Research Report: Regular Manuscript Differential impacts of repeated sampling on odor representations by genetically-defined mitral and tufted cell subpopulations in the mouse olfactory bulb https://doi.org/10.1523/JNEUROSCI.0258-20.2020
Cite as: J. Neurosci 2020; 10.1523/JNEUROSCI.0258-20.2020 Received: 3 February 2020 Revised: 16 June 2020 Accepted: 18 June 2020
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1 Title 2 Differential impacts of repeated sampling on odor representations by genetically-defined mitral 3 and tufted cell subpopulations in the mouse olfactory bulb 4 5 Abbreviated title 6 Reformatting of odor representations by sniffing 7 8 Journal Section 9 Systems/Circuits 10 11 Authors 12 Thomas P. Eiting, Matt Wachowiak 13 14 Department of Neurobiology and Anatomy, University of Utah, Salt Lake City, UT 15 16 Corresponding author 17 Thomas P. Eiting 18 Department of Neurobiology and Anatomy 19 University of Utah 20 Salt Lake City, UT 84103 21 [email protected] 22 23 Number of pages: 36 24 Number of figures: 6 25 Abstract: 250 words 26 Introduction: 590 words 27 Discussion: 1335 words 28 29 Conflicts of interest 30 The authors declare no competing financial interests 31 32 Acknowledgments 33 We thank S. Burton, A. Moran, S. Short, and I. Youngstrom for helpful comments, G. Vasquez 34 for help with virus injections, and J. Ball and R. Kummer for help with animal husbandry and 35 histological processing. We also thank two anonymous reviewers, whose constructive feedback 36 improved this paper substantially. This work was supported by funding from NIH 37 (F32DC015389 to TPE and DC006441 to MW). 38
1
39 Abstract
40 Sniffing—the active control of breathing beyond passive respiration—is used by
41 mammals to modulate olfactory sampling. Sniffing allows animals to make odor-guided
42 decisions within ~200 ms, but animals routinely engage in bouts of high-frequency sniffing
43 spanning several seconds; the impact of such repeated odorant sampling on odor representations
44 remains unclear. We investigated this question in the mouse olfactory bulb, where mitral and
45 tufted cells (MTCs) form parallel output streams of odor information processing. To test the
46 impact of repeated odorant sampling on MTC responses, we used two-photon imaging in
47 anesthetized male and female mice to record activation of MTCs while precisely varying
48 inhalation frequency. A combination of genetic targeting and viral expression of GCaMP6
49 reporters allowed us to access mitral (MC) and superficial tufted cell (sTC) subpopulations
50 separately. We found that repeated odorant sampling differentially affected responses in MCs
51 and sTCs, with MCs showing more diversity than sTCs over the same time period. Impacts of
52 repeated sampling among MCs included both increases and decreases in excitation, as well as
53 changes in response polarity. Response patterns across simultaneously-imaged MCs reformatted
54 over time, with representations of different odorants becoming more distinct. Individual MCs
55 responded differentially to changes in inhalation frequency, whereas sTC responses were more
56 uniform over time and across frequency. Our novel results support the idea that MCs and TCs
57 comprise functionally distinct pathways for odor information processing, and we suggest that the
58 reformatting of MC odor representations by high-frequency sniffing may serve to enhance the
59 discrimination of similar odors.
60
61
2
62 Significance Statement
63 Repeated sampling of odorants during high-frequency respiration (sniffing) is a hallmark
64 of active odorant sampling by mammals, however the adaptive function of this behavior remains
65 unclear. We found distinct effects of repeated sampling on odor representations carried by the
66 two main output channels from the mouse olfactory bulb, mitral and tufted cells. Mitral cells
67 showed more diverse changes in response patterns over time as compared to tufted cells, leading
68 to odorant representations that were more distinct after repeated sampling. These results support
69 the idea that mitral and tufted cells contribute different aspects to encoding odor information, and
70 they indicate that mitral cells (but not tufted cells) may play a primary role in the modulation of
71 olfactory processing by sampling behavior.
72
3
73 Introduction
74 Olfaction, a key sensory modality for mammals, is an important model system for
75 understanding how active sensation contributes to sensory processing (Uchida et al., 2006;
76 Wachowiak, 2011; Jordan et al., 2018b). Sniffing—the active control of breathing beyond
77 passive respiration—is used by mammals to modulate olfactory sampling. Sniffing provides
78 temporal control over olfactory sensation and can increase access to odor information by
79 increasing the flow of odorants through the nasal cavity, and also by allowing multiple samples
80 of odorant in a shorter time (Zhao et al., 2006; Verhagen et al., 2007; Courtiol et al., 2011; Rygg
81 et al., 2017). Repeated high-frequency (3 - 10 Hz) inhalations are a hallmark of sniffing behavior
82 in most mammals, including rodents (Youngentob et al., 1987; Laska, 1990; Thesen et al., 1993;
83 Wesson et al., 2008a). While mice and rats can discriminate odors in as little as one sniff (150-
84 200 ms (Uchida and Mainen, 2003; Abraham et al., 2004), they frequently exhibit longer sniffing
85 bouts lasting several seconds (Welker, 1964; Wesson et al., 2008a). How repeated sampling
86 influences olfactory processing by neural circuits in the olfactory bulb (OB) or elsewhere is not
87 well understood.
88 Previous work has shown that rapid sniffing induces adaptation of olfactory sensory
89 inputs to the OB (Verhagen et al., 2007); more recently, we and others have found that inhalation
90 frequency modulates subthreshold membrane potential and spiking patterns in mitral and tufted
91 cells (MCs and TCs), the two major subclasses of olfactory bulb output neurons (Bathellier et al.,
92 2008; Carey and Wachowiak, 2011; Díaz-Quesada et al., 2018; Jordan et al., 2018b). Multiple
93 functions of this frequency-dependent modulation have been proposed, including enhancing
94 olfactory sensitivity, increasing the salience of odorants against a background, and improving
95 fine-scale odor discrimination.
