Obrig et al. used near infrared spectroscopy to show that hypercapnia also attenuates spontaneous fluctuations in cerebral oxygenation in awake humans. In general, the prior studies suggest that vasodilation reduces the amplitude of spontaneous fluctuations, while vasoconstriction tends to increase fluctuations.Similar to task-related studies, the results of these resting-state studies suggest that the strength of neurovascular coupling between spontaneous neural activity and hemodynamic fluctuations is inversely related to baseline CBF. Furthermore, a restingstate fMRI experiment found that hypercapnia decreased BOLD connectivity measured in the motor cortex in addition to reducing low-frequency BOLD fluctuations . A number of animal studies have found that mild levels of hypercapnia do not affect neural activity . Jones et al. used optical imaging spectroscopy, laser Doppler flowmetry, and multi-channel electrophysiology to measure the hemodynamic and neural responses to whisker stimulation in rats anesthetized with urethane. They found that 5% CO2 did not significantly alter the cerebral metabolic rate of oxygen responses or the EEG responses. In another study with spontaneously breathing isoflurane anesthetized rats, Sicard et al. showed that both baseline CMRO2 levels and CMRO2 increases with forepaw stimulation were not significantly changed by 5% CO2. Zappe et al. found a trend toward hypercapnia reduced spontaneous neural activity as measured with intracortical recordings in the visual cortex of remifentanil anesthetized macaque monkeys,flood and drain hydroponics but it was not significant at 3% CO2 . These findings suggest that a decrease in BOLD connectivity caused by hypercapnia most likely reflects a reduction in the strength of neurovascular coupling, as opposed to an alteration in neural activity.
Therefore, factors that change baseline CBF may be significant confounds in resting-state fMRI studies, as a decrease in BOLD connectivity due to a reduction in the strength of neurovascular coupling might be incorrectly interpreted as a decrease in neural connectivity. An improved understanding of the effects that vascular changes produce on BOLD connectivity is especially important for clinical populations where disease and medication may alter both neural connectivity and neurovascular coupling. In this study, we examined the effect of a 200 mg caffeine dose on resting-state BOLD measures in the motor cortex. Caffeine is a commonly used neural and metabolic stimulant that readily binds to adenosine receptors, thereby competitively inhibiting adenosine activation and decreasing baseline CBF . As prior work with task-related BOLD fMRI suggests that caffeine may increase the sensitivity of the BOLD signal to stimulated neural activity, we hypothesized that caffeine would also increase the sensitivity of BOLD fluctuations to spontaneous neural activity and therefore produce an increase in resting-state BOLD connectivity. Eleven healthy volunteers participated in this study after providing informed consent. After exclusion of data from 2 subjects due to excessive motion , the sample consisted of 9 subjects . Participants were instructed to refrain from ingesting caffeine for at least 12 hours prior to being scanned. The estimated daily caffeine usage for each subject based on self-reports of coffee, tea, and soda consumption is presented in Table 2.1. The assumed caffeine contents for an 8-oz cup of coffee, an 8-oz cup of tea, and a 12-oz soda were 100 mg, 40 mg, and 20 mg respectively . Each subject participated in two imaging sessions: a caffeine session and a control session, in that order. The two imaging sessions were separated by at least 6 weeks. The caffeine session consisted of a pre-dose and a post-dose imaging section, each lasting around 45 minutes each.
Upon completion of the pre-dose section, participants ingested a 200 mg caffeine pill and then rested for approximately 30 minutes outside of the magnet before starting the post-dose section. This procedure is similar to our previous protocols using caffeine . The first resting-state scan of the post-dose section began approximately 45 minutes after the caffeine pill was ingested to achieve approximately 99% absorption of caffeine from the gastrointestinal tract . Control sessions used the same protocol, but without the administration of caffeine between sections, similar to the protocol used in . Subjects were not given a placebo during the control session. However, for convenience, we will still refer to the two scan sections as the “pre-dose” and “post-dose” sections, even though a dose was not administered. Each scan section consisted of a high-resolution anatomical scan, a bi-lateral finger tapping block design, CBF baseline and quantification scans, and two five-minute resting-state BOLD scans. Bilateral finger tapping was self-paced and the block design run consisted of 20s rest followed by 5 cycles of 30s tapping and 30s resting. Subjects were instructed to tap while a flashing checkerboard was displayed and then to rest during the display of a control image, consisting of a white square situated in the middle of a gray background. During resting-state scans, the control image was displayed for the entirety of the scan and subjects were asked to maintain attention on the white square.Imaging data were collected on a GE Signa 3 Tesla whole body system with an eight channel receive coil. Laser alignment was used to landmark subjects and minimize differences in head position between pre-dose and post-dose sections. Functional data were collected over six oblique 6-mm thick slices prescribed through the primary motor cortex. The finger tapping scan and a CBF baseline scan were acquired with a PICORE QUIPSS II arterial spin labeling sequence with dual echo spiral readout .
