All experiments were performed in accordance with relevant guidelines and regulations, including a protocol approved by the Institutional Animal Care and Use Committees of Yale University. For all surgical procedures, male or female adult (40–100 days old) mice were anesthetized with a mixture of ketamine (90 mg kg^–1) and xylazine (10 mg kg^–1). Anesthesia was supplemented as needed to maintain areflexia, and anesthetic depth was monitored periodically via the pedal reflex. Animal body temperature was maintained at approximately 37.5°C using a heating pad placed underneath the animal. For recovery manipulations, animals were maintained on the heating pad until awakening. Local anesthetic (1% bupivacaine, McKesson Medical) was applied to all incisions. Respiration was recorded with a piezoelectric sensor.

For virus injections, a small (<1 mm) craniotomy was performed and AAV1 expressing ArcLight or GCaMP (injection volumes between 0.2 and 2 μl) was injected slowly over 10–15 min using a glass capillary (tip diameter 8–15 μm) ∼500 μm below the surface of the bulb. The ArcLight virus was generated at the Penn Vector Core and had a titer of 4.6e12 genome copies (GC) ml^–1. The GCaMP3 and GCaMP6f virus were acquired from the Penn Vector Core and had titers of 4.7e13 GC ml^–1 and 4.3e13 GC ml^–1, respectively. We waited at least 10 days for expression of the virus prior to performing optical measurements.

The venerable, but not very reliable, method first described by Wachowiak and Cohen (2001) was used to load calcium dye into the olfactory sensory neurons. Mice were anesthetized, placed on their back, and an 8 μl mixture of 8/0.2% calcium dye/Triton-X was drawn into a flexible plastic syringe, which was inserted ∼10 mm into the nasal cavity. Using a Hamilton syringe, four injections of 2 μl of the dye/triton mixture was infused into the nose every 3 min. Mice were allowed to recover for at least 4 days prior to optical measurements. The organic calcium dye Fura dextran (F-3029) was from Thermo Fisher Scientific, Waltham, MA, United States. Cal-590 dextran is from AAT Bioquest (Sunnyvale, CA). The excitation spectra of these calcium dyes are well separated from that of many GEVIs and GECIs.

For epifluorescence or 2-photon imaging fluorescence measurements, mice were anesthetized, and the bone above both of the hemi-bulbs was either thinned or removed. The exposure was covered with agarose and then sealed with a glass coverslip.

Epifluorescence imaging was performed by illuminating the dorsal surface of the bulb with 150 W Xenon arc lamp (Opti Quip) on a custom antique Leitz Ortholux II microscope. The light was reflected by a 515 nm long-pass dichroic mirror before being delivered to the sample via an objective lens (various, typically a 4× 0.16NA or 10× 0.4NA lens). The fluorescence emission above 530 nm was recorded with a NeuroCCD-SM256 camera (RedShirtImaging, Decatur, GA, United States) with 2 × 2 binning at 40 or 125 Hz.

Two-photon imaging was performed with a modified MOM two-photon laser-scanning microscope (Sutter Instruments). 2-photon excitation was achieved using a Coherent Discovery laser (wavelengths between 940 and 980 nm), and laser scanning was performed with an 8 kHz resonant scanner (Cambridge Technology). Fluorescence was passed through a 510/84 nm bandpass filter and detected with a GaAsP PMT (Hamamatsu, Japan). Power delivered to the sample ranged from 75 to 140 mW as determined using a power meter (Thorlabs) placed underneath the microscope objective.

ArcLight A242-2A-nls-mCherry was constructed by fusing ArcLight A242 (Jin et al., 2012) with the self cleaving 2A peptide sequence followed by nuclear localized mCherry (Kim et al., 2012). To allow constitutive expression of the voltage sensor under the CAG promoter in wild type (C57BL/6) mice, ArcLight A242-2A-nls-mCherry was inserted into the aavCAG Jx vector (Gene bank JN898959) in a forward orientation. An adeno-associated virus serotype 1 (AAV1) of the ArcLight construct was produced at the Penn Vector Core at the University of Pennsylvania. For experiments with GCaMP3 and GCaMP6f, we used AAV1s expressing the gene under the human synapsin 1 (Figure 1B) promoter (#AV-1-PV1627 and AV-1-PV2822 purchased from the Penn Vector Core). For the TH-Cre targeting experiments, a Cre-dependent ArcLight virus was used (AV1.EF1a.ArcLight.DIO, Penn Vector Core).