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96 There is substantial evidence that mitral cells (MCs) and tufted cells (TCs) have distinct
97 odorant response properties and likely contribute differentially to encoding odor information
98 (Nagayama et al., 2004; Griff et al., 2008; Fukunaga et al., 2012; Jordan et al., 2018a; Short and
99 Wachowiak, 2019). Putative mitral and tufted cells also respond to odorants differently during
100 brief bouts of high-frequency sniffing (Jordan et al., 2018b). However, how - or whether - these
101 populations differentially represent odorants during repeated sampling of odorants remains
102 unclear. Ultimately, because odor coding involves combinatorial activity patterns across many
103 cells, understanding how sniffing impacts odor representations requires recording from multiple
104 cells simultaneously, ideally using genetic and strict anatomical criteria to define subpopulations
105 independent of their functional properties.
106 Here, we addressed these knowledge gaps by imaging from genetically- and
107 anatomically-defined subsets of MCs and TCs during repeated odorant sampling at different
108 inhalation frequencies. We use an artificial inhalation paradigm in anesthetized mice to allow for
109 precise reproduction of odorant sampling regimes and comparison of responses across cell type
110 subpopulations, with minimal impact of centrifugal inputs or other behavioral state-dependent
111 factors. We found substantial population-level differences between MCs and a subset of TCs
112 defined by their superficial location and their expression of the peptide transmitter
113 cholecystokinin (CCK). The CCK+ superficial TC (sTC) population showed stronger coupling to
114 individual inhalations, few suppressive responses, and little change in its population response
115 pattern during repeated odorant sampling. In contrast, MCs showed diverse changes in excitation
116 and suppression with repeated odorant sampling, such that the MC population response pattern
117 reformatted substantially from the beginning to the end of the odorant presentation, and did so in
118 a frequency-dependent manner. These effects point to an important role for inhalation
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119 frequency-dependence in odor perception and differential contributions by MC and sTC
120 populations in encoding odor information over repeated samples.
121 Materials and Methods
122 Animals. Adult transgenic mice (ages 6-16 weeks) of both sexes (n = 12 males and 13 females)
123 were used in all experiments. Imaging in mice was carried out in Cck-IRES-cre (Jackson
124 Laboratory (Jax) stock #012706) (Taniguchi et al., 2011) mice for imaging in sTCs or in either
125 Pcdh21-cre (Mutant Mouse Resource and Research Center stock #030952-UCD) (Gong et al.,
126 2003) mice or Tbet-cre (Jax stock #024507) (Haddad et al., 2013) mice for imaging in MCs.
127 Mice were either crossed with Ai95(RCL-GCaMP6f)-D (Jax stock #024105) (Madisen et al.,
128 2015) reporter mice or injected with adeno-associated viral vectors (AAV) to drive expression
129 (see below). All procedures were carried out according to NIH guidelines and were approved by
130 the Institutional Animal Care and Use Committee of the University of Utah.
131 Viral Vector Expression. GCaMP6f/s expression was achieved using recombinant viral vectors,
132 AAV1, AAV5, or AAV9 serotypes of hSyn.Flex.GCaMP6f.WPRE.SV40 or
133 hSyn.Flex.GCaMP6s.WPRE.SV40 (UPenn Vector Core). Virus titers were as follows: 1.7 x 1012
134 – 1.4 x 1013 (GCaMP6f) or 7.0 x 1012 –7.3 x 1013 (GCaMP6s). Virus was injected using pulled
135 glass pipettes into the anterior piriform cortex (aPC) at the following coordinates (relative to
136 Bregma): 2.4 mm anterior, 1.6 mm lateral, and 3.5 mm ventral. Injections were performed as
137 described previously (Rothermel et al., 2013; Wachowiak et al., 2013), achieving an infection
138 rate of ~80% as employed by our lab (Rothermel et al., 2013). Animals were injected with
139 carprofen (5 mg/kg; analgesic) and enrofloxacin (10 mg/kg; antibiotic) immediately prior to
140 surgery as well as the following day. After surgery, animals were singly-housed and were
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141 allowed to recover on a heating pad prior to transfer back to the animal colony. Imaging
142 experiments occurred 14-45 days after injection.
143 Olfactometry. Odorants were delivered via an air-dilution olfactometer, in which the odorants
144 were first diluted in mineral oil, followed by an air-phase dilution, for a final estimated
145 concentration presented to the animal of ~10-20 ppm (Wachowiak et al., 2013; Economo et al.,
146 2016). Odorants of different chemical groups (esters, aldehydes, ketones, organic acids) were
147 presented in random order with respect to inhalation frequency, and repeated for 8 trials (6 trials
148 in two sTC glomerular experiments), with a minimum 36 second inter-trial interval (ITI; Fig. 1).
149 Inhalation (1, 3, and 5 Hz) was controlled using an artificial inhalation paradigm (Wachowiak
150 and Cohen, 2001; Díaz-Quesada et al., 2018; Eiting and Wachowiak, 2018). Stimuli and artificial
151 inhalation were controlled with Labview software (National Instruments).
152 In vivo two photon imaging. Animals were initially anesthetized with pentobarbital (50 mg/kg);
153 and long-term anesthesia was maintained with isoflurane (0.5%-1.0% in oxygen) for the duration
154 of the experiment. Body temperature was maintained at 37°C. Following a craniotomy (~1.5 x 1
155 mm) over one olfactory bulb, we imaged glomeruli or cell bodies at appropriate depth: 20-30 m
156 below olfactory nerve layer (ONL) for glomeruli, ~120-150 m below the ONL for sTCs and
157 ~240-270 m below ONL for MCs. Calcium signals (GCaMP6f/6s) were collected using a 2-
158 photon laser and microscope system (Neurolabware), running a Ti-Sapphire laser (Coherent,
159 Chameleon Ultra-II) operating at 920-940 nm. Imaging was performed through a 16x, 0.8 NA
160 objective (Olympus), and emitted light was collected through a GaAsP photomultiplier tube
161 (Hamamatsu, H10770B-40). Frame rate was 15.5 Hz.
