Understanding the mechanisms by which neural activity regulates local blood flow is a fundamental issue in neuroscience. Changes in neural activity are coupled to hemodynamics via neurovascular coupling, where neural activity drives the dilation of arterioles and other vessels (Drew et al., 2011; Hillman, 2014; Hill et al., 2015; Mishra et al., 2016; Iadecola, 2017; Rungta et al., 2018; Drew, 2019). Arterial dilations are most strongly correlated to increases in the gamma-band power of the LFP (local field potential), with lower correlation to the power in other bands of the LFP (Goense and Logothetis, 2008; Logothetis, 2008; Mateo et al., 2017; Winder et al., 2017; Drew et al., 2020). While it is controversial whether capillaries dilate (Hall et al., 2014; Hill et al., 2015; Mishra et al., 2016; Rungta et al., 2018) and whether this dilation is active or passive (Mishra et al., 2016; Rungta et al., 2018), sensory stimulation drives reliable and large (~20%) dilations of cerebral arteries in un-anesthetized animals (Drew et al., 2011; Hill et al., 2015; Rungta et al., 2018; Drew, 2019), which contributes to increases in blood flow. The sensory-evoked dilation initiates in the deeper layers of the cortex (Tian et al., 2010; Rungta et al., 2018), and rapidly propagates up to the surface (pial) arteries (Drew et al., 2011; Mateo et al., 2017) via conduction of an electrical signal (Chen et al., 2011; Hillman, 2014; Longden et al., 2017). Pial arteries show dilations correlated with spontaneous gamma band power (Mateo et al., 2017), and in awake animals, pial arteries show stimulus-selective dilations in response to sensory stimulation (Drew et al., 2011; Gao and Drew, 2016; Winder et al., 2017). Pial arteries in the histologically reconstructed forelimb/hindlimb representation of primary somatosensory cortex dilate substantially more during locomotion than arteries just outside of this representation (Gao et al., 2015), although there may be less sensory specificity of the pial vessels responses in anesthetized animals (O'Herron et al., 2016). Simulations have suggested that the dilation of these arteries can play an important role increasing blood flow during functional hyperemia (Schmid et al., 2017; Rungta et al., 2018).

There are multiple signaling pathways and molecules implicated in linking neural activity (both directly and indirectly) to arteriole dilations (Attwell et al., 2010; Cauli and Hamel, 2010; Kleinfeld et al., 2011; Lacroix et al., 2015; Longden et al., 2017). While no single mechanism likely underlies neurovascular coupling, there is an extensive literature connecting the vasodilator nitric oxide (NO) to vasodilation both in the periphery and the brain (Tanaka et al., 1991; Iadecola, 1992; Adachi et al., 1994; Stefanovic et al., 2007; Hosford and Gourine, 2019; Han et al., 2019a). Recent in vitro evidence indicates neuronally-generated nitric oxide acts directly on arteries, while astrocytic signals control capillary dilations (Mishra et al., 2016). However, which set(s) of neurons control arterial diameter is not well understood. Optogenetic stimulation of interneurons drives a larger vasodilation than optogenetic stimulation of pyramidal neurons (Vazquez et al., 2014; Anenberg et al., 2015; Uhlirova et al., 2016b; Vazquez et al., 2018; Krawchuk et al., 2020), suggesting a subset of neurons exerts a disproportionate control over vasodilation. Optogenetic stimulation of neuronal nitric oxide (nNOS, also known as NOS1) expressing interneuron, but not in VIP or parvalbumin interneurons, produces increase in blood flow and vasodilation (Krawchuk et al., 2020; Lee et al., 2020), and this vasodilation is not accompanied by a detectable increase in neural activity (Lee et al., 2020), suggesting that nNOS neurons can influence local hemodynamics without detectably altering the activity of the rest of the network.

There are two types of nNOS–expressing neurons in the cortex, Type 1 and Type 2 (Kawaguchi and Kubota, 1997; Vruwink et al., 2001; Kubota et al., 2011). Type 1 nNOS neurons are sparse, are primarily found in deeper layers and express nNOS at higher levels. While Type 1 nNOS neurons receive many different neuromodulatory inputs (Williams et al., 2019; Williams et al., 2018), nearly all of them express the Substance P (SP) receptor (NK1R), and both single-cell genomic and histological studies have shown that they are the only cells in the mouse cortex that express the Substance P receptor (Vruwink et al., 2001; Dittrich et al., 2012; Barbaresi et al., 2015; Endo et al., 2016; Tasic et al., 2016). In vitro studies have shown that application of Substance P causes prolonged high-frequency spiking in type 1 nNOS neurons (Dittrich et al., 2012; Endo et al., 2016). Type 1 nNOS neurons also have extensive, long-range projecting axonal arbors that well-position them to influence the vasculature. In contrast, type 2 nNOS neurons are a heterogeneous group of interneurons that are substantially more numerous, found primarily in the deep and superficial layers of the cortex, with processes that can span multiple layers (Perrenoud et al., 2012). Type 2 nNOS neuron express nNOS at lower levels than type 1 nNOS neurons. The synthesis of NO by nNOS is calcium dependent, and as NOS is found both in the cell bodies and the processes of neurons NO will be produced throughout the cell when calcium levels rise with activity (Valtschanoff et al., 1993; Blottner et al., 1995).

While most studies of neurovascular coupling have focused on the impact of brief elevations of neural activity on hemodynamic signals, the role of neural activity in setting the baseline levels of these signals is not well understood, but have important implications for understanding the relationship between neural activity and hemodynamic signals. Most hemodynamic imaging modalities, such as BOLD fMRI, laser speckle, laser Doppler and Doppler ultrasound, are ratiometric, meaning they measure a percentage change from a baseline rather than an absolute change. This means that these measurements are sensitive to the baseline level of flow and dilation. For a given absolute change in flow, an elevated baseline will reduce the amplitude of the signal. This issue has long been appreciated in fMRI (Cohen et al., 2002; Whittaker et al., 2016; Kim et al., 2020), and there are techniques available to calibrate these signals (Kim and Ogawa, 2012). Differences in baseline are an important confound in comparisons across different groups, confounding aging and disease studies in humans (D'Esposito et al., 2003), particularly as in humans baseline blood flow drops with aging (Ruitenberg et al., 2005; Wolters et al., 2017). However, the impact of shifting the baseline levels, and particularly how neural activity could affect them, has been underappreciated in neurovascular coupling studies, which often compare the impact of disrupting a pathway in different groups of animals using ratiometric techniques. This is particularly a problem because it is not well understood how baseline (non-stimulus evoked) levels of neural activity control blood flow, and ongoing neural activity in the un-anesthetized brain is very high. In contrast, two-photon imaging can measure absolute hemodynamic signals (Shih et al., 2012b), such as dilations of single vessels and velocities (Kleinfeld et al., 1998) and fluxes (Chaigneau et al., 2003; Shih et al., 2009a) of red blood cells.