Protocadherin 21 (Pcdh21) (Nagai et al., 2005) embryos were acquired from RIKEN BioResource Center (No. RBRC02189) and recovered by the Yale Genome Editing Center. OMP-GCaMP3 transgenic mice were a gift from T. Bozza. TH-Cre transgenic line were a gift from Matthew McGinley (Jax Stock #008601). Thy1-GCaMP6f GP5.11 transgenic mice were acquired from Jax (Stock #024339). Tbx21-Cre transgenic mice were acquired from Jax (Stock #024507) and crossed to a floxed GCaMP6f reporter transgenic mouse (Jax Stock #024105). Animals used in the study were confirmed to express the sensor via genotyping by Transnetyx (Cordova, TN, United States), and by visual inspection (in vivo and histologically).

For all experiments, odorant-evoked signals were collected in consecutive (1–20) trials separated by a minimum of 45 s. Individual trials were manually inspected and were discarded if they exhibited obvious movement artifact. Trials were averaged after being aligned to the time of the first inspiration following the odorant presentation. Individual glomeruli were visually identified via a frame subtraction analysis that identified stimulus activated glomeruli. The activation maps were generated by subtracting the temporal average of the 1–2 s preceding the stimulus from a 1 s temporal average at the signal peak using frame subtraction in NeuroPlex (RedShirtImaging). Spatial filtering is indicated in the figure legend. The response maps were depixelated for display. Response amplitudes were calculated as the difference between the peak of the response, and the 1–2 s period preceding the stimulus. Fluorescence signals were converted to ΔF/F by dividing the spatial average of each glomerulus by resting fluorescence (the average of the time period prior to the odor presentation).

The input and output measurements in Figure 5 were performed alternatively using Fura dextran and ArcLight. The 0.04% odor concentration did not evoke any detectable input glomerular response, and was subtracted from the input for the traces and values in (C) and (D). The evoked signal size for each concentration was normalized to the signal evoked at 11% of saturated vapor. To illustrate the similarity of the output maps, in Figure 5 each output response map was scaled so that all five maps had the same maximum and minimum intensity values. The input map for 11% saturated odor was scaled to have the same maximum and minimum brightness values as the five output maps. The input maps for the lower odorant concentrations were first scaled by the same scaling factors that were used for the output maps and are shown using the same maximum and minimum brightness scale as the 11% odorant map.

The signal-to-noise analysis was performed by measuring the amplitude of the ArcLight response to the first sniff of the odorant vs. the response immediately preceding the odorant. This analysis was performed in 10 preparations in averaged trials that were aligned to the first sniff following the odorant. An ROI that evoked the largest signal for that trial was selected for each preparation.

For the 2-photon input and output measurements in Figure 7, glomerular responses were normalized to the signal evoked at the highest odorant concentration (6% of saturated vapor). The responses from all identified individual glomeruli were measured (as in Figure 7B), and averaged together to form the values plotted in Figure 7C. Statistical significance for Figure 7 was measured using a Wilcoxon rank sum test comparing the average of input vs. output preparations at each concentration.

For the ArcLight measurements from TH expressing interneurons in Figure 8, functional signals were measured in 5 preparations, of which histology was processed and examined to confirm expression in the expected locations in 4 of them. The activity maps in Figure 8B are scaled to the minimum and maximum values evoked by the highest odorant concentration. The data in Figure 8D come from concentration series performed in 3 of the preparations. For a given odor, all of the activated glomeruli were identified, measured and then averaged together for each odor concentration to give each data point. The ΔF/F values were normalized to the highest odor concentration used for that preparation (11% of saturated vapor). Responses to 3 odorants were measured in one preparation, only one odorant was used in the other two preparations. The input and output data in Figure 8D (red and black lines) are taken from Storace and Cohen (2017). The statistical comparison of the data in Figure 8D was performed using a Wilcoxon rank sum test, and similar results were obtained whether the comparisons were performed across preparations (N = 3 independent TH measurements), across odor presentations (5 independent TH measurements), or when collapsing all normalized values to the lower odor concentrations (yielding 9 independent TH measurements).

