Neural activation increases blood flow locally. This vascular signal is used by functional imaging techniques to infer the location and strength of neural activity1,2. However, the precise spatial scale over which neural and vascular signals are correlated is unknown. Furthermore, the relative role of synaptic and spiking activity in driving haemodynamic signals is controversial3,4,5,6,7,8,9. Previous studies recorded local field potentials as a measure of synaptic activity together with spiking activity and low-resolution haemodynamic imaging. Here we used two-photon microscopy to measure sensory-evoked responses of individual blood vessels (dilation, blood velocity) while imaging synaptic and spiking activity in the surrounding tissue using fluorescent glutamate and calcium sensors. In cat primary visual cortex, where neurons are clustered by their preference for stimulus orientation, we discovered new maps for excitatory synaptic activity, which were organized similarly to those for spiking activity but were less selective for stimulus orientation and direction. We generated tuning curves for individual vessel responses for the first time and found that parenchymal vessels in cortical layer 2/3 were orientation selective. Neighbouring penetrating arterioles had different orientation preferences. Pial surface arteries in cats, as well as surface arteries and penetrating arterioles in rat visual cortex (where orientation maps do not exist10), responded to visual stimuli but had no orientation selectivity. We integrated synaptic or spiking responses around individual parenchymal vessels in cats and established that the vascular and neural responses had the same orientation preference. However, synaptic and spiking responses were more selective than vascular responses—vessels frequently responded robustly to stimuli that evoked little to no neural activity in the surrounding tissue. Thus, local neural and haemodynamic signals were partly decoupled. Together, these results indicate that intrinsic cortical properties, such as propagation of vascular dilation between neighbouring columns, need to be accounted for when decoding haemodynamic signals.
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We thank A. Shih for comments on the manuscript. This work was supported by grants from the National Institutes of Health (NS088827), National Science Foundation (1539034), and Whitehall and Dana Foundations to P.K.
The authors declare no competing financial interests.
Extended data figures and tables
a, Region of cat visual cortex labelled with iGluSnFR. Pixels are colour-coded by preferred orientation with the brightness indicating the response strength. Time courses and polar plots (averages of four trials) are shown for three regions of tissue with different orientation preferences. b, Orientation maps of iGluSnFR responses from a different cat. Time courses and polar plots are averages of ten trials.
a, Time courses and polar plots of arteriole dilation (red) and the release of glutamate in a 400-μm-diameter window surrounding an arteriole (blue). Averages of eight trials are shown for vessel dilation and ten trials for glutamate responses. In time courses, error bands represent s.e.m. and grey bars represent the periods of visual stimulation. The responses to the 135° and 180° stimuli (outlined by the black box over the time courses) are large for the vessel dilation but virtually non-existent for the glutamate activity. b, Quantifying the relative amplitude of the vessel and neural responses to each of the eight stimulus directions for the single cat experiment shown in a. Each data point in the scatterplot represents the average response of the vessel and of the neural tissue surrounding it to a single direction of visual stimulation, normalized by the response to the best direction. c, Quantifying the relative amplitude of vessel and neural responses across all cat experiments. Top panel shows glutamate versus dilation data (n = 37 windows and vessels in 5 cats) and the bottom panel shows calcium versus dilation responses (n = 19 windows and vessels in 8 cats). Each data point in the scatterplot is as described in b. The histograms at the top and right show the distributions of neural and dilation responses, respectively. In both population scatterplots, there are many data points in the top left quadrant, indicating stimuli that drove robust dilation responses but minimal glutamate or calcium responses. All data are from cat visual cortex layer 2/3.
Extended Data Figure 3 Direction selectivity of parenchymal vessels and of local spiking and synaptic activity.
a, Population distributions of the direction index of calcium (green, n = 19 windows in 8 cats), glutamate (blue, n = 37 windows in 5 cats) and vessel dilation (red, n = 79 vessels in 18 cats) responses. All data were obtained from cat visual cortex and neural responses were pooled over 400-μm-diameter windows. The DI of spiking activity was greater than the DI of synaptic responses (P < 0.01, Mann–Whitney test) and the DI of vessel dilation (P < 0.0005, Mann–Whitney test). The DI of synaptic activity was not different from the DI of vessel dilation (P = 0.70, Mann–Whitney test). Solid bars are medians and boxes show the interquartile range. b, For each vessel that had a corresponding 400-μm-diameter window of calcium or glutamate activity, the vessel direction index is plotted against the corresponding neural direction index. There was no significant correlation for calcium (R = 0.2, P = 0.43, n = 19 pairs) or glutamate (R = 0.2, P = 0.23, n = 37 pairs).
Extended Data Figure 4 Dilation and velocity responses in parenchymal blood vessels with different baseline diameters.
a, The diameter of all vessels and their OSI values from cat visual cortex layer 2/3. For arterioles, OSI was determined based on dilation (n = 79 vessels in 18 cats) whereas for capillaries, OSI was calculated from blood velocity measurements (n = 15 vessels in 7 cats). b, The distribution of OSI for the three subgroups of layer 2/3 vessels analysed in our study (>15 μm, n = 44 vessels in 15 cats; ≤15 μm, n = 35 vessels in 14 cats; capillaries, n = 15 vessels in 7 cats). The OSI of the ≤15 μm vessels was greater than the OSI of the >15 μm vessels (P < 0.05, Mann–Whitney test). The OSI of the ≤15 μm vessels was not different from the OSI of the capillaries (P = 0.16, Mann–Whitney test). Solid bars are medians and boxes indicate the interquartile range. c, The OSI distribution of dilating vessels and 400 μm-diameter windows of calcium and glutamate responses.
