The dashed lines represent linear fits where subjects marked in blue were excluded from the calculation

The amplitudes of BOLD and CBF percent signal changes, both during rest and task, were calculated as root mean square values by computing the standard deviation across the length of the time courses. Note that for the task-related BOLD and CBF signals, only the last 3 cycles were used in this calculation. As CBF signal changes can be overestimated due to low SNR in ASL CBF data, we removed voxels containing RMS %∆CBF outliers from all analyses. Outliers were de- fined as values lying more than 1.5 times the interquartile range above the third quartile or below the first quartile of all RMS %∆CBF values . Average values for RMS %∆BOLD and RMS %∆CBF were calculated for each subject by first averaging the time courses in the motor cortex ROIs and then calculating RMS values. For comparison with previous research , the evoked BOLD and CBF response amplitudes to finger tapping were also calculated using a GLM analysis on the average %∆BOLD and %∆CBF time courses in the motor cortex. Instead of computing RMS values, task amplitudes were computed as the weights of the stimulus related regressor, which was described in the ROI Definition section. Resting-state BOLD data were also used to measure functional connectivity strength between the right and left motor cortices for each subject. This was done by correlating the average BOLD time course from the left motor ROI with the average BOLD time course from the right motor ROI for a measure of BOLD connectivity. Relationships between BOLD and CBF measures were examined across subjects using correlation analysis.

Linear fits were also computed for each relationship,vertical grow rack and the slopes were compared between the task and rest conditions using an ANCOVA.Relationships between BOLD amplitude and baseline CBF are shown during task and rest in Figure 4.1a. Similar to a previous study using a visual stimulus , we find that the BOLD response to finger tapping displays a significant negative correlation with baseline CBF. In contrast, while the resting BOLD fluctuation amplitude exhibits a trend of inverse dependence on baseline CBF, it is not significant . Furthermore, the linear fit for the finger-tapping data has a significantly steeper slope than for the resting-state data = 9.8, p = 0.004. We did not find a significant relationship between resting-state BOLD connectivity and baseline CBF , however we did find resting-state BOLD connectivity and amplitude measures to be correlated across subjects . Note that the inverse dependence of task-related BOLD signal changes on baseline values of CBF was also found using the GLM-based task amplitudes instead of RMS values . Preliminary work suggests that the inverse dependence of the task BOLD am-plitude on baseline CBF is caused by the direct dependence of %∆BOLD on %∆CBF, which is modeled in the Davis equation . This is because %∆CBF is inversely related to baseline CBF, as CBF0 is the denominator in calculating %∆CBF. Empirically determining the dependence of %∆BOLD on %∆CBF during rest can be challenging because of the inherently low signal to noise ratio in ASL. This can be seen in Figure 4.2, which plots the correlation coefficients between the average motor cortex BOLD and CBF time courses during task and rest. The correlation values are visibly much higher during the task condition, where the solid line represent equality between the two states, reflecting the larger SNR during task than rest.

In Figure 4.2 data points shown in blue represent subjects with insignificant < 0.16, p > 0.05 correlation values during resting state. We explore the relationships between RMS %∆BOLD and RMS %∆CBF during finger tapping and rest in Figure 4.3a, where again subjects with insignificant correlations between their BOLD and CBF time courses are marked in blue. In this plot, lines represent linear fits to the data and correlation values are shown. To investigate the cause of the shallower slope during resting state shown in , we plotted absolute RMS CBF verses baseline CBF in units of ml/ in Figure 4.4a, where solid lines represent linear fits to the data. The absolute CBF fluctuations are independent of baseline CBF during task and rest . In addition, when we compared the slopes of the linear fits to flat lines intersecting the RMS CBF means for task and rest we did not find a significant difference < 0.76, p > 0.39. Note that the mean of the RMS CBF values during task is significantly larger than the mean during rest = 12.2, p = 1.6e-9. The independence of the absolute RMS CBF values on baseline CBF and the significantly smaller mean RMS CBF value during resting state explain the weakened dependence of relative changes in CBF on baseline CBF. To show this, the experimental values of RMS %∆CBF are plotted versus CBF0 in Figure 4.4b. In this plot, solid lines represent simulated RMS %∆CBF assuming a constant absolute RMS CBF of 20.5 for task and 8.4 for rest. These simulated lines closely follow the excursions of measured RMS %∆CBF across the range of baseline CBF, with the simulated task line displaying a visibly steeper slope. To further explore the weakened dependence between RMS %∆BOLD and RMS %∆CBF during resting state , the ratio of RMS %∆BOLD to RMS %∆CBF was determined and plotted in Figure 4.5a for each subject during the rest and task conditions. The solid line represents equality between the two states. A significantly higher BOLD to CBF ratio was found during task than rest = 8.5, p = 2e-7 across all subjects, and also across only those subjects with significant BOLD-CBF correlations shown as black data points = 7.2, p = 2e-5.