Odorants (Sigma-Aldrich) were diluted from saturated vapor with cleaned air using a flow dilution olfactometer (Vucinic et al., 2006). The olfactometer provided a constant flow of air blown over the nares. Through a separate set of tubing, odorants were constantly injected into the olfactometer, but sucked away via a vacuum that was switched off during odorant presentation. Different odorants were delivered using separate Teflon tubing. Odorants were delivered at different concentrations (between 0.1 and 6% of saturated vapor). Ethyl tiglate, methyl valerate, 2-heptanone, a mixture of the 3 odorants, and n-butyl acetate were used in these experiments. The time course and relative concentrations of odorants presented by the olfactometer was confirmed using a photo-ionization detector (Aurora Scientific Inc., Aurora, ON, Canada) at the beginning of experiments.

ArcLight was used to record the population voltage signals from mitral and tufted cell dendritic tufts in each glomerulus. ArcLight was expressed using an adeno-associated virus serotype 1 (AAV1) that co-expressed nuclear localized mCherry to facilitate identification of the transduced neurons (Figure 1A). GECIs GCaMP3 and GCaMP6f were similarly expressed via AAV transduction. Sensor expression was examined by comparing the fluorescence of the GEVIs and GECIs histologically. The ArcLight (Figure 1D) and GCaMP3 (Figure 1E) vectors had similar expression patterns in the external bulb layers, and were both largely selective for mitral and tufted neurons (Figures 1D,E). We presume that the labeled glomeruli are the result of sensor expression in the mitral/tufted neuron primary dendritic tufts. These AAV1 vectors were selective for restricted cell populations in the bulb: this specificity may be due to a combination of the AAV serotype and the promoter selectivity.

Different odorants evoke distinct spatial and temporal patterns of glomerular activation in the mouse olfactory bulb (Rubin and Katz, 1999; Wachowiak and Cohen, 2001; Spors and Grinvald, 2002). AAV vectors carrying the genes for ArcLight and GCaMP3 or GCaMP6f (Figures 1A,B) were injected into separate bulb hemispheres (Figure 1C) between 10 and 50 days prior to optical measurements. Expression tended to be widespread in the injected hemispheres.

The ArcLight voltage signals were compared with those from the GECIs GCaMP3 (Tian et al., 2009) and GCaMP6f (Chen et al., 2013) using simultaneous recordings from opposite olfactory bulb hemispheres. Odor-evoked responses could be detected in the glomerular layer in single trials from all three sensors. ArcLight’s temporal kinetics were substantially faster than both GCaMPs but the signal-to-noise ratios were lower.

Odorants presented for 0.3 s often coincided with a single inhalation, which resulted in ArcLight and GCaMP3 (Figure 2A, red vs. green trace) or ArcLight and GCaMP6f (Figure 2B, red vs. blue trace) fluorescence signals that were easily detected in single trials. Depolarizations measured with ArcLight and increases in calcium measured with the GCaMPs are shown as upward signals.

The ArcLight and GCaMP signals had different amplitudes, time courses and signal-to-noise ratios. While ArcLight had a much smaller fractional fluorescence change (ΔF/F) than either GCaMP, ArcLight had a faster onset, rise time, and decay (Storace et al., 2015). With a longer odorant pulse that elicits two odorant inhalations (Figures 2C,D) the ArcLight signal returns almost all the way to the baseline between the two inhalations while the GCaMP signals either have only an inflection (Figure 2C) or a modest return toward the baseline (Figure 2D).

While the signal-to-noise ratios of the ArcLight signals are relatively large, the ArcLight signals in Figure 2 appear noisier than those of the GCaMPs. We attempted to quantify the ArcLight signal-to-noise ratio by measuring the difference between the odor-evoked change, and the pre-odor oscillations. On average the largest signal evoked by an odor was 1.83% (±0.17), and the baseline oscillation was 0.47% (±0.05). The fold-change of the odor vs. baseline was 4.07 (±0.28). However some of this baseline “noise” is actually a real respiratory signal which is emphasized more in the ArcLight signals because of the faster ArcLight response (Figures 2B,D). We compared the timing of baseline ArcLight and GCaMP signals. Consistent with the notion that the baseline signals are physiological and not movement artifacts, the ArcLight signals preceded the GCaMP signals.