a, Vessel-by-vessel comparison of the onset latency difference between the response to preferred and orthogonal (null) stimulus orientations. Each whisker diagram represents a single vessel with the circle position indicating the standardized mean difference (SMD; calculated as Hedge’s g) in latency. The whisker length represents the 95% confidence interval (CI) of the SMD. The size of the circle represents the weight given to the vessel when calculating the population summary SMD. The population summary SMD is shown by the solid square with the error bands giving the 95% CI. The population average shows that parenchymal vessels responded significantly faster for the preferred than the null stimulus orientation. b, As a control, the analysis shown in a was repeated after randomizing the assignment of preferred and null on individual trials for each vessel. All data are from cat visual cortex layer 2/3 (n = 79 vessels in 18 cats).
a, The steps of the circle fitting algorithm are illustrated for a blank and a stimulus frame corresponding to the penetrating arteriole shown in the bottom panel of Fig. 1b. The raw image data (first panel) is oversampled by linear interpolation between pixels (second panel). Then a luminance threshold (a fraction of the gradient between the brightest and darkest pixel of the image) is applied (third panel). Finally, a two-dimensional sobel filter is applied to the thresholded pixels to detect the edge of the vessel (fourth panel). The circle fit is only applied to the pixels in the fourth panel but it is overlaid on all the panels for illustration purposes. b, As the threshold is increased, fewer pixels pass the threshold and therefore the baseline diameter changes. However, the percentage change in diameter across baseline and stimulus presentations (the response amplitude) and the response selectivity remain the same. Note that for vessel geometries needing an elliptical fit rather than a circular fit (see Extended Data Fig. 8c and Methods), the shorter axis of the fitted ellipse was used to estimate the vessel diameter.
Extended Data Figure 7 Dilation measurements using the cross-section algorithm do not depend on the precise location and angle of the selected cross-section.
a, Example cat pial artery (from Fig. 1c) labelled with Texas Red Dextran. b, Another pial artery from a different cat labelled with the artery-specific dye Alexa 633. Both arteries show similar tuning for cross-sections drawn >100 μm apart and also drawn perpendicular and obliquely relative to the vessel walls.
Extended Data Figure 8 Dilation measurements in small arterioles and comparison of dilation measurement techniques.
a, A penetrating artery (#1, the responses of which are shown in the top panel of Fig. 1b) and its daughter branch (#2) in cat layer 2/3 labelled with Texas Red Dextran. Red lines indicate the position of the laser scan path across the vessels for line-scan diameter measurements. b, Individual line-scans are stacked next to each other to create X-time (XT) images. The four large rectangular panels are XT images of a blank and stimulus frame for each of two vessels shown in a. The small panels to the right are the average across the image (~0.96 s) for each of the four frames. The computed diameter values are also shown. These images were oversampled by interpolating between pixels (by 5 times for vessel 1 and by 20 times for vessel 2) before the diameter was calculated. c, The time courses and polar plots of the responses for three different diameter measurements are shown for vessel 1—as a line-scan, a cross-section from a full-frame imaging run (seven trials), and the circle fit from the full-frame imaging run. In this particular example we used an ellipse rather than a circle because of the elongation of the vessel due to its diving obliquely to the imaging plane. d, Time courses of the vessel responses to preferred stimulus orientations for the three groups of vessels shown in Extended Data Fig. 4b. The responses for each vessel were aligned by stimulus onset and binned in 400-ms bins. The population average was then smoothed with a three-frame running average. Mean responses in dark colours and light bands indicate s.e.m. Note that the similar error bands and temporal profiles indicate that the smallest vessels had a similar quality of responses to the larger ones.
Extended Data Figure 9 Comparison of orientation selectivity in regions of calcium responses with and without neuropil.
a, In vivo anatomical image of cells labelled with OGB-1 AM in cat visual cortex and selection of two different masks for quantitative analysis of orientation selectivity. Left, a 400 μm-diameter mask comprising soma pixels only. Right, a 400 μm-diameter mask comprising all significantly responding pixels (see Methods). b, The time courses of calcium responses computed from the two masks. Time courses are averages of five trials, error bands represent s.e.m. and grey bars represent the periods of visual stimulation. c, For a population of 16 imaged regions (from 7 cats), the OSI was computed with the two masks and found to be indistinguishable (cell bodies only OSI mean ± s.e.m. = 0.46 ± 0.04; cell bodies and neuropil OSI mean ± s.e.m. = 0.47 ± 0.04; P = 0.12, paired t-test).
a, Region of cat visual cortex labelled with OGB-1 AM (to measure spiking activity) and SR101 (to distinguish astrocytes). Note the much sparser density of neuronal cell bodies in layer 1 (left) compared with the higher density of cells deeper in layer 2/3 (right). The polar plots are the responses of the two layer 1 neurons labelled in the image. b, Region of cat visual cortex labelled with iGluSnFR (to measure synaptic activity). Again the density of cell bodies (the small black holes) in layer 1 (left) is much lower than in layer 2/3 (right). The polar plots are the responses of a 400-μm- and 100-μm-diameter window of layer 1 glutamate activity.
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O’Herron, P., Chhatbar, P., Levy, M. et al. Neural correlates of single-vessel haemodynamic responses in vivo. Nature 534, 378–382 (2016). https://doi.org/10.1038/nature17965
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