Elucidating which neuronal cell types control arterial dilation (Kleinfeld et al., 2011; Uhlirova et al., 2016a) is important for interpreting hemodynamic imaging signals (Logothetis, 2008; Kim and Ogawa, 2012). Moreover, the regulation of basal arterial diameter, which plays a role in the control of baseline blood flow (Gagnon et al., 2015; Schmid et al., 2017), is also important because decreases in basal cerebral blood flow occur with aging, and the magnitude of these decreases predicts neurodegeneration (Ruitenberg et al., 2005; Wolters et al., 2017).

We used two-photon microscopy (Shih et al., 2012b) to chronically image pial and penetrating arterioles in the somatosensory cortex of awake, head-fixed mice (Figure 1A and B; Drew et al., 2011; Gao and Drew, 2016; Winder et al., 2017) through polished and reinforced thinned-skull (PoRTs) windows (Drew et al., 2010b), which allow chronic imaging without inflammation. Because we were able to repeatedly image from the same vessels over multiple imaging sessions (Figure 1C), we were able to make quantitative comparisons of individual vessel diameter changes in response to manipulations of neural activity, rather than compare vessel responses from two different groups of animals. All drug/CNO, vehicle infusions, and injections were randomly counterbalanced across animals. As we measured from multiple vessels in each mouse, we used linear mixed-effect models (LME, see Materials and methods) (Aarts et al., 2014) for statistical tests to account for within-animal correlations (Winder et al., 2017; Adams et al., 2018) that make methods such as ANOVA inappropriate (Aarts et al., 2014).

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We measured arteriole diameter dynamics evoked by locomotion, as behavior is the primary driver of neural and hemodynamic signals in the awake brain (Figure 1D; Gao and Drew, 2016; Winder et al., 2017; Stringer et al., 2019), and because sensory stimulation in awake animals invariably elicits movement (Cooke et al., 2015; Drew et al., 2019; Musall et al., 2019; Salkoff et al., 2020). The change in diameter and neural activity during locomotion was quantified by averaging the dilation or neural activity 3 to 4 s after the onset of locomotion. We reconstructed the locations of individual arterioles relative to the forelimb/hindlimb (FH/HL) representation in somatosensory cortex (purple and green shaded regions Figure 1B, top), as arteries inside the FL/HL region dilate selectively in response to locomotion, significantly more so than arteries immediately outside the histologically-identified FL/HL (Gao et al., 2015). Locomotion-induced arterial dilations in the FL/HL area of somatosensory cortex have highly reliable and stereotyped dynamics (Huo et al., 2015b), and are unaffected by pharmacological manipulations of heart rate and blood pressure (Huo et al., 2015a), consistent with local neural control. During bouts of voluntary locomotion, neural activity increased substantially in the forelimb/hindlimb representation in somatosensory cortex, as measured by changes in multi-unit firing rate and power in the gamma-band of the LFP (Figure 1—figure supplement 1; Huo et al., 2014; Zhang et al., 2019). These increases are driven primarily by cutaneous sensation rather than proprioception (Chapin et al., 1981; Chapin and Woodward, 1981; Chapin and Woodward, 1982; Chapin and Lin, 1984). During locomotion, this neural activity is sustained, and shows minimal adaptation (Zhang et al., 2019). In response to this increase in neural activity, both pial and penetrating arterioles in the FL/HL representation dilated (Huo et al., 2015b; Gao and Drew, 2016; Figure 1D and Figure 1—figure supplement 2 and Video 1 and 2) with short latency (onset time: 0.59 ± 0.31 s in the FL/HL region).

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Bidirectional chemogenetic manipulation of local neural activity controls basal arterial diameter

We then asked if we could bi-directionally manipulate arterial diameters using chemogenetic techniques to drive changes in overall neural activity. We expressed either hM4D-G(i) or hM3D-G(q)-coupled DREADDs (Urban and Roth, 2015) pan-neuronally under a human synapsin promoter (hSyn) in C57BL/6J mice. G(i)- and G(q)-coupled DREADDs will respectively decrease and increase the excitability of the cells expressing them after injection of the DREADDs agonist CNO. As a control, mice infected with an AAV encoding only the fluorescent reporter mCherry did not show significant changes in neural activity, or in basal or evoked arterial diameter after the injection of CNO (Figure 2—figure supplement 1B–D), showing CNO has minimal off-target effects on neural activity and arterial diameters.

We imaged arterioles in the DREADD-expressing region of cortex (identified by mCherry expression seen in vivo, Figure 2A, and histologically, Figure 2B). Injections of CNO in mice with pan-neuronal expression of hM4D-G(i) DREADDs resulted in a non-significant decrease in gamma-band power relative to vehicle injections (Figure 2C, basal −1.9 ± 27.2%, p<0.09; locomotion, +3.6 ± 10.3%, p<0.07), likely because of the parallel changes in excitability of inhibitory and excitatory cells cancelled out. Still, activation of hM4D-G(i) DREADDs resulted in significant decreases in basal arterial diameter (Figure 2D, −7.1 ± 7.0%, LME p<0.02 n = 7 mice, 45 vessels), which was particularly noticeable in the largest arterioles. We note that the hM4D-G(i) DREADDs did not uniformly lower neural activity, as we observed bursting activity in our electrophysiological recordings every few seconds (Figure 2—figure supplement 2A), and corresponding arterial dilations at similar frequencies (Figure 2—figure supplement 2B). While we saw clear constrictions in arteriole diameters when activating hSyn G(i)-DREADDs relative to baseline, there were also large spontaneous dilations, which on average cancelled out. The net effect of hM4D-G(i) DREADDs on the locomotion-evoked response was minimal (Figure 2E, locomotion-evoked response: vehicle 20.5 ± 2.0%, CNO 18.3 ± 4.1%, LME p<1, n = 7 mice, 25 arterioles in FL/HL representation).