The results from repeated imaging trials were relatively consistent (Storace et al., 2015), which demonstrates that substantial photo-bleaching or photodynamic effects were not present with either ArcLight or the GCaMPs at the incident light intensities which we used. Our comparison of intrinsic signal activity from injected and control hemispheres did not detect a pharmacological effect of ArcLight on normal bulb function. However, continued attention to the possibility of photodynamic and phototoxic effect is desirable. The ArcLight signals were sufficiently large and fast, which made them clearly distinct from the intrinsic light scattering and flavoprotein autofluorescence signals.

The differences in time course and respiration coupling that we found between ArcLight and the two GCaMPs are likely due to a combination of differences in the time courses of the cellular voltage and calcium changes as well as the response speeds of the different sensors. To further understand the differences in signal time courses, we compared the temporal kinetics of the three kinds of protein sensors.

ArcLight had onset and offset time constants of 20 and 30 m s, respectively, for 80 mV depolarizing steps in HEK293 cells (Figure 3A). GCaMP3 has onset time constants of 1100 and 250 m s for calcium steps to 250 and 490 nM (Figure 3B, green line, time constants of 1100 and 250 m s) (Akerboom et al., 2012). GCaMP6f is about 50% faster for calcium concentration steps to ∼ 510 and ∼ 940 nM (Figure 3B, blue line). Figures 3C–E compares the temporal responses for ArcLight (C), GCaMP3 (D), and GCaMP6f (E) for selected steps of voltage and calcium. The GCaMP3 and GCaMP6f decay constants are reported to be ∼150 m s (Sun et al., 2013) and 71 m s (Kim et al., personal communication), respectively. These observations were done when starting at a high calcium concentration, however the effect of different calcium steps on these GECI decay times has not been reported. Clearly, ArcLight has faster kinetics than either of the two GCaMPs, which may explain some of its improved ability to detect individual inspiratory responses.

The ArcLight signal likely reflects the average of all of the mitral/tufted dendritic processes in the glomerular region of interest. Electrode measurements have shown that individual mitral and tufted cells can produce action potentials that are tightly linked to the respiration cycle (Dhawale et al., 2010; Carey and Wachowiak, 2011; Shusterman et al., 2011). Thus, our ArcLight measurements appear to accurately reflect the respiration driven envelope of mitral/tufted cell spiking activity (Rojas-Libano et al., 2014).

The onset and decay kinetics of the GCaMP sensor responses to step changes in calcium result from the calcium binding and unbinding rates. The mechanism generating the ArcLight signal results from a dimerization of the super ecliptic pHluorin of two ArcLight molecules which is then affected by the movement of S4 in the voltage sensitive domain (Kang and Baker, 2016). A pH fluorescent protein like super ecliptic pHluorin is necessary but the ArcLight signal is not the result of a change in pH (Han et al., 2014; Kang and Baker, 2016).

An approach was developed to measure both the input and output of the same glomeruli in the mouse olfactory bulb. Spectrally distinct sensors of neural activity were used; one in the olfactory receptor neurons (input), the other in the mitral and tufted cells (output). This approach employed both anatomical and genetic targeting. Olfactory receptor neurons (input) were labeled via nasal infusion with an organic calcium sensitive dye (Figure 4A; Friedrich and Korsching, 1997; Wachowiak and Cohen, 2001). In the same preparation, GEVIs or GECIs were targeted to mitral and tufted (output) cells using cre-dependent AAVs in a transgenic mouse (Protocadherin 21) that expresses cre recombinase in the mitral and tufted cells (Figure 4A; Nagai et al., 2005). Appropriate targeting of the sensors in the expected locations was confirmed via histological examination (Figure 4B).