162 Data Analysis. Image processing and analysis of optical signals followed procedures similar to
163 those described previously (Wachowiak et al., 2013; Economo et al., 2016). Analyses of calcium
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164 data were performed on fluorescence signals collected at 15.5 Hz. Regions of interest (ROIs)
165 were either glomeruli or cell bodies, selected as contiguous polygons of responsive pixels. ROIs
166 were initially defined based on visually inspecting average odor-evoked response maps and
167 choosing a single polygon above a certain visual threshold of response relative to background. In
168 cases where cell bodies and dendrites appeared to overlap, we selected and analyzed only those
169 portions of the cell body that were non-overlapping. Some ROIs were selected using a manual
170 procedure to select strong responses and when the automated thresholding procedure failed to
171 select single cell bodies or glomeruli. ǻF/F values were calculated as the change in fluorescence
172 during 8 s odorant stimulation compared to the 4 s immediately prior to odorant stimulation,
173 divided by the mean baseline fluorescence value. ROIs were included if the peak value of their
174 odor-evoked ǻF/F signal exceeded 6 standard deviations of the signal during the 4 s immediately
175 prior to the odorant stimulation. If a cell or glomerulus was responsive at one frequency but not
176 another, it was kept and analyzed across all three inhalation conditions. In this way, a non-
177 response can be reasonably interpreted as contributing to the signal. Analyses were carried out
178 only when blank air generated few or no responses (max 5% responding cells/glomeruli), and
179 individual ROIs were removed from analyses if they responded to blank air stimulation.
180 Correlation-to-early (Figs. 3C, D; Fig. 5C, F) calculations were carried out as follows. Data were
181 broken into matrices of ROI-by-time fluorescence values for each odorant-by-frequency (1, 3, or
182 5 Hz) combination. ROI signals were averaged over each 1 s time period (approximately 15 time
183 bins of data), for the full 8 s odorant presentation. The ROI population response at a given 1 s
184 time point was correlated with the response in the 1 s immediately prior, with the correlation at
185 the starting time bin set to “1.” These correlations were then grouped together either by
186 experiment or by cell type, as indicated in the Results.
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187 The analysis in which we broke the MC cell body dataset into groups of cells with
188 different response strengths (cf. Fig. 4C) was done as follows for each inhalation frequency and
189 odor combination. First, for each odorant response, the MC population was split into 3 groups as
190 follows: strongly excitatory (the top 50% of all excitatory responses), weakly excitatory (the
191 bottom 50% of all excitatory responses), and suppressed cell groups. This resulted in groups of
192 4-22 cells in each odor-by-frequency case for a given FOV (avg 7-11 cells across all FOVs),
193 save for two experiments, in which 5 Hz suppressive responses were not observed. Finally, the
194 cells that made up each group were subtracted from the overall populations, and correlations-
195 over-time were recalculated as above.
196 Principal components analysis (PCA) was carried out for experiments in which three or
197 more odorants generated consistent responses, resulting in 5 MC-cell body (n = 13-58 ROIs)
198 experiments and 3 sTC-cell body (n = 18-23 ROIs) experiments (Fig. 6). For each experiment,
199 PCA was carried out as follows. First, responses to any given odor-by-inhalation frequency
200 condition were averaged across the eight repeated presentations of that stimulus, and binned per
201 frame (i.e. ~15.5 Hz; each bin ~65 ms). Data were then concatenated for all odors into one
202 dataset for each inhalation-frequency condition. PCA was carried out on each of these three
203 datasets (1, 3, and 5 Hz), computed on ROI-by-time (2-photon sampling rate) matrices, similar to
204 what has been done in previous studies (e.g., Bathellier et al., 2008). The PCAs were primarily
205 utilized for visualization.
206 Finally, Euclidean distances (calculated as the square root of the sum of squared
207 distances) were calculated across cell responses between each successive time bin, and these
208 were summed across all odors for each inhalation condition. Euclidean distances were
209 standardized by number of odorants within a given experiment, because this measure provided
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210 an unbiased method to compare the spread of points in visualization (PC) space across
211 experiments or conditions. These values were used as a way to examine how the temporal
212 evolution of MC and sTC odorant responses were represented in the cell body populations.
213 Experimental Design and Statistical Analyses. Unless otherwise noted, analyses were done using
214 mean responses within a given experimental preparation as our unit of replication. Statistical
215 tests were carried out using custom scripts written in Matlab 2019b (Mathworks) or R v.3.3.2 (R
216 Foundation for Statistical Computing). Details of each analysis are presented in the relevant
217 section of the results. Raw data and analysis code are available upon request.
218 Results
219 Our major goals were to understand how inhalation frequency affects activity patterns of mitral
220 and tufted cell populations, and to explore differences in their responses in the context of
221 inhalation frequency. To achieve these aims we collected fluorescent calcium signals from mitral
222 (MC) and superficial tufted (sTC) cells under 2-photon microscopy using an artificial-inhalation
223 paradigm to control inhalation frequency in isoflurane-anesthetized mice (Fig. 1A, B)(Díaz-
224 Quesada et al., 2018; Eiting and Wachowiak, 2018). To target MCs, protocadherin21-Cre mice
225 were injected with cre-dependent virus into the anterior piriform cortex to generate expression
226 predominately in piriform-projecting MCs (Rothermel et al., 2013). Superficial tufted cells
227 (sTCs) were targeted by crossing cholecystokinin (CCK)-IRES-Cre mice with Rosa-GCaMP6f
228 mice (line Ai95D), as previously reported (Economo et al., 2016; Short and Wachowiak, 2019).
229 For each cell type, we lowered the imaging plane to the appropriate depth. We gathered MC and
230 sTC responses from populations of cells imaged while presenting clean air and then odorant at
231 different inhalation frequencies (see Methods). We presented eight successive odorant
232 presentations of 8 s duration (interspersed with a 36 s inter-trial interval) at each inhalation
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233 frequency. Example resting fluorescence, activity map, and traces from a MC-cell body imaging
234 experiment show examples of average traces produced from individual trials (Fig. 1C-E). In
235 general, variability from trial to trial was small and, as is apparent in Fig. 1E, tended to be
236 correlated across cells, suggesting a difference in stimulation effectiveness or other global
237 change in excitability rather than variations in cell-specific responses.
