III.1 Depth-resolved imaging of the hemodynamic response
shows depth-resolved cortical functional activation maps from one rat, acquired using LOT during electrical forepaw stimulation; shows a CCD camera image of the field of view, acquired with 570nm illumination prior to LOT imaging (the LOT field of view is identified by the dotted white square). shows horizontal LOT slices of the depth-resolved HbR, HbO2 and HbT functional changes 0.6 seconds after cessation of the stimulus (block-average of 140 stimuli). The most superficial (0 μm) slice partially samples the dura and cerebrospinal fluid and the very top of the superficial vasculature. The 200μm depth slice shows more of the pial vasculature, and contains some signal from the superficial cortex (layer I). The 600μm deep slice corresponds to deeper cortical layers (layers III–IV) and predominantly reveals changes in the capillary bed.
Depth-resolved hemodynamic imaging
show vertical slices through the 3D HbO2 data in the x-z plane. The vertical slice locations are labeled i and ii in A and B, and transect a surface draining vein and the focal capillary region respectively. The depth-resolved time courses of HbO2, HbR and HbT in these regions (along the dotted vertical lines) are also shown.
illustrates the superficial location of the draining vein. The depth-resolved time-courses for this slice show little change in the cortex below the vein. It is also interesting to note that the vein does not appear to exhibit significant HbT changes. In contrast, shows a much deeper response, corresponding to a combination of capillary bed activation and diving arterioles and venules, in addition to superficial signals from the pial vasculature. Timecourses from the layers in this slice reveal changes in HbO2
, HbR and HbT to depths of > 1400 microns. Equivalent results for a second rat are shown in the supplementary data (Fig S1)
III.2 Spatiotemporal isolation of vascular compartments
While the 3D LOT images of the vasculature can spatially resolve structures corresponding to superficial vessels and deeper capillary beds, we wish to exploit this spatial separation to examine the dynamic behavior of each vascular compartment individually.
We can readily extract the HbR, HbO2 and HbT timecourses of the voxels corresponding only to the superficial draining vein (labeled ‘v’ in ), and similarly for the deeper capillary bed region (region ‘c’). In addition, we notice that there is a 3rd distinct region, visible in the 200 micron deep HbT image. This region does not seem to exhibit a substantial HbR change, and is superficial. From comparison with the grayscale CCD images, we conclude that this region is a surface arteriole (region ‘a’ in Fib 2B). The functional timecourses from these three regions are shown in , normalized to the peak of their HbO2 response. The mean averages of similarly selected regions from 5 rats are shown in (error bounds show the standard error on the mean).
3D Spatiotemporal Separation of Vascular Compartments
There are many statistically significant differences between the evolution of HbR, HbO2
and HbT across these vascular compartments which are consistent across all 5 rats (as described in more detail below). Strong features include: 1) The delay in venous HbO2
and HbR responses relative to the arteriolar and capillary compartments, 2) the small magnitude of the venous HbT change, 3) the rapid onset and decay of the arteriolar response, and 4) the latency of the capillary post-stimulus decay. These observations are consistent with the compartment-specific onset hemodynamics in the superficial cortical vasculature of cats as reported by (Vanzetta et al., 2005
), and in rat somatosensory cortex as reported by (Li et al., 2003
; Sheth et al., 2005
) using 2D optical imaging. (Berwick et al., 2005
; Vanzetta et al., 2005
) also note small venous HbT changes.
To ensure that these timecourse differences aren’t the result of subjective selection of voxels, the process was repeated using only a simple algorithm which sought regions with common functional behavior (looking for major features such as delayed HbO2
onset, prompt decay and high amplitude changes in HbO2
, HbT and HbR). The result was a set of masks which corresponded to the voxels exhibiting this behavior, and which overlaid well with the regions selected subjectively The functional timecourses extracted using these masks were almost identical to those shown in . (These masks are shown for two rats in supplemental data, Fig S3
The extracted compartment timecourses are distinct signatures of each vascular compartment, a result of differing structural and physical properties such as smooth muscle, compliance and oxygen perfusability. Based on this, we hypothesized that each voxel in our 3D time-series of HbR, HbO2 and HbT could be represented purely as a linear combination of arteriole, capillary and vein, e.g:
where c(t) is a compartment’s functional time-course, IHbO(r,t) is the 3D HbO2 image series, and Iartle(r) is an image of the arteriolar component (Icap(r) is capillary and Ivein(r) is venous).