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When we pan-neuronally expressed hM3D-G(q) DREADDs, which will increase excitability and intracellular calcium levels (Alexander et al., 2009; Pati et al., 2019), activation of the DREADDs with CNO injections caused increases in gamma-band power relative to vehicle (Figure 2F, basal 18.6 ± 11.2%, p<0.02; locomotion, 43.6 ± 15.0%, p<7.1×10⁻³). Injections of CNO caused substantial increases in the basal arterial diameter over controls (Figure 2G, +18.8 ± 5.6%, LME p<0.03, n = 7 mice, 37 vessels). The increase in basal arteriole diameter by hM3D-G(q) DREADD activation was comparable to the locomotion-evoked response (Figure 2H, locomotion-evoked response: vehicle 18.6 ± 1.7%, CNO 26.0 ± 4.2%, LME p<1, n = 7 mice, 23 arterioles in FL/HL representation). These results suggest that neurons, or a subset of neurons, tonically release vasodilator(s) due to ongoing background neural activity, and elevation of this activity can drive arterial dilations.

Altering pyramidal neuron excitability drives large neural activity changes without corresponding changes in arterial diameter

The importance of local neural activity on the regulation of arterial dilation raises the question of which sub-population(s) of neurons are involved. We manipulated the excitability of pyramidal neurons by injecting AAVs encoding hM3D(q) or hM4D(i) DREADDs under a CaMKIIa promoter, which will restrict the expression to pyramidal neurons (López et al., 2016; Yuan and Grutzendler, 2016). CaMKIIa-DREADDs labeled cells colocalized with CaMKIIa expression and were primarily localized to neurons with cell bodies in layer 5 (Figure 3A). Previous work has shown that optogenetic stimulation of layer 5 pyramidal neurons drives increases in neural activity in all layers via recurrent connections, and these increases in neural activity are very similar to what is seen with sensory stimulation (Vazquez et al., 2014; Vazquez et al., 2018), so chemogenetic stimulation of these cells will likely produce neural activity patters similar to those normally found in the cortex. The dilatory signal in the deeper cortical layers is electrically conducted through the vasculature rapidly by gap junctions (Bagher and Segal, 2011; Welsh et al., 2018) to the pial vessels (Rungta et al., 2018). Activating hM4D(i) DREADDs in excitatory neurons with CNO caused large decreases in basal gamma-band power (Figure 3B and D, basal −36.0 ± 16.4%, p<0.01; locomotion, −26.8 ± 15.8%, p<0.02). When hM3D(q) DREADD receptors in excitatory neurons were activated, a corresponding large increase in basal gamma-band power was observed (Figure 3C and G, basal +52.4 ± 18.9%, p<5.0×10⁻³; locomotion, +50.9 ± 31.6%, p<0.02). Despite the large changes in neural activity, we did not see significant changes in the basal arterial diameters with manipulation of pyramidal neuron activity (−2.2 ± 5.7%, LME p<1, n = 7 mice, 38 arterioles for inhibition and +7.2 ± 8.8%, LME p<0.66, n = 6 mice, 41 arterioles for excitation) (Figure 3E and Figure 3H, respectively). The locomotion-evoked dilations were also not affected by manipulations of neural excitability (Figure 3F G(i) DREADDS: vehicle 25.3 ± 1.9%, CNO 21.6 ± 4.3%,LME p<1, n = 7 mice, 29 arterioles in FL/HL representation; Figure 3I G(q) DREADDS: vehicle 19.1 ± 2.3%, CNO 17.3 ± 4.7% LME p<1, n = 6 mice, 13 arterioles in FL/HL representation).

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The lack of change in the arterial diameters could not be due to a lack of an effect of the chemogenetic manipulations as the changes in neural activity were very large. The decreases in basal neural activity generated by activation of G(i)-coupled DREADDs in pyramidal neurons were nearly as large as those elicited by muscimol (Figure 3B), and the increases in basal neural activity generated by activation of G(q)-coupled DREADDs in pyramidal neurons were as large as those seen during locomotion (Figure 3C), yet in neither of these cases did we observe arterial diameter changes of similar magnitude. Thus, pyramidal neuron activity is a strong driver of gamma band LFP power, but only has a moderate effect on basal arterial diameter, and little effect on the locomotion-evoked dilations.

nNOS-expressing neurons and NO signaling control arterial diameter independent of overall neural activity

Previous work has implicated neuronally-generated nitric oxide (NO) (Hosford and Gourine, 2019), generated by interneurons (Krawchuk et al., 2020; Lee et al., 2020) in the dilation of cerebral arteries. To test the role of neuronal nitric oxide synthase (nNOS) expressing neurons, we expressed hM3D(q) and hM4D(i) DREADDs along with the reporter protein mCherry in nNOS-expressing neurons using flexed AAVs in nNOS-cre- mice (B6.129-Nos1^tm1(cre)Mgmj/J, Jackson Laboratory #017526) (Leshan et al., 2012; Augustine et al., 2018). Expression of the reporter protein mCherry was primarily in the deeper and more superficial layers of the cortex (Figure 4A,B), consistent with the observed densities of nNOS-expressing neurons (Perrenoud et al., 2012). Co-labeling with antibodies for nNOS (Figure 4A,B) showed co-expression (white) of mCherry (magenta) and nNOS (green) in both cell bodies and processes of neurons. Neurons showing strong anti-nNOS labeling were taken to be type 1 nNOS neurons, with-type 2 nNOS neurons showing less intense anti-nNOS labeling, consistent with previous anatomical studies (Perrenoud et al., 2012). Immunolabeling (n = 2 mice) revealed that 28.6% (2/7 cells) type 1% and 35.2% (19/54) of type 2 nNOS neurons expressed DREADDs, and that 44.6% (21/47) of DREADD-expressing cells were nNOS positive. Neurons expressing mCherry also expressed GAD65, indicating they were GABAergic interneurons (Figure 4C).