238 We first compared responses of MCs and sTCs to repeated sampling of odorant at 1, 3,
239 and 5 Hz. Examples of imaging experiments targeted to each cell type are shown in Figs. 2A and
240 B, illustrating qualitative differences in how MCs and sTCs respond to repeated sampling, and
241 how these responses change as a function of frequency. MCs showed more diverse temporal
242 responses over time that included slower increases in activity peaking over the course of odorant
243 presentation, while sTC responses tended to be simpler, generally following the onset and offset
244 of odorant presentation (Fig. 2A, B). sTCs also more commonly followed individual inhalations
245 at 1 Hz than did MCs. These trends were evident across the entire population of imaged MCs and
246 sTCs, compiled from seven and five mice, respectively (Fig. 2C, D). Finally, suppressive
247 responses were common in MCs but were rarely observed in sTCs. MC responses included a
248 substantial percentage of suppressive cells: 207/655 (32%) cell-odor pairs at 1 Hz, 163/655
249 (25%) cell-odor pairs at 3 Hz, and 168/655 (26%) cell-odor pairs at 5 Hz were suppressive. By
250 contrast there were very few suppressive sTC responses: 23/445 (5%) cell-odor pairs at 1 Hz,
251 31/445 (7%) cell-odors pairs at 3 Hz, and 24/445 (5%) cell-odor pairs at 5 Hz were suppressive.
252 Signals from MC cell bodies using both GCaMP6f (4 mice) and GCaMP6s (3 mice) showed
253 similar temporal response patterns and prevalence of suppression (not shown), suggesting that
254 the observed differences between MC and sTC populations were likely not due to differences in
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255 the temporal dynamics of the calcium indicator used. Overall, this suite of differences
256 recapitulates those reported earlier at 2 Hz inhalation frequency (Economo et al., 2016).
257 MCs responded heterogeneously to different inhalation frequencies (Fig. 2A). For
258 example, cell 3 in Fig. 2A shows no response at 1 Hz inhalation but strong excitation at 5 Hz,
259 while cell 4 switches response polarity from excitation at 1 and 3 Hz to suppression at 5 Hz.
260 Neighboring cells also show different responses to repeated sampling of the same odorant. For
261 example, cell 3 in Fig. 2A (mentioned above) can be contrasted with its neighbor, cell 5, which
262 responds fairly consistently across all three inhalation frequencies. Across the MC population,
263 cells switched response polarity from suppressed to excited roughly 3-4 times as frequently as
264 excited to suppressed: 49/438 (11%) excited to suppressed from 1 Hz to 3 Hz, 64/438 (15%)
265 excited to suppressed from 1 Hz to 5 Hz; 84/217 (39%) suppressed to excited from 1 Hz to 3 Hz,
266 111/217 (51%) suppressed to excited 1 Hz to 5 Hz (Fig. 2C). MCs also became more excitable
267 with increasing inhalation frequencies: more cells responded to greater numbers of odorants at 3
268 and 5 Hz compared to 1 Hz (Fig. 2D). By contrast, sTCs typically responded similarly to all
269 three inhalation frequencies (Fig. 2B, E), though more sTCs responded to greater numbers of
270 odorants at higher frequencies. In many cells a decrease in excitation suggesting adaptation was
271 apparent with repeated sampling at higher frequencies (e.g., cells 4 and 5 in Fig. 2B). Changes in
272 response polarity in sTCs were much rarer compared to MCs: 22/402 (5%) switched from
273 excited to suppressed responses when comparing 1 Hz to 3 Hz, and 17/402 (4%) switched from
274 excited to suppressed in the 1 Hz to 5 Hz case. Furthermore, while only 5-7% of sTCs showed
275 suppressive responses to 1 Hz inhalation, nearly half of these cells switched polarity from
276 suppression to excitation when inhalation frequency increased to 3 Hz (39%; 9/23 cells) or 5 Hz
277 (61%; 14/23 cells). These differences between MCs and sTCs were likely not due to differences
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278 in frequency-dependent excitability, as sTCs showed a similar pattern to MCs of cells become
279 more excitable with increasing inhalation frequency (Fig. 2F). Overall, these analyses indicate
280 that MCs and sTCs show distinct impacts of inhalation frequency on responses to repeated
281 odorant inhalation, but that across both cell types, as inhalation frequency increased, cells tended
282 to switch from suppression to excitation much more frequently than from excitation to
283 suppression.
284 Heterogeneity in MC (and to a lesser extent sTC) responses implies that neural
285 representations of odor identity, measured in terms of spike rate across each population, will
286 change as a function of repeated odor sampling (Patterson et al., 2013; Díaz-Quesada et al.,
287 2018). Example experimental preparations in Fig. 3A, B show how populations of cells (MCs in
288 Fig. 3A, sTCs in Fig. 3B) change over an 8 s odorant presentation at 1 Hz and 5 Hz inhalation. In
289 the MC example, numerous cell bodies changed their response polarity or their response
290 amplitude across the 8 s odorant period, and this shift occured more often at higher inhalation
291 frequency (Fig. 3A). By contrast, in the sTC example, very few cells switched their response
292 polarity, or even changed their activity level appreciably, regardless of inhalation frequency (Fig
293 3B).