Because the input and output sensors had substantially different excitation spectra, input vs. output signals could be measured in the same glomeruli by changing the excitation wavelength. Odor-evoked activity was measured using epi-fluorescence imaging across ∼2 log units of odorant concentration in freely breathing anesthetized mice. Input and output measurements were made from the same hemi-bulb using the calcium dye Fura dextran as the input sensor, and the protein voltage sensor ArcLight as the output sensor. The Fura dextran input signal was imaged using 380 nm excitation light. The ArcLight output signals were measured with an excitation light of 480 nm. Fluorescence time courses were recorded from regions of interest corresponding to activated glomeruli. These time courses reflect the population average of the olfactory receptor neuron axon input activity or the population average of the mitral and tufted neuron output activity from individual glomeruli.

In the experiment illustrated in Figure 5, signal measurements were made from 10 glomeruli at five odorant concentrations. The output frame subtraction maps at the five odorant concentrations are more similar to each other than are the input maps (Figure 5A). The similarity of the input vs. output maps at different odor concentrations was quantified by performing a spatial correlation of each map with one another (Figure 5B). The output maps had a significantly higher spatial correlation than the input maps (p < 0.05, two-sample t-test). The signals from the 10 input and output glomeruli (Figure 5C, ROIs) also demonstrate that the input glomeruli have a considerably steeper function of odor concentration than the output glomeruli. The input exhibited no detectable signal at the lowest odorant concentration (0.04% saturated vapor, not shown), and very few had a signal at 0.12% saturated vapor. In contrast, an output signal was detected for all glomeruli at an odorant concentration of 0.04%.

The amplitudes of the odor-evoked input and output signals for each glomerulus were normalized to the response evoked by the highest odorant concentration (11% of saturated vapor). Responses from individual glomeruli are plotted as the thin lines in Figure 5D, and the mean evoked signals are shown in the thick lines (red for output; black for input). Reducing the concentration of the odor presentation from 11 to 0.12% reduced the input amplitude to decrease by more than 95%, while the output decreased by only 40% (p < 0.001). This result was similarly consistent in a population average across 13 preparations (Storace and Cohen, 2017). Thus both the output activity maps and the output signal size are much less concentration dependent than are the input maps and signals. The olfactory bulb contributes to the perception of concentration invariance of odor recognition.

In another mouse we measured the concentration dependence of the output maps using two different odorants, methyl valerate and 2-heptanone. Figure 6A again shows that for each odorant the output maps do not change markedly over a substantial range of odorant concentration. Nonetheless the output maps are markedly different for the two odorants. Figures 6B,C show that the map correlations for the individual odorants are relatively large while the correlations across odorants are very small. Thus the bulb contributes to the perception of concentration invariance while maintaining an odorant specific output.

One concern about the results illustrated in Figures 5C,D (and in similar figures in Storace and Cohen, 2017) is the possible contribution of the out-of-focus mitral/tufted lateral dendrite signals to the measurements. Accordingly, we have repeated the measurements of input and output concentration dependence using 2-photon microscopy where the depth-of-field is <10 microns instead of the >100 microns of wide-field microscopy. These experiments were carried out using different animals for each input and output measurement. Figure 7A illustrates the results from one glomerulus from two different animals. The input signals decline markedly as a function of concentration while the output signal is much less concentration dependent. Figure 7B shows a plot of signal size vs. odorant concentration for all of the identified glomeruli in the two preparations used in (a). The normalized response of the output was significantly higher than the input for all tested concentration (p < 0.05; Input: 31 glomeruli; Output: 37 glomeruli). Figure 7C shows that across a population the average input signal (N = 5 preparations; thick black line) declines much more rapidly than the average output signal (N = 7 preparations; thick red line) (Figure 7C) (p < 0.05 using a Wilcoxon rank sum test for all comparisons). The results in Figure 7 are very similar to those published earlier (Storace and Cohen, 2017) using wide-field microscopy and thus they alleviate the concern that the wide-field conclusion might have been in error because of contamination from mitral/tufted lateral dendrite signals.

We conclude that the olfactory bulb contributes to the perception that the quality of an odorant is considered the same over a range of concentrations. It has been hypothesized that the combination of odorant receptors that are activated by an odorant determines odor identity.