If we solve equation 1
using a non-negative least-square fit (Lawson and Hanson, 1974
), the result will be 3D images of the three vascular compartments involved in the functional response, based only on their characteristic temporal HbR, HbO2
and HbT dynamics. The results of this spatiotemporal separation are shown in , where each column shows image slices at different depths (compare to Fig 2B). Each image depicts regions whose functional time-courses correlate with the dynamic behavior of arterioles, capillaries and veins (from left to right).
Note the accentuation of confluent, vessel-like structures in the arteriolar and venous images, and the deeper rounded shape of the capillary compartment. These three components are also shown as 3D surface renderings (40% isosurfaces) in . Equivalent results for a second rat are shown in the supplementary data (Fig S2)
. A similar compartment-resolved result for 2D optical imaging was recently obtained with an automated spatiotemporal separation algorithm (Berwick et al., 2005
The residuals of our spatiotemporal fit are small, suggesting that much of the vasculature within a compartment indeed reacts with very similar characteristic timecourses as those shown. As detailed in supplementary data (Fig S4)
: only one region was found to be unaccounted for in this spatiotemporal fit. This region exhibited a response with negligible HbR change. When the functional timecourse of this region was incorporated into a 4 component fit, the response localized to the base of the large artery, and the residuals of the 4 component fit were uniformly small. The lack of HbR response in the main artery is consistent with a high (~98%) baseline oxygen saturation. Quantification of the residuals and singular value decomposition of the data also confirms that the main compartment timecourses are highly representative of the first three orthogonal components of the entire data set, accounting for ~85% of the total variance (see Fig S4
). We expect that the remaining variance accounts for the behaviors of transition vessels such as pre- and post-capillary arterioles and venules, as well as local subtleties of the temporal responses.
III.3 Spatial validation: comparison of compartments with 3D vascular architecture
Although the structures isolated from their dynamic behavior resemble confluent vessels, we can in fact validate whether these regions correspond to the correct vascular architecture using the ex-vivo vascular casts created following LOT data acquisition. shows a two-photon image stack of the (un-macerated) ex-vivo vascular cast of the same animal. Identification of arterial, arteriolar and venous vasculature is based on vessel smoothness, direction and connectivity. In , the superficial vascular patterns from the cast have been overlaid on the 200μm deep (pial-to-layer I) LOT slice. The capillary region identified by LOT is overlaid in green onto the vascular cast image.
These results illustrate the strong agreement between the regions identified by their dynamics and the physical vasculature, particularly for the venous compartment. For the arteriolar compartment the match to the static vessels is not exact, however this illustrates an important and useful facet of this method: Since the maps reveal regions responding with a characteristic timecourse, only those branches of the arteriolar tree that are recruited during the functional response are visible in the LOT result. The broader arterial base also does not appear owing to its differing functional response as shown in Supplemental figure S4
. We therefore conclude that the spatial distributions of the LOT compartments are indeed consistent with the 2D cortical vascular architecture.
We can also compare the depth-resolved compartment structures with the static vascular architecture. For the rats whose vascular casts were placed in KOH to macerate away soft tissue, only a very fine structure of vessels remained which could be imaged using two-photon microscopy to depths of 1mm. The resulting two-photon 3D image stack could be analyzed quantitatively to determine the microvascular density as a function of depth. The region examined corresponded to the part of the somatosensory cortex where the forepaw stimulus response was observed in-vivo.