294 To quantify changes among populations of MCs and sTCs, we correlated the population
295 response to an odorant at a given time point to the population response at the first time point
296 (corresponding to the first inhalation at 1 Hz, see Methods for precise times) over the length of
297 odorant presentation. This analysis was performed separately for each ensemble of MCs or sTCs
298 imaged in the same field of view (n = 13-58 MCs and 10-43 sTCs per field of view, 1 field of
299 view per animal). Correlation series for different odorants tested in the same field of view were
300 averaged before compiling across animals, to avoid bias from different numbers of odorants
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301 tested in different animals. These analyses revealed substantial differences in the evolution of
302 odor representations between MCs and sTCs. Among MCs (Fig. 3C), high-frequency inhalation
303 appeared to result in more substantial decorrelation compared to low-frequency inhalation: after
304 8 s, the correlation to the initial response pattern was relatively high at 1 Hz (r = 0.72 ± 0.29,
305 mean ± SD), with lower correlation values at higher inhalation frequencies (3 Hz, r = 0.63 ±
306 0.37; 5 Hz, r = 0.61 ± 0.37). These differences across frequency were not statistically significant,
307 however, (n = 7 mice, Mann-Whitney U test, 1 Hz vs 3 Hz, p = 0.30; 1 Hz vs. 5 Hz, p = 0.71),
308 due to the relative high variance in the degree of decorrelation for different fields of view (see
309 below). Nonetheless this result for MCs contrasts with that for sTCs (Fig. 3D), which maintained
310 highly similar response patterns over the 8 s odor duration, with correlations to the initial
311 response of r = 0.90 ± 0.07 in the 1 Hz case, 0.89 ± 0.02 at 3 Hz, and 0.81 ± 0.12 at 5 Hz (n = 5
312 mice). Regardless of inhalation frequency, MCs decorrelated significantly more over the 8
313 seconds compared to sTCs (correlation coefficients in final time bin for all frequencies, two
314 sample t-test, p = 9.2x10-5). MC cell bodies decorrelated to similar levels when either GCaMP6s
315 or GCaMP6f was used (Fig. 3C), indicating that the differences observed between MC and sTC
316 populations were not a result of different GCaMP reporters; in subsequent analyses we combined
317 data from both variants. Overall, this analysis shows that MC responses show more decorrelation
318 in response patterns with repeated sampling than do sTCs, and suggests that higher inhalation
319 frequencies may drive greater decorrelation in the MC population.
320 Linear decorrelation in population response patterns could arise from systematic changes
321 in MC (or sTC) responsiveness. Such changes could include, for example, increases in excitation
322 that saturate at the high end of a cell's dynamic range or rise above threshold at the low end, or
323 decreases in excitation that have the opposite effects. Alternatively, decorrelation could result
14
324 from distinct effects of repeated sampling in different cells. To distinguish between these
325 possibilities, we measured the change in MC or sTC excitation over the course of the odorant
326 presentation, expressed as the change in ǻF/F from the first to the last second of the presentation
327 (Fig. 4A). There was substantial heterogeneity in the effect of repeated sampling on excitation,
328 reflected as a large variance across cells in the change in ǻF/F (Fig. 4A). Across all cells
329 analyzed and all inhalation frequencies, there was a significant net increase in ǻF/F from the first
330 to the last second, though the magnitude of the difference was small relative to the variance
331 across different cells (Fig. 4A; Wilcoxon sign-ranked test: MC, 1 Hz, mean change in ǻF/F ± SD
332 = 0.075 ± 0.22, p = 1.2x10-11; 3 Hz, 0.13 ± 0.31, p = 1.1x10-15; 5 Hz, 0.12 ± 0.36, p = 3.1x10-10;
333 sTC, 1 Hz, 0.12 ± 0.31, p = 7.5x10-11; 3 Hz, 0.21 ± 0.30, p = 3.5x10-26; 5 Hz, 0.056 ± 0.29, p =
334 3.1x10-2). The magnitude of these differences did not vary significantly across inhalation
2 335 frequencies among MCs, though it did among sTCs (Kruskal-Wallis test: MC, Ȥ = 5.12,1176, p =
2 -11 336 0.08; sTC, Ȥ = 49.82,813, p = 1.5x10 ), with the sTC responses at 3 Hz increasing significantly
337 more than at 1 Hz or 5 Hz inhalation frequencies (bonferroni-adjusted pairwise comparisons, p <
338 0.00001 for both 1 Hz-vs-3 Hz and 3 Hz-vs-5 Hz). These results are consistent with the idea that
339 cells respond to repeated sampling with a net increase in excitability over the duration of the
340 odorant presentation.
341 We next asked whether increasing inhalation frequency systematically impacted MC or
342 sTC excitability within a given cell, either initially (i.e., in the first second) or after prolonged
343 sampling (i.e., after 8 seconds). To test this we compared response magnitude (ǻF/F) for the
344 same cell-odor pairs at 1 Hz inhalation with that at 3 and 5 Hz, for both the initial (i.e., 'early')
345 and 8-second (i.e, 'late') time-points (Fig. 4B). We found that increasing inhalation frequency
346 significantly increased excitation for both early and late time-points in both MCs and sTCs
15
347 (Fig.4B; Wilcoxon sign-ranked test: early MC: 3 Hz, mean change in ǻF/F ± SD: = 0.024 ±
348 0.067, p = 1.2x10-11; 5 Hz = 0.023 ± 0.078, p = 3.0x10-8; late MC: 3 Hz, 0.081 ± 0.31, p =
349 1.1x10-9; 5 Hz = 0.072 ± 0.4103, p = 7.9x10-3; early sTC: 3 Hz = 0.17 ± 0.15, p = 2. 6x10-40; 5
350 Hz = 0.19 ± 0.25, p = 2.6x10-27; late sTC: 3 Hz = 0.26 ± 0.32, p = 3.4x10-27; 5 Hz = 0.13 ± 0.43,
351 p = 5.6x10-9). The net increase in excitation in both the initial and late time bins was smaller in
352 MCs than in sTCs (two-sample t-tests, early 3 Hz MCs vs early 3 Hz sTCs, late 3 Hz MCs vs late
353 3 Hz sTCs, and so on; p < 0.05 in all cases). Together these results indicate that, while increasing
354 inhalation frequency modestly enhances net excitation, repeated odorant sampling reorganizes
355 MC and sTC responses differently. In particular, sTCs show an increase in excitation that affects
356 all sTCs similarly, whereas MCs respond to increasing inhalation frequencies with a more
357 modest increase in excitability, but more pronounced differentiation among individual cells.