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CNO injections in mice expressing G(i)-DREADD in nNOS-expressing neurons resulted in no significant change in gamma-band power (Figure 4D, basal −1.2 ± 11.6%, p<1; locomotion, −5.7 ± 2.2%, p<0.09). Increasing the excitability of nNOS-expressing neurons resulted in a significant decrease in basal gamma-band power (Figure 4G, basal −19.8 ± 2.6%, p<4.0×10⁻³; locomotion, −12.8 ± 4.7%, p<0.10), consistent with these neurons being inhibitory. However, decreasing the excitability of nNOS neurons drove substantial and significant decreases in both basal arteriole diameter (−10.3 ± 6.4% LME p<1.3×10⁻⁴, n = 9 mice, 49 vessels Figure 4E) and the locomotion-induced dilation (Figure 4F, vehicle 15.3 ± 2.0%, CNO 0.3 ± 4.3%, LME p<6.3×10⁻³, n = 6 mice, 22 arterioles in FL/HL representation). Elevating the excitability of nNOS-expressing neurons significantly increased the basal arterial diameter (+5.8 ± 6.6%, LME p<2.7×10⁻⁴, n = 8 mice, 52 vessels, Figure 4H), but did not increase the locomotion-evoked increase above the control (Figure 4I vehicle 17.4 ± 1.8%, CNO 19.6 ± 3.8%, LME p<1, n = 8 mice, 25 arterioles in FL/HL representation). Interestingly, the diameter changes moved in the opposite direction as neural activity when the excitability of nNOS-expressing neurons was increased, consistent with nNOS neurons being inhibitory.

We then tested whether the effects of nNOS-expressing neuron activity on arteriole diameter was mediated by NO, as these neurons can also release vasoactive peptides (Cauli et al., 2004). Previous studies with NOS inhibitors have shown conflicting effects (Lindauer et al., 1999; Stefanovic et al., 2007). Discrepancy in the literature could be due to differences in experimental methodology: topical application of drugs may not reach lower cortical layers (Greenberg et al., 1997; Ferezou et al., 2006) where most of the highly expressing nNOS neurons reside, and systemic administration impacts the cardiovascular system. To avoid these experimental confounds, we infused the water-soluble NO synthase inhibitor, Nω-nitro-L-arginine methyl ester (L-NAME) through an implanted cannula to decrease NO-mediated signaling. In our hands, pharmacological infusions through cannula affect all cortical layers within ~1.5 mm of the infusion site (Winder et al., 2017). Note that recent studies, using both single-cell genomic methods as well as immunohistochemistry, have shown that some cortical neurons express eNOS (Yousef et al., 2004; Lein et al., 2007; Tasic et al., 2016), and that some endothelial cells of cerebral arterioles express nNOS (Vanlandewijck et al., 2018; Zeisel et al., 2018), so the endothelial/neural specificity of these enzymes is not complete. Additionally, crystal structures and careful pharmacology experiments have revealed that ‘selective’ pharmacological inhibitors of nNOS are much less selective than was originally thought (Bland-Ward and Moore, 1995; Reiner and Zagvazdin, 1998; Engelhardt et al., 2006; Pigott et al., 2013; Poulos and Li, 2017), so it is likely that there are no inhibitors of nNOS or eNOS are specific enough to target one enzyme over another in vivo. Finally, locomotion-evoked dilations are unlikely to be mediated by eNOS expressed in endothelial cells as increases in eNOS activity in response to flow-evoked changes in diameter evolve over minutes, not seconds (Kim et al., 2016) (too slow to account for the locomotion-evoked dilations), and there are no shear-stress changes seen with sensory-evoked dilation (Ngai and Winn, 1996). Blocking the production of NO caused no significant change in the basal gamma-band power (Figure 4—figure supplement 1A, basal −5.0 ± 8.5%, p<0.55; locomotion, −7.5 ± 9.6%, p<0.43), but drove a decrease in basal and locomotion-evoked arterial diameter (−10.6 ± 4.6%, LME p<7.6×10⁻⁶, n = 6 mice, 36 arterioles, and vehicle 13.2 ± 2.4%, L-NAME 4.2 ± 3.8%, LME p<0.04, n = 6 mice, 20 arterioles in FL/HL representation, Figure 4—figure supplement 1B and C). The basal arterial diameter constrictions produced by L-NAME were not significantly different from those produced by G(i) DREADDs in nNOS neurons (−10.6% vs. −10.3%, LME p<0.57 Figure 4—figure supplement 1D). Although there is likely some contribution from the inhibition of eNOS contributing to these constrictions (Atochin and Huang, 2011), these results are consistent with the hypothesis that the NO produced by nNOS-expressing neurons contributes maintaining the diameter of cerebral arterioles.

Pharmacological manipulations of type 1 nNOS neuron activity

As we saw expression of DREADDs primarily in type 2 nNOS neurons, we wondered how activation of type 1 nNOS neurons might affect arteriole dynamics. Type 1 nNOS neurons are unique among cortical neurons in that they express the receptor for Substance P (NK1R) (Vruwink et al., 2001; Tomioka et al., 2005; Tomioka and Rockland, 2007; Gerashchenko et al., 2008; Kilduff et al., 2011; Kubota et al., 2011; Dittrich et al., 2012; Dittrich et al., 2015; Endo et al., 2016; Williams et al., 2019; Williams et al., 2018), whose activation drives depolarization and spiking (Dittrich et al., 2012; Endo et al., 2016). As multiple single-cell genomics studies have shown there is no NK1R expressed in mouse cerebral vascular cells or in glial cells (Vanlandewijck et al., 2018; Zeisel et al., 2018), we can pharmacologically manipulate the activity of Type 1 nNOS neurons independently of other neurons by infusing SP, or an antagonist for the SP receptor, CP-99994 through a chronically implanted cannula. Infusions of CP-99994 caused non-significant changes in gamma-band power (Figure 5A, basal −5.4 ± 4.7%, p<0.28; locomotion, +7.3 ± 8.0%, p<0.37) and a non-significant decrease in basal arteriole diameter (−8.0 ± 7.2%, LME p<1, n = 7 mice, 28 vessels, Figure 5B) and locomotion-evoked dilation response (vehicle 13.7 ± 2.6%, CP-99994 9.7 ± 3.3%, LME p<1, n = 7 mice, 14 arterioles in FL/HL representation, Figure 5C). The lack of a substantial effect suggests that either basal activation of the Substance P receptors in the cortex is low, generating a floor effect and/or the basal activity of the type 1 nNOS neurons is low. When we activated the type 1 nNOS neurons via infusions of SP, we observed non-significant decreases in gamma-band power (Figure 5D, basal −20.0 ± 32.4%, p<0.53; locomotion, +5.2 ± 16.0%, p<0.73), but a substantial increase in basal diameter (+13.4 ± 4.4%, LME p<3.6×10⁻³, n = 7 mice, 30 arterioles, Figure 5E), although the effect was not significant for locomotion-evoked responses (vehicle 13.0 ± 2.2%, SP 24.8 ± 4.7%, LME p<0.75, n = 7 mice, 14 arterioles in FL/HL representation, Figure 5F). To test the hypothesis that the Substance P facilitated dilation was mediated by increases in neural activity, we co-infused SP with muscimol to block local neural activity, and observed a reduction of the arteriole diameter (−20.0 ± 14.9%, LME p<3.4×10⁻⁷, n = 5 mice, 27 arterioles, Figure 5G) and no locomotion-evoked dilation (vehicle 14.2 ± 3.0%, SP+muscimol −14.5 ± 3.7%, LME p<2.8×10⁻³, n = 5 mice, seven arterioles in FL/HL representation, Figure 5H), consistent with the action of SP being mediated through local neural activity. These results suggest that type 1 nNOS neurons play an important role in NO-mediated changes in arteriole diameter.