The two resting-state BOLD scans were acquired using BOLD-weighted imaging with spiral readout . Additional CBF quantification scans were acquired using the same in-plane parameters as the functional scans, but the number of slices was increased to ensure coverage of the lateral ventricles. These scans included a cerebrospinal fluid reference scan consisting of a single-echo, single repetition sequence , and a minimum contrast scan . The high-resolution anatomical scan was acquired with a magnetization prepared 3D fast spoiled gradient sequence . Cardiac pulse and respiratory effort data were monitored using a pulse oximeter and a respiratory effort transducer , respectively. The pulse oximeter was placed on the subject’s index finger, and the respiratory effort belt was placed around the subject’s abdomen. The pulse oximeter was not worn during the bilateral finger tapping scan. Physiological data were sampled at 40 samples per second using a multichannel data acquisition board . Images from each scan section were co-registered using AFNI software . In addition, the anatomical volume from each post-dose section was aligned to the anatomical volume of its respective pre-dose section, and the rotation and shift matrix used for this alignment was then applied to the post-dose functional images. The outer two slices of the functional data were discarded to minimize partial volume effects associated with the rotation of the post-dose data, and the first 10s of each functional run were not included. In addition,indoor vertical farming voxels from the edge of the brain were not included in the analysis in order to minimize the effects of motion. The second echo data from the finger tapping scans were used to generate BOLD activation maps of the motor cortex. This was accomplished using a general linear model approach for the analysis of ASL data . The stimulus-related regressor was produced by the convolution of the square wave stimulus pattern with a gamma density function . Constant and linear trends were included in the GLM as nuisance regressors. In addition, the data were pre-whitened using an autoregressive model of order 1 . The statistical maps were based on the square root of the F-statistic, which is equal to the t-statistic in the case of one nuisance term . Active voxels were defined using a method based on activation mapping as a percentage of local excitation . In summary, the √ F maps were separated into left and right hemispheric regions. The highest value in each region was identified and then every voxel was converted to a percentage of the peak statistical value for the region ×100. Active voxels were required to exceed an AMPLE value of 45% and a √ F value of 2 . The final activation maps were defined from the intersection of voxels active in both pre-dose and post-dose scan sections. Regions of interest were then defined for the left and right motor cortices from these activation maps. Thus, the same ROIs were used in the comparison of pre-dose and post-dose functional connectivity within an imaging session. Baseline CBF images were calculated from the average difference between the tag and control images in the CBF baseline scan. The mean ASL images were corrected for coil sensitivity and B1 field in homogeneities with the minimum contrast scan , and converted to physiological units, ml/, using the CSF reference scan . Average baseline CBF values were extracted from each subject’s motor cortex, defined as the union of the right and left motor ROIs.
The time series data from the BOLD resting-state runs were used to generate measures of resting-state functional connectivity. First, nuisance parameters were removed from the raw data through linear regression. These regressors included constant and linear trends, physiological noise terms from the measured cardiac and respiratory signals , and six motion parameters obtained during image coregistration. Data were then temporally low-pass filtered using a finite impulse response function with a cutoff frequency of 0.08 Hz. This cutoff frequency was chosen for consistency with previous functional connectivity studies . The average signal from either the left ROI or the right ROI was used to define a reference time course. This reference time course was then correlated with all other voxel time series within the brain to generate a functional connectivity map. The correlation coefficients in these maps were converted to z scores in a method similar to that used by Fox et al. . For a qualitative presentation of functional connectivity changes, average z score maps for the pre-dose and post-dose sections were calculated for each subject by averaging across the two resting-state runs and thresholding at z = 2.58 . Voxels were required to have at least 2 nearest neighbors for inclusion in the resting-state connectivity maps. Two metrics were used to quantitatively assess the strength of resting-state functional connectivity in the motor cortex. For the first metric, the mean z score was extracted from either the right or left ROI , where the average signal from the opposite ROI was used as a reference time course. The second metric, referred to as the percent overlap, was first used by Biswal etal. , and is described in more detail in these references. To summarize, the quantity ¯nLR/nL is the percent of voxels in the left ROI that are significantly correlated with all voxel time courses from the right ROI , where the subscripts R and L refer to right and left, respectively. In this method, ¯nLR/nL provides a measurement of connectivity between hemispheres, with ¯nLR/nL necessarily equal to ¯nRL/nR. These quantities, ¯nLL/nL and ¯nRR/nR , represent the percent of voxels in the left and right ROIs, respectively, that are significantly correlated with all other voxel time series from within the respective ROIs. Two-tailed paired t-tests were performed between the pre-dose and post-dose results to assess changes in these metrics of functional connectivity. In addition, a repeated measures two-way analysis of variance was performed for each metric . Also, the correlation coefficient threshold used in the percent overlap method was varied between 0.24 and 0.42 in increments of 0.02 to assess the robustness of this measurement. For frequency domain analysis, power spectra were calculated from the preprocessed resting-state data using a minimum 4-term Blackman-Harris window. Average power spectra were extracted from the motor cortex in the pre-dose and post-dose sections for each subject. A quantitative measurement of energy in the low-frequency BOLD fluctuations was calculated as the sum of the average power below 0.08 Hz. Paired t tests were performed to assess changes in energy between the pre-dose and post-dose sections. Additional processing steps were taken to determine whether changes in resting-state functional connectivity might be due to changes in low-frequency respiration variations. This was accomplished by adding an extra regressor to the original nuisance matrix. The additional term was either the global signal or the respiration volume per time signal . In order to minimize bias that can be introduced when motor cortex fluctuations are included in the regression , the global signal was extracted from the anterior portion of the brain in the four slices that were analyzed.