358 Reformatting of the population responses among MCs could be a result of changes across
359 all cells, or it could occur across only a subset of cells depending on their initial response to the
360 odorant. To differentiate between these possibilities we broke the datasets into groups of strongly
361 responding, weakly responding, and suppressive cells based on their response within the first
362 second of odor presentation (see Methods); each group had roughly equivalent numbers of cells
363 overall (average strongly-excited cells: 10 (1 Hz), 10 (3 Hz), 11 (5 Hz); weakly excited cells: 9
364 (1 Hz), 10 (3 Hz), 10 (5 Hz); suppressive cells: 9 (1 Hz), 8 (3 Hz), 7 (5 Hz); 20 odor-by-
365 frequency presentations in seven mice). To test whether any of these subpopulations
366 preferentially drive reformatting, we removed each subset of cells and recalculated the
367 correlation-to-early plots as done previously (cf. Fig. 3C). Removing strongly excited MCs from
368 the population appeared to eliminate frequency-dependent differences in the degree of
369 decorrelation (Fig. 4C, compare to Fig. 3C). However, sampling-dependent decorrelation
16
370 persisted after removal of each MC subgroup (strongly-excited, weakly-excited and suppressed
371 MCs) (Figs. 4C, D), with no significant differences in the degree of decorrelation relative to each
2 372 other or relative to the full population, at any frequency (Kruskal-Wallis test: 1 Hz, Ȥ = 0.723,24,
2 2 373 p = 0.87; 3 Hz, Ȥ = 0.183,24, p = 0.98; 3 Hz, Ȥ = 0.983,24, p = 0.81). Overall these analyses show
374 that decorrelation is not driven by changes in the responsiveness of particular subsets of MCs
375 defined by their initial response; instead, all cells contribute to the population reformatting
376 observed in our datasets.
377 Glomeruli are the functional unit of odor representations at the level of OB inputs, and
378 each MC or TC has a single apical dendrite that branches heavily in one glomerulus and is the
379 sole source of excitatory synaptic input for that cell (Mombaerts et al., 1996; Schoppa and
380 Westbrook, 2001; Wachowiak et al., 2004; Wachowiak and Shipley, 2006; Economo et al.,
381 2016). We have shown previously that temporally diverse response patterns, including
382 suppressive and excitatory responses, are prevalent in glomerular MC signals (Economo et al.,
383 2016). However, it is possible that different MCs arising from the same glomerulus (i.e., 'sister'
384 MCs; (Dhawale et al., 2010) may show distinct effects of repeated sampling or inhalation
385 frequency, which could ultimately obscure the decorrelation among sister cells. Thus, to further
386 investigate how inhalation frequency impacts odor representations, we imaged MC calcium
387 signals from glomeruli of the dorsal OB.
388 We found that, as with cell body imaging, glomerular MC responses (n = 11 mice, 15-41
389 glomeruli per field of view) were more diverse at higher inhalation frequencies compared to low
390 (Fig. 5A, B). Suppressive responses were prevalent, occurring in 472/1164 (40.5%) of all
391 glomerulus-odorant pairs at 1 Hz inhalation, with slightly lower percentages at high inhalation
392 frequencies: 451/1164 (38.7%) at 3 Hz, and 391/1164 (33.6%) at 5 Hz. These percentages are
17
393 similar to our MC cell body data presented above, as well as to those reported earlier using a 2
394 Hz inhalation frequency (Economo et al., 2016). We also observed frequency-dependent changes
395 in responsiveness as well as response polarity: from 1 to 3 Hz, 109/692 (15.7%) glomerulus-odor
396 pairs switched from excited to suppressed, and from 1 to 5 Hz, 111/692 (16.0%) switched from
397 excited to suppressed. Responses that switched from suppressed to excited were more common
398 by a factor of ~2: from 1 to 3 Hz, 114/472 (24.2%) switched from suppressed to excited, and
399 from 1 to 5 Hz, 176/472 (37.3%) switched from suppressed to excited. These percentages are
400 roughly similar to the percentages of MC cell bodies that switched polarity with increasing
401 inhalation frequency.
402 Other aspects of the MC glomerular signals differed notably from the MC cell body
403 signals. For example, glomerular signals showed less decorrelation at the end of the 8 s odorant
404 presentation compared to cell bodies (Fig 5C; t-test, p = 0.0037), and they also showed a
405 statistically significant effect of inhalation frequency on the amount of decorrelation, with
406 responses at 1 Hz (r = 0.90) greater than those at 3 Hz (r = 0.75, Mann-Whitney U-test: p =
407 0.022, n = 11 mice) and 5 Hz (r = 0.78; Mann-Whitney U-test: p = 0.036, n = 11 mice). Also,
408 glomerular signals imaged with GCaMP6s appeared to show a greater difference in decorrelation
409 between low and high inhalation frequencies compared to the GCaMP6f data (Fig. 5C). With
410 both reporters, higher inhalation frequencies resulted in greater decorrelation, though only the
2 2 411 result for GCaMP6s was significant (Kruskal-Wallis test: 6s, Ȥ = 6.862,12, p = 0.032; 6f, Ȥ =
412 2.682,15, p = 0.26). Overall, these data point to a similar amount of decorrelation in MC dendrites
413 as in their cell bodies.
414 We also analyzed glomerular signals among CCK+ TCs, to compare with response
415 patterns recorded from sTC cell bodies. A caveat to this comparison is that the CCK+ TC
18
416 population also includes middle and deep TCs and, potentially, external tufted cells (Seroogy et
417 al., 1985; Baltanás et al., 2011; Economo et al., 2016); thus glomerular CCK+ GCaMP6f signals
418 cells may reflect summed responses across a more functionally diverse population than the sTC
419 subtype. Glomerular TC responses showed some diversity in responses, but not as much as in
420 MCs, as example traces show (Fig. 5D). Across the entire population of glomerulus-odor pairs (n
421 = 15-50 per field of view, compiled from 3 mice), inhalation-linked activity was seen in 1 and 3
422 Hz conditions, and most glomeruli showed sustained activity for the duration of the odorant
423 presentation (Fig. 5E). Suppression was rare, occurring in 27/288 (9.4%) of all glomerulus-
424 odorant pairs at 1 Hz inhalation, with slightly greater percentages at high inhalation frequencies:
425 32/288 (11.1%) at 3 Hz, and 37/288 (12.8%) at 5 Hz. As with the sTC cell body imaging, CCK+
426 glomerular signals showed little decorrelation from their initial response patterns with repeated
427 sampling (Fig. 5F), with correlation coefficients after 8 s of odorant sampling of r = 0.92 for 1
428 Hz inhalations, 0.85 at 3 Hz, and 0.78 Hz at 5 Hz (n = 288 cell-odor pairs from 3 mice); these
429 values were not significantly different from those observed among sTC cell bodies (comparing
430 same inhalation frequencies, paired t-test, p > 0.05 in all cases). These results suggest that
431 dendritic signals from TCs behave in a similar fashion to sTC cell bodies.