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Comparison of pial and penetrating arteriole basal and evoked diameter changes

It is informative to compare the responses of pial and penetrating arterioles to the manipulations performed here. We saw some differences between pial and penetrating arterioles, both in changes to their basal diameters, and in locomotion-evoked dilations. When we looked at basal diameter changes, we saw a significantly smaller constriction of penetrating arterioles than pial arterioles with muscimol infusions (Figure 6A). With pan-neuronal excitatory DREADDs, we saw a significantly smaller dilation in penetrating arterioles than in the pial arteries (Figure 6D). For all other manipulations, which in general produced smaller changes than muscimol and pan-neuronal excitatory DREADDs, there was no significant difference in the induced basal diameter changes between penetrating and pial arteries.

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We then examined the percentage change in diameter during locomotion in pial and penetrating arterioles, here defined as the change from the respective pre-locomotion baseline normalized by the pre-locomotion baseline, for each of the manipulations. For this metric, a manipulation that causes a 10% constriction of baseline and shows a dilation of 5% above the control baseline will have a 15% locomotion-induced dilation (Figure 6—figure supplement 1). If the vessel has a 10% baseline dilation and during locomotion dilates to 15% above the control baseline, the percentage change will be 5%. This metric only captures the locomotion-induced dilation component and differs from the measures of dilation reported in the sections above, which included the effects of the baseline shift in diameter. When we looked at all the control condition (vehicle injections and aCSF infusions Figure 6—figure supplement 2), we saw a large and substantial difference in the pial arterial dilation versus the penetrating arteriole dilation (17.57 ± 9.35% pial vs. 6.79 ± 6.54% penetrating, LME p<8×10⁻³⁷). This difference is consistent with previous measurements of pial and penetrating arteriole dynamics during locomotion (Gao et al., 2015), so we treated penetrating and pial arteries as separate groups for further statistical analysis. We then compared the percentage diameter change during locomotion for pial arterioles and penetrating arterioles (Figure 6—figure supplement 2). With this metric, we saw significant differences in the locomotion-evoked responses of pial arterioles with muscimol, pan-neuronal excitation (hsyn-Gq), excitation of pyramidal neurons (CaMKIIa-Gq), inhibition of nNOS neurons (nNOS-Gi) and L-NAME. Interestingly, the expression of excitatory DREADDs in pyramidal neurons and pan-neuronally had the paradoxical effect of decreasing the amplitude of the locomotion-evoked dilation when quantified relative to its within treatment baseline. This result can be explained by the increased baseline neuronal activity increasing baseline arteriole diameters while not extending the maximum amplitude of arterial dilations. However, none of our manipulations produced a significant change in the locomotion-evoked diameter change of penetrating arterioles from the control condition (Figure 6—figure supplement 2).

Overall, the locomotion-evoked changes in penetrating arteriole diameters were smaller than those in the pial arteries, and the size of the penetrating arteriole dilations were not affected by our manipulations. The difference observed between penetrating and pial arterioles cannot be due to imaging artifacts, as sub-micron cellular structures like spines and microglial processes can be imaged at this depth with a thinned skull window (Drew et al., 2010b; Shih et al., 2012a), and our diameter measurement algorithm (see Materials and methods) has been validated to work robustly in much lower signal-to-noise regimes than present here (Gao and Drew, 2014). There are several non-exclusive possibilities for the differences between the responses of pial and penetrating arteries to behavioral and experimenter-evoked changes in neural activity. One possible reason for this difference could be that penetrating arterioles are less sensitive to vasodilators, with a less steep voltage-diameter relationship that pial arterioles. As there are differences in mural cell morphology at different levels of the arteriole tree (Hartmann et al., 2015), it is possible that there are some previously unobserved differences in the smooth muscle or endothelial cells between penetrating and pial arteries. When mice are anesthetized with the powerful vasodilator isoflurane, pial and penetrating arteries dilate to the same extent, suggesting that the vessels have the same maximal dilation (Gao et al., 2015). The diameter of arterioles is linearly related to the membrane potential of smooth muscle cells (Wölfle et al., 2011), and any electrical signals at one point are conducted via gap junctions up to several hundred microns away (Segal, 2005; Bagher and Segal, 2011; Hald et al., 2012). As the pial arteries may be further up the arterial tree than penetrating arteries, they will be also integrating signals from many more smaller vessels (Segal, 2000; Welsh et al., 2018), and this may account for the differences in the amplitudes of the responses of the two vessel types. Another possibility could be the spatial location of the generation of the vasodilator(s) relative to the arterioles, particularly in the case of nitric oxide. Simulation of NO diffusion and degradation dynamics in the tissue have shown that NO production needs to be very close (of order microns to tens of microns) to the arteriole in order to exert an appreciable dilatory effect (Haselden et al., 2020). It could be that NO is produced closer to pial vessel (potentially in the processes of more superficial type two neurons), than near the penetrating arterioles in the superficial layers. Finally, the different mechanical environments of the pial and penetrating arterioles may account for their differing responses. The pial arterioles are surrounded by CSF (Abbott et al., 2018), whereas the penetrating arterioles are surrounded by a thin paravascular space (Iliff et al., 2012) filled with collagen fibers tethering the artery to the brain (Roggendorf and Cervós-Navarro, 1977). When the smooth muscle cells surround pial arteries relax, the vessel’s dilation need only displace CSF, which has viscosity near that of water, while dilation (or constriction) of penetrating arterioles must displace (or pull upon) the viscoelastic brain tissue (Goriely et al., 2015; Weickenmeier et al., 2018a; Weickenmeier et al., 2018b; Kedarasetti et al., 2020). The viscoelasticity of brain tissue will function as an ultra-low-pass mechanical filter on diameter changes of penetrating arterioles, reducing the amplitude of ‘rapid’ dilations (on the order of seconds), although allowing slower dynamics (on the order of minutes), which could explain why we saw similar changes in both pial and penetrating arterioles baseline (which take place over minutes), but no effects on the ‘rapid’ locomotion-evoked dilations. Studies in peripheral vascular structures have shown that when blood vessels are imbedded in tissue, the mechanics of the surround tissues dominates and reduces their dilation (Fung et al., 1966; Liu et al., 2007). Brain tissue is stiffer when the skull is intact than after a craniotomy (Hatashita and Hoff, 1987). Brain tissue exhibits strain-stiffening (becoming stiffer under pressure) (Marmarou et al., 1975; Marmarou et al., 1978), and locomotion is accompanied by an elevation of intracranial pressure (Gao and Drew, 2016; Norwood et al., 2019; Eftekhari et al., 2020). All these factors may exacerbate mechanical restriction of dilation by stiffening the brain tissue, preventing full expression of the arterial dilation to locomotion in penetrating arterioles. These results show that pial and penetrating arterioles display similar basal diameter changes for manipulations that produced moderate changes in diameter, although the locomotion-evoked changes in diameter of penetrating arterioles were not affected by any of the manipulations of neural activity. Elucidating the vascular, neural, and/or mechanical origins of the differences in the responses of pial and penetrating arterioles will be informative for understanding their roles in regulating cerebral blood flow (Lorthois et al., 2011; Gould et al., 2017; Schmid et al., 2017).