shows the 2-photon x-z projection of the vasculature in the region indicated in the x-y stack in . shows a plot of the capillary density from the vascular cast as a function of depth. The depth profile of the capillary and venous regions identified from their 3D dynamic behavior in-vivo (using LOT) for 2 rats are overlaid. The small surface vein in the vascular cast corresponds to the shallow spike in the black trace in . The LOT venous traces (blue) represent cross sections through a much larger draining vein, which from the cast images have diameters approaching 200 microns, suggesting good agreement between the vascular cast and the LOT venous results. In addition, both capillary traces agree well with the vascular density profile, within the limits of the LOT image z-resolution. These capillary depth profiles agree well with published profiles for microvascular density in rat somatosensory cortex (Masamoto et al., 2003
Depth-resolved validation using in-vitro two-photon microscopy
Achieving spatial isolation of the capillary compartment response is strongly motivated by the hypothesis that the location and amplitude of the hemodynamic response in the capillaries will relate more closely to neuronal activation (Malonek and Grinvald, 1996
; Woolsey et al., 1996
). We have demonstrated good spatial correlation between the 3D structure of the vascular architecture and the LOT-segmented 3D vascular compartments identified only
from their dynamic behavior. This confirms that spatiotemporal separation is a potentially powerful technique for delineating the hemodynamic response into its vascular compartment distributions. The distinct differences in the venous, capillary and arteriolar responses, even if only HbR changes are considered, suggest that spatiotemporal segmentation of the functional response could provide significant improvements to other functional imaging techniques including 2D optical imaging and fMRI (Berwick et al., 2005
; Krings et al., 1999
; Yacoub et al., 2006
; Zwart et al., 2005
III.4 Summary of the temporal features of the vascular compartments
The spatial correspondence between the static vascular architecture and the compartments identified only from their dynamic timecourses strongly supports the assertion that the timecourses used for the spatiotemporal separation are indeed representative of the distinct characteristics of the vascular compartments. By examining both these timecourses and the spatial distributions of the vascular compartments involved in the hemodynamic response, we can begin to resolve how the hemodynamic response evolves and is controlled.
illustrates the key features of the average temporal responses of the vascular compartments (over 5 rats). This data is shown in closer detail and with error bounds in the supplementary data (Figs S5 and S6)
. Each plot compares timecourses normalized to their peak, to accentuate the differences in the timing of the onsets and decays of the responses. The bar graphs provide summaries of the relative onset times, amplitudes and the fractional contribution of each compartment to the overall hemodynamic response. Details on methods used for parameter extraction are provided in the supplementary data
Analysis of Vascular Compartment Time-Course Dynamics
The arteriolar response exhibits prompt onset and prompt post-stimulus decay, with a small undershoot (labeled (i) in ). This temporal pattern is seen for all hemoglobin types and closely resembles previously reported blood flow
timecourses in rat during somatosensory stimulus (Jones et al., 2001
). This relation is investigated further below. We also note that a measurable change in HbR is seen in the arteriolar compartment (53% ± 4% of arteriolar HbO2
change, p = 0.01, paired t-test, n=5), suggesting that initial hemoglobin oxygen saturation in branching arterioles is less than 98%. This is in agreement with PO2
measurements of branching arterioles in rat cortex (Vovenko, 1999
), and in hamster cheek pouch (Duling and Berne, 1970a
), and the findings of (Berwick et al., 2005
; Zheng et al., 2005
), although it is contrary to the assumption that arterioles do not contribute to the BOLD signal in fMRI (see also ).
The delayed onset of HbR and HbO2
in the veins relative to the arterioles and capillaries is an obvious feature (Δt30%
= 0.57 ± 0.22 secs, p<0.01, labeled (ii) in ). This is a well documented phenomenon caused by the time taken for changes in arterial flow to affect the oxygenation state of the venous out-flow, and is related to the capillary transit time and changes in oxygen extraction fraction. However, the HbT change in the veins (which is small: 10% ± 3% of the total HbT change, p<0.016, in agreement with (Berwick et al., 2005
) and (Vanzetta et al., 2005
)), does not exhibit a significant delay
relative to HbT changes in the arteriolar and capillary compartments (p>0.5 at 30% max, labeled (iii) in ). The small amplitude and prompt onset of HbT changes in the venous compartment are contradictory to standing basic assumptions applied to fMRI interpretation which assume that the majority of HbT and HbR changes occur in the veins and are uniformly delayed (Marota et al., 1999
). This is investigated further below.