432 Finally, we examined how the evolution of MC and sTC population responses might
433 contribute to odor identity coding during repeated sampling. First, to better visualize how
434 population responses change with repeated sampling, we performed principal components
435 analysis (PCA) on the cell body population data (see Methods). Across all preparations, between
436 89.1% to 99.7% of the variance in temporal response was captured in the first 3 PCs. The high
437 proportion of variance explained by only the first 3 PCs likely reflects simple but prevalent
438 aspects of the odor-response time courses, such as slow increases in excitation or inhibition.
19
439 Figure 6A demonstrates this effect from an example MC dataset by displaying the change over
440 time of odor responses in principal component space across the three inhalation frequencies.
441 Odor representations grow further apart in the same 8 second block at higher inhalation
442 frequencies compared to low (Fig. 6A). In contrast, the same plot in an example sTC imaging
443 experiment (Fig. 6B) shows a quick evolution of the signal in PC space (top), followed by
444 periodic “swings” in trajectories corresponding to responses to individual inhalations. This result
445 is qualitatively similar to that seen in 'synthetic' populations compiled from multiple MTC
446 recordings (Bathellier et al., 2008).
447 To quantify these effects, we calculated the Euclidean distance between all cell responses
448 in a field of view and averaged these across preparations (see Methods). At 1 Hz inhalation, MC
449 and sTC populations showed parallel trajectories in terms of the dynamics and magnitude of the
450 change in Euclidean distance between different odor representations (Fig. 6C). However, at 3
451 and 5 Hz inhalation, MC populations diverge from sTC populations midway through the 8 s odor
452 presentation, after which the distance between MC odor representations remains high, while that
453 for sTC representations declined somewhat by the end of the 8 s odorant presentation, becoming
454 more similar to the values at the beginning of the odorant presentation (Fig. 6D, E). Final
455 Euclidean distance values between MC and sTC datasets were not statistically different at 1 Hz
456 (MC mean ± SD: 1.61 ± 0.72, sTC: 1.40 ± 1.54, paired t-test, p = 0.80), while the differences at
457 3 and 5 Hz were marginally significant (3 Hz, MC mean ± SD: 2.81 ± 1.05, sTC: 1.41 ± 0.90,
458 paired t-test, p = 0.10; 5 Hz, MC: mean ± SD: 2.55 ± 1.06, sTC: 0.83 ± 0.79, paired t-test, p =
459 0.052), owing to the high variability and relatively low sample sizes (n = 5 MC experiments and
460 3 sTC experiments). These differences in Euclidean distance between MCs and sTCs suggest
461 that while sTC population responses to different odorants initially diverge, they fairly quickly
20
462 plateau and in many cases begin to converge to be more similar within the period of odorant
463 presentation. On the other hand, MC representations continue to diverge over the full 8 sec
464 odorant presentation and appear to diverge to a greater degree at the higher inhalation
465 frequencies (Fig. 6C-E). Altogether, the results from the Euclidean distance analyses support a
466 role for high-frequency inhalation in generating more distinct odor representations over the
467 course of repeated sampling among MCs, with a smaller impact on odor representations among
468 sTCs.
469 Discussion
470 Previous studies have demonstrated that a single inhalation of odorant is sufficient to
471 robustly encode odorant identity, and that rodents can use information sampled in a single sniff
472 to direct odor-guided behaviors (Rinberg et al., 2006; Kepecs et al., 2007; Wesson et al., 2008b;
473 Wesson et al., 2008a). However, animals routinely sample odorants with bouts of high-frequency
474 sniffing that can last multiple seconds (Vanderwolf, 1992; Thesen et al., 1993; Verhagen et al.,
475 2007; Wesson et al., 2008a). Despite its being a fundamental aspect of active odor sampling,
476 little is known about how such repeated sampling facilitates odor-guided behaviors or impacts
477 odor representations. Earlier studies in diverse species have found that odor representations
478 evolve with sustained odorant stimulation over a period of seconds (Friedrich and Laurent, 2001;
479 Verhagen et al., 2007). Here, by imaging from many cells simultaneously and by targeting
480 defined projection neuron subtypes, we have gained new insights into this process in the
481 mammalian olfactory system. We found that repeated odorant sampling impacts odor
482 representations by MCs and CCK+ sTCs differently, with MCs showing a reformatting of the
483 initial odor representation that increased in magnitude with increasing inhalation frequency,
484 while the sTC odor representation remained relatively consistent across repeated samples and
21
485 across frequencies. These results further support the idea that MCs and TCs constitute distinct
486 functional pathways for early odor information processing, and suggest that these differences
487 extend to the realm of repeated odorant sampling that is a hallmark of odor investigation in the
488 behaving animal.
489 Imaging from relatively large numbers of cells simultaneously allowed us to gain insights
490 into the nature of the reformatting of the MC population response. We observed that initial
491 response magnitude had little influence in how MCs responded over time (Fig. 4C) - instead, our
492 results suggest that changes in response patterns across all cells contribute to the MC
493 decorrelations. Our results are largely consistent with predictions from a previous study that
494 relied on whole-cell recordings from presumptive MT cells (Díaz-Quesada et al., 2018), which
495 found that individual MT cells showed diverse and frequency-dependent changes in excitation
496 with repeated sampling at 1, 3 and 5 Hz. Likewise, they are consistent with recordings of
497 presumptive MT cells in awake mice, which found substantial changes in MT cell spiking
498 patterns over the first few inhalations of odorant (Carey and Wachowiak, 2011; Patterson et al.,
499 2013; Díaz-Quesada et al., 2018). The fact that we observed cell type-specific and frequency-
500 dependent reformatting of MT cell odor representations that was sustained over a longer time-
501 period of up to 8 seconds in anesthetized mice suggests that the changes seen in awake mice
502 likely result from 'bottom-up' effects related to changes in the dynamics of incoming sensory
503 input, as opposed to modulation by centrifugal inputs related to behavioral state.