Locomotion drives robust Ca²⁺ responses in nNOS neurons

If nNOS neurons contribute to the locomotion-induced dilation of arteries, then we would expect their activity to increase during locomotion. Electrophysiological recordings have shown that voluntary locomotion drives large increases in the activity of pyramidal neurons and interneurons in FL/HL representation (Figure 1—figure supplement 1; Zhang et al., 2019), but it is not known if nNOS-positive interneurons exhibit increased activity, as their activity cannot be separated out electrophysiologically. To determine how nNOS-positive interneuron activity is affected by locomotion, we used fiber photometry (Schulz et al., 2012) to simultaneously monitor the activity of nNOS neurons expressing GCaMP6s (Chen et al., 2013) and local cerebral blood volume deep in the parenchyma, which was labeled with an intravenous injection of TRITC dextran (Cerri et al., 2019). Calcium signals have been shown to be strong quantitative predictors of hemodynamic signals (Aydin et al., 2020). Fiber photometry will record bulk calcium signals from the processes and cell bodies of a specific neuronal cell type, and these calcium signals should correlate with nitric oxide production (whose synthesis is known to be calcium dependent) in nNOS-expressing neurons. Fiber photometry is not imaging forming, and will report the summed fluorescence of neurons within ~200 µm from the tip of the fiber (Pisanello et al., 2019), so the contributions of type 1 and type 2 nNOS neurons cannot be differentiated. However, given the low density of type 1 nNOS neurons, the signal is likely to be primarily from type 2 nNOS neurons. We corrected for the absorbance of fluorescence by hemoglobin (Gunaydin et al., 2014; Cerri et al., 2019) in the blood using the TRITC signal, and validated this method on mice that expressed GFP ubiquitously (Okabe et al., 1997; Figure 7—figure supplement 1). The slow (on the timescale of tens to hundreds of seconds) rise and fall of the CBV signals is due to the venous component. The venous contribution to the CBV signal is known to be larger than the arterial component (Kim et al., 2007; Huo et al., 2015b; Huo et al., 2015a) and have slower dynamics than the arterial component (Kim et al., 2007; Drew et al., 2011; Moon et al., 2013; Gao et al., 2015; Huo et al., 2015b; Huo et al., 2015a; Gao and Drew, 2016), particularly in the parenchyma (Kim and Kim, 2010). We found that calcium signals from GCaMP expressed pan-neuronally, in pyramidal neurons, and in nNOS-positive neurons greatly increased during locomotion (Figure 7A–C,E Population GCaMP intensity change in z-units: hSyn: 2.51 ± 0.15, LME difference from CaMKII: p<0.44; CaMKII: 2.59 ± 0.38; nNOS: 1.94 ± 0.37, LME difference from CaMKII: p<1e-3). Activity in all these neuron types was correlated with vasodilation (Figure 7—figure supplement 2, CaMKII: 0.60 ± 0.17; hSyn: 0.54 ± 0.14, LME difference from CaMKII: p<0.7; nNOS: 0.43 ± 0.11, LME difference from CaMKII: p<0.02). We also asked if the activity of nNOS neurons were sustained during locomotion, as there is a sustained dilation of arteries during locomotion (Huo et al., 2015b; Gao and Drew, 2016), and it has been suggested that the response of nNOS neurons is transient (Iadecola, 2017). We found that the responses of nNOS neurons were sustained throughout the locomotion bouts (Figure 7—figure supplement 3 nNOS population GCaMP intensity change in z-units, 10 s: 1.90 ± 0.46, LME: p<0.01, 15 s: 1.84 ± 0.52, LME: p<0.97, 30 s: 1.56 ± 0.40, LME: p<0.72).

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When we compared the change in the TRITC fluorescence (a measure of blood volume change) evoked by locomotion in GCaMP-nNOS mice to those in mice expressing GCaMP in pyramidal neurons we found a significantly smaller responses than in mice with calcium indicators in pyramidal neurons (Figure 7D Population TRITC intensity change (z-units), hSyn: 0.42 ± 0.16, LME difference from CaMKII: p<0.08, CaMKII: 0.75 ± 0.38, nNOS: 0.46 ± 0.18, LME difference from CaMKII: p<0.04). Pan-neuronal expression of GCaMP also decreased the CBV change, though not significantly. We do not know the origin of the difference between hemodynamic responses of nNOS and CaMKII-GCaMP mice, but one plausible cause could be that smaller locomotion-evoked response might be caused by the expression of a calcium indicator in the nNOS neurons. Calcium indicators will buffer calcium levels (Higley and Sabatini, 2008; McMahon and Jackson, 2018), reducing the amplitude of activity-dependent calcium transients by competing with endogenous calcium-binding proteins. This calcium buffering could reduce the production of NO in cells expressing the indicator because the activity of nNOS is calcium-dependent (Garthwaite, 2008).

