative susceptibility mapping (QSM) is a technique widely used for the measurement of venous oxygen saturation levels, through local deoxyhemoglobin concentration. In this work, QSM is used to explore the relationship between magnetic susceptibility and BOLD signal changes during resting state and task based fMRI experiments, in order to better understand their cerebrovascular mechanisms. Negative correlations between susceptibility and BOLD signal were observed and evaluated for both resting state and task based experiments.
Introduction
The blood-oxygen level dependent (BOLD) effect is primarily driven by the change in local deoxyhemoglobin concentration, which depends on the combined changes of blood flow, metabolic rate and the cerebral blood volume1. However, increased neural activity tends to alter each of these physiological variables, but these changes have conflicting effects on the BOLD response1,2. Increased blood flow tends to wash out the deoxyhemoglobin, while increased metabolic rate increases local production of deoxyhemoglobin. Quantitative susceptibility mapping (QSM) allows the measurement of local venous oxygen saturation levels, through deoxyhemoglobin concentration, and can be used to understand the BOLD signal information3. In this work, we performed task-based and resting state experiments to compare the correlations between BOLD change4 and susceptibility variations (Δχ) in order to evaluate whether their underlying cerebrovascular mechanisms were consistent between these two types of fMRI experiments.Methods
Nine healthy subjects were scanned using the multiband 2D-EPI sequence5 (TE/TR=25ms/1s, 1.6mm isotropic resolution, multiband factor = 5 and 600 measurements) on a 7T MRI system (Siemens, Magnetom Step 2.3, Erlangen, Germany). The original phase images were unwrapped6 and demeaned for each time point. A second order global polynomial fit was used to reduce any remnant background components while preserving the phase from the activation region. Magnitude data were linearly motion corrected in FSL7, and further pre-processing was carried out in FMRI Expert Analysis Tool (FEAT)7. Motion correction parameters from the magnitude data were then applied to the demeaned phase. The task-based experiment was performed by using a 60-second block design of visual stimuli with a concentric checkerboard (flickering at 8Hz), presented on a grey background. Dual regression was used to generate seed-based correlation maps for both magnitude and QSM timeseries. In order to compare the visual and resting state experiments, the visual cortex was chosen as a seed region. The correlation slopes between BOLD signal and Δχ changes were calculated using weighted-least square fitting and were evaluated based on the corrected z-score8 to determine whether these correlation slopes for resting state and visual task were significantly different.Results
An example of the seed-based correlation of BOLD signal and Δχ during resting state is shown in Figure 1. The variations in BOLD and Δχ were found to be negatively correlated for the selected region, whereas the correlation networks were in agreement between the two metrics. In Figure 2, the visual cortex region was selected as a seed region, and a negative correlation between the Δχ and BOLD changes was found for both task-based and resting state experiments. The correlation slopes across all subjects for resting and visual task experiments, found to be not significantly different (|zcorr|<2), are shown in Figure 3. The most deviant data points, identified by the shaded regions in Figure 3, were located in the larger veins (diameter > 3 voxels).Discussions and Conclusion
In these preliminary results, we have observed a strong negative correlation between BOLD and Δχ in both resting state and visual task experiments. This negative correlation is in agreement with the fact that the aforementioned wash out of deoxyhemoglobin results in a decrease in the Δχ value and, consequently, an increase in T2* rate that rises the BOLD signal2. The magnitude of the rsfMRI signal was found to be comparable to the task based BOLD signal and we noticed no difference in correlation slopes of the BOLD vs. Δχ between rest and visual task results (Figure 3). This suggests that the BOLD response during task-based activities has a similar underlying cerebrovascular mechanism with the BOLD changes during rest. It is also important to note that the inclusion of the large veins introduced a non-linearity in the resting state BOLD response (Figure 3, blue shaded regions), as opposed to the smaller venules and the tissue. Hence, these large veins should be avoided in assessing functional connectivity, as their response appears to be in a non-linear regime.Acknowledgements
The authors acknowledge Trevor Szekeres for acquiring the MRI data. This work was supported by the Canadian Institutes of Health Research (CIHR) Foundation grant (FDN 148453).References
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