Considering the dependence of %∆BOLD on %∆CBF as modeled in Eq. 4.1, we note that the parameter M is not expected to change substantially between task and rest because M depends on experimental parameters and baseline physiology. The experimental parameters are identical for the two scans, while the subject’s baseline physiology is not expected to significantly change between the task and rest scans, which are acquired right next to each other in the scan session. However, a difference in the CBF-CMRO2 coupling factor n could exist between the task and rest conditions, and would give rise to the observed differences in the BOLD to CBF relationship. Estimates of n for each subject are shown for both task and rest in Figure 4.5b, with M assumed to be previously determined 7.2% . We found n to be significantly higher during task = 8.4, p = 3e-7. This result was insensitive to our selection of M, which we varied from 3.4% to 12% in increments of 0.2% < 10.2, 0.03 > p > 2e-8. When only subjects with significant BOLD-CBF correlations were considered, we found that n remains significantly higher during task for M equal to 4.2% and higher < 8.3, 5e-6 < p < 0.01. Using M = 7.2% and the mean n values from Figure 4.5b , we used the Davis model to compute RMS %∆BOLD values and compared those to the measured RMS %∆BOLD values . It can be seen that the smaller n during rest makes the BOLD signal less sensitive to CBF changes. Dashed lines represent model estimates using mean n values calculated from subjects with significant BOLD-CBF correlations. The results presented in this paper are from the two dual-echo ASL/BOLD scans,cannabis grow racks but we also compared the resting-state BOLD measures acquired from the second echo of the resting-state ASL/BOLD scans with those acquired during the single-echo BOLD weighted imaging scans. The same processing methods were applied to the data from the two single-echo BOLD-weighted resting-state scans, with the exception that running average filtering was not applied. Values of RMS %∆BOLD and functional connectivity strength were then averaged across the two runs. We found that RMS %∆BOLD values measured using the dual-echo ASL/BOLD and single-echo BOLD-weighted scans were significantly correlated across subjects . Furthermore, use of the single-echo BOLD-weighted imaging data in place of the dual-echo ASL/BOLD data did not change our overall conclusions. Resting-state fMRI is frequently used to measure patterns of spontaneous neural activity in the brain. However, the BOLD signal provides only an indirect measure of neural activity and is a complex function of blood flow and oxygenation changes.

In this study, we find that inter-subject differences in the amplitude of the BOLD response to finger tapping demonstrate an inverse dependence on baseline CBF, in agreement with previous findings . This suggests that hemodynamic differences between subjects may need to be taken into account when comparing task-related evoked BOLD responses. In contrast, the amplitudes of spontaneous BOLD fluctuations were not significantly related to inter-subject differences in CBF. This reduced dependence appears to be caused by a combination of two factors. The first, and perhaps most dominant, is that percent changes in CBF displayed a weaker inverse dependence on baseline CBF during rest than task, where the BOLD signal is directly linked to relative CBF changes as modeled in the Davis equation . The lower sensitivity of %∆CBF changes on CBF0 is due to the significantly smaller amplitudes of absolute CBF fluctuations during the resting state. As we found absolute CBF fluctuations to be independent of baseline CBF during both finger tapping and rest, dividing the smaller absolute fluctuations by baseline CBF led to a shallower slope between relative changes in CBF and baseline CBF. The independence of absolute functional CBF changes on baseline CBF during visual stimulation has been previously reported , and is consistent with an additive model of functional CBF changes, which are constant for a given stimulus regardless of baseline blood flow. Absolute changes in CBF are presumably smaller during rest because this state is less demanding in terms of energy cost, so a smaller amount of oxygen needs to be delivered to the motor cortex. In addition,as flow-metabolism coupling appears to be tightened during rest, smaller fluctuations in CBF may still accompany fairly large fluctuations in oxygen consumption. The second factor leading to reduced sensitivity of the resting BOLD signal to baseline CBF is the weakened relationship between %∆BOLD and %∆CBF, which seems to be caused by tighter flow-metabolism coupling in the motor cortex during rest. The ratio of the relative changes in CBF and CMRO2 has previously been shown to vary across brain region . In addition, differences in n were found within the visual cortex depending on the subjects’ state of attention . Recent studies have shown that flow-metabolism coupling increases with greater visual stimulus contrast and frequency suggesting that n is modulated by task difficulty. Our results in the motor cortex are consistent with this finding, using the assumption that the resting state represents the lowest level of task difficulty. In contrast to our findings, a previous study did not find significant differences in the BOLD/CBF ratio between rest and a visual task . A potential source of this discrepancy is the use of non-quantitative CBF measures in the prior study. It should be noted that the difference in flow-metabolism coupling observed between task and rest was for a sensorimotor task that elicited a robust task-related response. We expect that similar differences in coupling will also be observed for other paradigms and brain regions with robust task-related responses . However, we expect that there will not be a significant difference in the coupling observed during task and rest conditions for cognitive paradigms and brain regions with relatively weak task-related responses, such as memory-encoding responses in the medial temporal lobe . For these paradigms, the coupling between flow and metabolism is already tighter as compared to the coupling observed in the visual and motor regions . The reason for the tighter coupling is not yet known, but may reflect a difference between brain regions that have adapted to primarily process inputs from the external world versus those that have developed to process intrinsic information from other brain regions. We expect that the tighter coupling for task-related responses in brain regions that handle intrinsic information will also reduce the dependence of the task-related BOLD signal on baseline CBF for paradigms that activate these areas. Further work is needed to test these conjectures. The results of this study suggest that inter-subject differences in resting-state functional connectivity are relatively insensitive to variations in CBF. In a preliminary study, we previously reported that BOLD connectivity strength and baseline CBF were negatively correlated .