There are several caveats to these experiments. The fluorescence signals from nNOS neurons, whether measured as absolute fluorescence or in the absolute changes in fluorescence, was substantially smaller than the signals from pan-neuronally expressed GCaMP or GCaMP expressed pyramidal neuron localized GCaMP signals. This is a consequence of the much lower number of GCaMP-nNOS neurons than the with the pan-neuronal or pyramidal neuron specific promoters (Figure 7A–C). This large difference in the absolute signals for these different conditions means that it would be inappropriate to draw any strong conclusions in differences in the calcium signal amplitudes or in correlation coefficients between blood volumes and neural activity. Calcium indicators are qualitative indicators of neural activity, as simultaneous calcium imaging and electrophysiology has found that the correlation between calcium signals and spiking activity is moderate (Harris et al., 2016; Theis et al., 2016; Pachitariu et al., 2018), and there are likely cell-type specific differences in calcium levels, indicator expression, and coupling of calcium changes to spiking that makes it untenable to make quantitative comparisons across calcium measurements of activity across different cell types. Different neuronal subtypes are known to have differing calcium buffering (Lee et al., 2000; Egger and Stroh, 2009; Matthews et al., 2013) and nitric oxide synthase expressing neurons show low levels of endogenous calcium binding proteins (Dun et al., 1994). These results show that nNOS neurons, like pyramidal neurons and other interneurons (Zhang et al., 2019), increase their activity during locomotion.

Relationship between neural activity and arterial dilation

One of the key utilities of hemodynamic imaging is that it allows us to make inferences about neural activity. As we have measured both neural activity and arterial diameter for multiple different perturbations, we sought to understand the relationship between them for different manipulations in pial arteries (Figure 8—figure supplement 1). We plotted the arterial diameter and gamma band power changes for each of the manipulations from the vehicle basal condition in Figure 8, with the basal and locomotion conditions connected by a line. A horizontal (left-right) shift means that neural activity is changed without a corresponding change in arterial diameter, while any vertical shift of the points means that there is change in arterial diameter without a corresponding change in neural activity. If there was a perfect, one-to-one ratio between gamma band power and arterial diameter, all of these points would lie along a line or a curve. If this is the case, by knowing the change in arterial diameter, one could infer the change in neural activity accurately from knowing the changes in arterial diameter. At the other extreme, if there were no relationship between neural activity and diameter, the points would be a shapeless blob. In this situation, it is not possible to infer neural activity from a change in arterial dilation.

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Within all the manipulations, we found that the increase in neural activity accompanying locomotion was accompanied by an arterial dilation. However, across conditions there was only a weak relationship between neural activity and arterial diameter. For example, the gamma band power was similar for both CaMKII-G(i) mice during locomotion and stationary nNOS-G(i) mice, but there were very large (~30%) differences in the arterial diameter. As another example, the change in arterial diameter was the same for stationary CaMKII-G(i) mice as for nNOS-G(i) during locomotion, even though there was an approximately threefold difference in neural activity A linear regression between change in neural activity and change in diameter (excluding the outlier muscimol) reveals no significant relationship between the two (p<0.12). We also looked at the relationship between power in other bands in the LFP (1–10 Hz and 10–40 Hz) and there was either a very weak relationship (for 10–40 Hz, p<0.04, R² = 0.04) or no significant relationship (1–10 Hz, p<0.05) (Figure 8—figure supplement 2). The lack of a strong relationship between arteriole diameter and LFP, which reports the summed activity of all neurons, though with large pyramidal neurons giving a disproportionally large contribution (Lindén et al., 2011; Einevoll et al., 2013; Pesaran et al., 2018), implies that a small set of nNOS expressing neurons can influence arterial diameter without influencing the LFP and vice versa.

Here, we showed that neural activity controls not only evoked arterial dilations, but also basal arterial diameter. Increases or decreases in overall neural excitability drove corresponding basal dilations or constrictions of arterioles. Surprisingly, modulation of the activity of pyramidal neurons had only small effects on basal and evoked arterial dilations. Neurons that express nNOS played an important role in controlling the basal dilation, as chemogenetic inhibition of nNOS positive neurons or NOS inhibition produced a change in basal diameter that was about half as big as seen when silencing activity with muscimol. Although nNOS positive neurons play an important role in controlling arterial diameter, changing their activity makes little contribution to the LFP. These results extend previous work showing that optogenetic stimulation of all interneurons (Anenberg et al., 2015; Uhlirova et al., 2016b), and nNOS positive interneurons in particular (Krawchuk et al., 2020; Lee et al., 2020) drive robust vasodilation, with optogenetic stimulation of pyramidal neurons being able to drive only small vasodilations (Vazquez et al., 2018). The small effect of manipulations on pyramidal cell activity on basal arterial diameter suggests that nNOS-positive neurons either do not receive strong local pyramidal neuron input, as large changes in pyramidal neuron firing had only small effects on basal and evoked dilations, or these inputs undergo short-term synaptic depression (Abbott et al., 1997). When synaptic depression is present at a synapse, it will eliminate the effects of changes in background firing rate (such as those caused by DREADDs) and only transmit the percentage changes in rate. Under normal circumstances in the somatosensory cortex of the awake behaving mouse, the activity of these nNOS-positive neurons is likely correlated to the activity of nearby neurons, as with other neurons, nNOS neurons receive cholinergic modulatory inputs (Williams et al., 2019; Williams et al., 2018), and cholinergic input increases during locomotion (Harrison et al., 2016). Because the activity of nNOS-expressing neurons will be correlated with other neurons, this explains the observed correlations between neural activity and vasodilation. Though increases in blood flow are usually correlated with neural activity, this is not always the case. Hemodynamic signals can occur without corresponding detectable increases in neural activity (Sirotin and Das, 2009; Cardoso et al., 2012; Cardoso et al., 2019), and neural activity increases are not always followed by corresponding increases in blood flow (Huo et al., 2014; Zhang et al., 2019). In the striatum, increases in neural activity can be accompanied by vasoconstriction and decreases in blood flow (Shih et al., 2009b; Shih et al., 2011). There are other known mismatches between neural and hemodynamic signals in the visual cortex (Maier et al., 2008; Boynton, 2011). Our data suggest a mechanism underlying these cases of neurovascular decoupling. It is possible that these mismatches are found when the activity of the vasodilatory nNOS neurons diverges greatly from the rest of the neural population.