Another notable feature is the latency of the capillary bed post-stimulus decay (labeled iv in and v in ). At 50% max post-stimulus, tcap − tvein = 0.61 ± 0.54s, p = 0.03. The capillary compartment (given by the voxels responding with capillary-like dynamics) also composes the largest fraction of the overall hemodynamic signal for all hemoglobin types, as shown in .
III.5 Temporal validation: In-vivo two-photon microscopy of vascular dynamics
In order to validate our interpretation of the dynamic timecourses from LOT, we used in-vivo two-photon microscopy to investigate the following two aspects of the hemodynamic response: 1) The possible direct correspondence between arteriolar HbT and blood flow changes, offering insights into the control mechanisms of the hemodynamic response, and as a potentially new way to infer blood flow, and 2) the mechanism of the small change in venous HbT for short (4 second) stimuli, since the general assumptions in fMRI analysis (where longer stimuli are usually considered) is that the majority of the BOLD and cerebral blood volume (CBV) changes are due to a significant dilation/ballooning of the veins (Buxton et al., 1998
; Hoge et al., 1999
; Kong et al., 2004
; Mandeville et al., 1999
; Zheng et al., 2005
For each rat, we focused our two-photon measurements on the area responding to a 4 second forepaw stimulus (defined by CCD-based HbT imaging prior to microscopy, as illustrated in ). Rapid series of 180 × 180 micron images were acquired during stimulation at 14 frames per second to simultaneously capture movies of the dynamics of both the arterioles and veins within the responding area. Each stimulus block was repeated 3 to 5 times, and up to 15 different fields of view were studied to cover the active area. Consistent results were seen in all rats studied. We present data from the animal for which the most sites within the active area were reliably and repeatedly measured. The image series were processed as described in supplementary data Fig S7
In-vivo two photon microscopy of vascular compartments
Our results confirm that for a 4 second forepaw stimulus: 1) The arterioles dilate significantly in response to stimulus (), and constrict with a small undershoot following stimulus cessation: a timecourse consistent with our previous LOT arteriolar HbT changes (). 2) A measurable diameter increase was not observed in the veins in response to a short 4 second forepaw stimulus (). In addition, we were able to observe an increase in the speed of the flow in the veins (). In 40% of the veins examined, a slightly delayed increase in red blood cell (RBC) density was also noted (17% ± 6% where seen and 6.4% ± 8.6% overall change, at cessation of stimulus) as shown in . These trends were consistent across all rats. summarizes the mean changes over the whole active region illustrated in .
TABLE 1 Parameters of vascular dynamics across the active region shown in during 4 second forepaw stimulus. Data were acquired using rapid full-field two-photon microscopy (data processing methods are described in supplementary data Fig S7). (n) describes (more ...)
For our paradigm therefore, the arterioles dilate and a concomitant increase in blood flow is seen in the veins. This increase in flow manifests primarily as a change in the speed of the blood flow in the veins, sometimes accompanied by a small delayed increase in the venous RBC density, and not as a significant venous dilation or stretching. This red blood cell density change may account for the small HbT change that we observed in the veins in our LOT results, particularly the latent tail of the venous HbT increase. It is possible that the early changes in the LOT venous HbT are the result of a very small venous diameter increase, below our measurement threshold. This slight % change might correspond to the increased inflow pressure, and would be expected to vary with the arteriolar dilation. Note that further studies are required to determine whether venous dilation becomes a more significant phenomenon for longer or stronger stimuli, for significantly larger veins, or for different species.
As shown in , we find very close correlation (ρ = 0.985, y = 1.00x + 0.03, R2 = 0.97) between the percentage changes in the venous flow (RBC density × speed) and the percentage change in diameter4 of the arteriole (as given by Poiseuille’s law). This finding strongly supports the notion that blood flow dynamics may indeed be calculable from measurements of arteriolar HbT.