However, previous studies have found that the olfactory bulb glomerular input maps were a confound of odorant identity and concentration (Wachowiak and Cohen, 2001; Bozza et al., 2004). While the activated receptors are critical for odor identification, our results show that odorant identity is determined by the olfactory bulb output. The intensity information may be normalized in the olfactory bulb, and thus the bulb in part removes the qualitative effect of odorant concentration so that odor identity is represented in the output maps. However, the mitral and tufted cell population average still maintains some concentration dependence so that intensity information is not entirely discarded.

The signal-to-noise ratio in the Fura dextran input recordings has a threshold that is ∼5% of the largest signal. If the largest signal represents the activation of ∼1000 olfactory receptor neurons, then the smallest detectable signal would reflect the average activity of less than 50 receptor neurons. The activity of <50 receptor neurons is enough to generate substantial output signals and enough to enable odorant recognition (Homma et al., 2009). However, this argument assumes linearity of the sensor signal with calcium concentration, while calcium signals are typically nonlinear.

The possibility that the olfactory bulb could be involved in normalizing the well-described concentration dependence of the olfactory sensory neurons was proposed by Thomas Cleland (Cleland et al., 2007, 2011). Since that suggestion there is a growing body of supporting evidence across multiple species including Drosophila (Asahina et al., 2009), Zebrafish (Niessing and Friedrich, 2010), and mouse (Banerjee et al., 2015; Sirotin et al., 2015; Storace and Cohen, 2017; this paper). A strength of the results in Storace and Cohen (2017) is that the input and output of the olfactory bulb were measured in the same preparation (in some cases simultaneously) allowing a direct comparison to be made. Candidate mechanisms include different types of interneurons with distinct anatomical connections that could facilitate communication across glomeruli, and the ability of some cell types to bidirectionally modulate circuits (Yaksi and Wilson, 2010; Zhu et al., 2013; Banerjee et al., 2015). The results presented here and in other reports (Banerjee et al., 2015; Storace and Cohen, 2017; Bolding and Franks, 2018) also demonstrate that not all concentration information is discarded in the olfactory bulb. It seems likely that the olfactory bulb is performing computations that are critical for downstream targets (e.g., in the Piriform Cortex) to perform invariant object identification. Recent evidence has shown that while the olfactory bulb mitral/tufted cells are relatively concentration invariant, piriform cortex cells are even less sensitivity to concentration, a function that involves feedback from the olfactory cortex to the olfactory bulb (Bolding and Franks, 2018). Thus, concentration invariant odorant perception likely involves dynamic processing across multiple brain regions. Nonetheless, it is clear that the olfactory bulb is involved in a critical processing step to normalize the highly concentration dependent olfactory bulb input.

Measuring the contribution of different olfactory bulb cell types may help reveal the mechanisms that shape the transformations occurring in the olfactory bulb. Here, we targeted ArcLight to bulb tyrosine hydroxylase (TH) interneurons with an AAV1 cre dependent ArcLight vector. The TH interneurons are restricted to the glomerular layer and include more than one interneuron type (Pignatelli et al., 2005; Pignatelli and Belluzzi, 2017). Figure 8A illustrates the DAPI and ArcLight expression. The ArcLight expression is restricted to cells and processes in the juxtaglomerular layer consistent with the possibility that the expression is restricted to TH periglomerular interneurons.

Activity maps for the odorant responses (Figure 8B) were made by subtracting imaging frames prior to the odorant stimulus from frames acquired during the response. Maps for three concentrations of three odorants are illustrated. These maps are very concentration dependent suggesting that they reflect the olfactory receptor cell input to the bulb rather that the mitral/tufted cell output (Banerjee et al., 2015). The time course of the ArcLight fluorescence changes at three concentrations from 11 glomeruli are shown in Figure 8C (single trials). Figure 8D is a plot of normalized response amplitude vs. odor concentration of the glomerular TH measurements, overlaid with the population input and output measurements from Storace and Cohen (2017).

The normalized TH concentration dependence was not statistically different than the input, and was significantly smaller than the output (p < 0.05; Wilcoxon rank sum). While these measurements are from a more limited dataset and performed in different animals, the result support other studies that have proposed that these cells carry the concentration dependent information from the bulb input. These signals may be transmitted throughout the bulb via long-range lateral connections that are found in many of these cells (Aungst et al., 2003; Zhu et al., 2013; Banerjee et al., 2015).