These results also show that it is critical to perform quantitative, within-vessel measurements or other calibrations when testing the role of specific signaling pathways on evoked vasodilation. Here, we were able to get absolute measures of arterial diameters for the same vessels under both control and the manipulation conditions. However, hemodynamic signals are often measured ratiometrically relative to the baseline in the given condition, and changes in baseline vessel diameter can confound these ratiometric signals (Cohen et al., 2002; Figure 8—figure supplement 3). Whenever responses in two different groups of subjects are compared (e.g. transgenic vs. wildtype), the potential for changes in the baseline are a confound. However, any changes in the baseline in population can be detected by dilating the vessels with isoflurane (Cudmore et al., 2017) or CO₂ (Hutchinson et al., 2006), or testing the basal tone of the vessel in vitro (Adebiyi et al., 2007). These tests will reveal if the baseline changes, as the apparent maximal dilation/relaxation will be reduced. Our results show the critical importance of these controls when trying to establish the mechanisms and cellular underpinnings of neurovascular coupling.

There are several caveats to our work. First, the net effect of our chemogenetic manipulations on neural activity depend on the cellular machinery and network interactions in the local neural circuits. Because chemogenetic manipulations alter excitability via endogenous G-protein-coupled ion channels, there will be some variability in their effects between cell-types, and between G(i) and G(q) DREADDs in the same cells, as the amplitude of the excitability modulation depends on the compliment of ion channels present. Our viruses did not infect all nNOS neurons, and were not completely specific. Expression of chemogenetic proteins may also affect basal activity levels in neurons (Saloman et al., 2016), which is why whenever possible we have tried to use both pharmacological and chemogenetic manipulations (e.g. G(i)-DREADDs in nNOS neurons and NOS inhibitors) to generate converging lines of evidence. Additionally, increasing and decreasing the activity of a single neuron type does not always have symmetric effects on network activity due to interactions within the cortical circuit (Phillips and Hasenstaub, 2016). Similarly, pharmacological effects may not be symmetrical due to levels of baseline activity or modulatory tone. For example, Substance P receptors may have a low level of basal activation in the cortex of awake mice, so blocking them may only have a small effect on the activity of type 1 nNOS neurons in the cortex. In vitro studies have shown that activation of Substance P receptors drives large increases in activity (Endo et al., 2016; Williams et al., 2019; Williams et al., 2018), potentially accounting for the asymmetry of vascular responses to the application of blockers and activators of these receptors. Simulations have shown that the location of NO production relative to the arteriole has a large impact on its efficacy (Haselden et al., 2020), so the location of the infected neurons relative to the arterioles may cause some variability. We performed our experiments in awake mice, as anesthetics cause large decreases in brain metabolism, cardiovascular output, and ongoing neural activity (Gao et al., 2017), but there could be some variability associated with the mice being awake. However, the locomotion-evoked hemodynamic responses were not due to systemic changes in cardiovascular output, as the locomotion-evoked vasodilation is spatially localized to the FL/HL representation of the somatosensory cortex (Huo et al., 2014; Huo et al., 2015b; Huo et al., 2015a; Zhang et al., 2019), not affected by drugs that alter heart rate and blood pressure (Huo et al., 2015a), and blocked by local neural silencing (Figure 1E). Although we did not monitor heart rates here, head-fixed mice show heart rates comparable to freely moving mice (Gehrmann et al., 2000), and fluctuations in heart rates in head-fixed mice do not explain spontaneous and evoked changes in blood flow or vasodilation (Drew et al., 2011; Winder et al., 2017). None of the manipulations of neural activity used here produced significant changes in the amount of locomotion, so their effects cannot be attributed to changes in behavior. Because many of the manipulations of neural activity (i.e. CaMKIIa-G(i) DREADDs) resulted in minimal changes of arterial diameter across conditions, systemic fluctuations were unlikely to play a substantial role in our preparation. Interestingly, none of our manipulations substantially increased the sensory-evoked dilations above those in control conditions, although some drove large increases in neural activity and/or basal arterial diameter. It seems the dilations that occur during locomotion (~20% above the basal diameter) are near saturation for cerebral arteries under normal circumstances, as increasing the activity of all neurons or nNOS positive neurons were unable to raise the evoked dilation substantially above this level.

Our results suggest a model where approximately half of the dynamic range in the basal and evoked blood arterial diameter is controlled by a small group of neurons and the rest is controlled by other neurons and astrocytes. Any damage to or dysfunction of nNOS neurons could result in decreased basal blood flow, regardless of the metabolic need. Importantly, changes in activity patterns of these neurons will alter basal diameter of arteries, which is known to affect the amplitude of fMRI signals (Cohen et al., 2002). Simulations have shown that cerebral arteries account for approximately half of the resistance in the cerebral vasculature (Schmid et al., 2017; Rungta et al., 2018), so arterial diameter will play an important role in setting basal and evoked blood flow levels. There is a decline in the number of interneurons, particularly nNOS-expressing interneurons, with aging (Miettinen et al., 1993; Necchi et al., 2002), and the removal of their tonic vasodilatory signal could contribute to decreases in cerebral blood flow that are thought to lead to dementia (Wolters et al., 2017). Indeed, alterations of nNOS expression have been implicated in Alzheimer’s disease (Han et al., 2019b) and chronic stress (Han et al., 2019a). Protecting these neurons from insults and damage could be a promising strategy for preventing neurovascular disorders.

The Matlab code and data to generate the figures have been uploaded to Dryad. The DOI for download is here: https://doi.org/10.5061/dryad.b8gtht79h.

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   Data from: nNOS-expressing interneurons control basal and behaviorally-evoked arterial dilation in somatosensory cortex of mice.

   https://doi.org/10.5061/dryad.b8gtht79h

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Author details

1. Christina T Echagarruga

   Bioengineering Graduate Program, Pennsylvania State University, University Park, United States

   Contribution

   Conceptualization, Data curation, Software, Formal analysis, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

2. Kyle W Gheres

   Molecular, Cellular, and Integrative Biology Graduate Program, Pennsylvania State University, University Park, United States

   Contribution

   Conceptualization, Resources, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-7568-9023

3. Jordan N Norwood

   Cell and Developmental Biology Graduate Program, Pennsylvania State University, University Park, United States

   Contribution

   Funding acquisition, Investigation, Visualization, Writing - original draft

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8093-5938

4. Patrick J Drew

   1. Bioengineering Graduate Program, Pennsylvania State University, University Park, United States
   2. Molecular, Cellular, and Integrative Biology Graduate Program, Pennsylvania State University, University Park, United States
   3. Cell and Developmental Biology Graduate Program, Pennsylvania State University, University Park, United States
   4. Departments of Engineering Science and Mechanics, Biomedical Engineering, and Neurosurgery, Pennsylvania State University, University Park, United States

   Contribution

   Conceptualization, Software, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing

   For correspondence

   PJD17@PSU.EDU

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-7483-7378

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