504 Our finding that MC responses evolved with repeated sampling over an 8 s odorant
505 presentation substantially more than sTCs supports the idea that these two subpopulations serve
506 distinct roles in odor information coding. In the context of active odor sampling, sTCs may
507 convey a reliable, sniff-by-sniff snapshot of an animal’s odor environment, while MCs may have
22
508 the capacity to encode multiple aspects of odor information and do so flexibly, as a function of
509 the animal's sampling behavior. MC activity patterns may also reflect distinct stimulus features
510 at different times during a sniff bout, similar to what occurs in MCs of the zebrafish OB
511 (Friedrich et al., 2004; Friedrich and Laurent, 2004), and relatedly, as occurs with repeated
512 tastant sampling among neurons of gustatory cortex (Katz et al., 2001).
513 The circuit mechanisms underlying the frequency-dependent reformatting of MC odor
514 representations remain to be determined. Inhibition from granule cells onto MC lateral dendrites
515 has been proposed to decorrelate 'sister' MCs on a faster time-scale (Dhawale et al., 2010), and
516 this process may also work across repeated sampling. However, the fact that we observed
517 similar, albeit somewhat smaller, time- and frequency-dependent changes in patterns of MC
518 activity imaged across OB glomeruli, each of which contains the apical dendrites of multiple
519 'sister' MCs, points to circuit mechanisms in the glomerular layer as playing an important role in
520 this reformatting. One such mechanism may be interglomerular inhibitory circuits that are
521 differentially engaged depending on the overall pattern of glomerular excitation relative to a
522 given MC (Economo et al., 2016; Díaz-Quesada et al., 2018). TCs are thought to be less subject
523 to this inhibition (Christie et al., 2001; Christie and Westbrook, 2006; Fukunaga et al., 2012;
524 Phillips et al., 2012; Jordan et al., 2018b), consistent with our findings that these cells show more
525 uniform responses over time and across inhalation frequency. Signals recorded from TC
526 dendrites in the glomerular neuropil were generally similar to sTC cell body signals in their
527 response patterns, although they showed a slightly greater divergence in decorrelation values
528 across frequencies compared to the sTC cell body dataset. The similarity between these two
529 datasets, despite the fact that sTCs comprise only a fraction of all TCs, is consistent with the idea
23
530 that TCs with cell bodies deeper in the external plexiform layer are also functionally distinct
531 from MCs (Fukunaga et al., 2012; Jordan et al., 2018b).
532 An important distinction in our comparison of sTCs and MCs is that we targeted sTCs
533 defined by their expression of CCK, which constitutes a subset of the entire TC population
534 (Seroogy et al., 1985; Liu and Shipley, 1994; Tobin et al., 2010). We have previously shown that
535 CCK+ sTCs show shorter-latency and simpler excitatory responses to odorants even relative to
536 the larger tufted cell population (Economo et al., 2016; Short and Wachowiak, 2019). This
537 difference may explain why, in our previous study that relied simply on cell body depth to define
538 MT subtype, we did not observe differences in prevalence of suppressive responses or impact of
539 inhalation frequency on excitability of tufted and mitral cells (Díaz-Quesada et al., 2018).
540 However, other studies have observed marked differences in MC and TC response dynamics
541 using cell body depth as an identifying criterion (Fukunaga et al., 2012). Future experiments
542 using additional genetic or anatomical criteria - for example, cortical projection target or
543 expression of other transmitter receptors - will be important in better understanding the nature of
544 diversity in the response properties of OB output neurons.
545 In awake, behaving animals, inhalation frequencies occasionally reach 10 Hz or even
546 higher, which is substantially faster than the highest frequency used here. However, even the 5
547 Hz inhalation frequencies used in this study—which approach technical limits of our artificial
548 inhalation approach—show dramatic impacts on odor representations when contrasted with
549 lower frequencies (Carey and Wachowiak, 2011; Díaz-Quesada et al., 2018). Additionally, while
550 brief bouts of high frequency inhalations may reach 10-12 Hz, sustained bouts (lasting 2 or more
551 seconds) rarely stay so high (Wesson et al., 2008a). At these higher frequencies we might expect
552 even greater decorrelation of initial response patterns, leading to rapid population-level
24
553 reformatting of odorant responses. We also predict that such bouts could lead to higher
554 proportions of suppressive responses in MCs, based on the modest increase in the prevalence of
555 suppression seen when inhalation frequencies increased from 1 to 5 Hz. Such a result could
556 approach levels of suppression seen in awake mice (e.g., 46% in Kollo et al., 2014).
557 The diverse changes in MT cell excitability contrast with those of odorant responses
558 among OSNs, where high-frequency inhalation more uniformly attenuates OSN inputs due to
559 adaptation (Verhagen et al., 2007). How this adaptation leads to a more complex reformatting of
560 MTC response patterns, including both decreases and increases in excitation, is unclear.
561 Recently, by imaging glutamate signals onto MTC dendrites, we observed greater than expected
562 diversity in the dynamics and magnitude of excitatory input onto MTCs during repeated
563 sampling an anesthetized and awake mice (Moran et al., 2019). Thus, patterns of OSN-driven
564 excitation onto MT cells may be more diverse than previously thought. In future experiments it
565 will be important to image simultaneously from OSNs and MTCs to gain further insight into the
566 mechanisms underlying this reorganization of odor representations as a function of sampling
567 behavior.
25
568 Figure legends
569 Figure 1. Imaging mitral and tufted cell population odor responses with artificial inhalation. A,
570 Schematic of experimental paradigm. Odorants are delivered using an artificial inhalation
571 paradigm, with inhalation frequencies of 1, 3, or 5 Hz. A sample inhalation trace (1 Hz) is
572 pictured at the bottom. B, Representative images of resting fluorescence in three types of
573 experiments, showing typical fields of view for sTC cell bodies, MC cell bodies, TC glomeruli,
574 and MC-innervated glomeruli. C, Resting fluorescence image from one field of view, showing
575 over 50 MC cell bodies. D, Odorant-evoked calcium signals, represented as ¨F/F, of the same
576 field of view shown in C. E, Left, Example traces (from ROIs indicated in C and D), showing
577 evoked fluorescence for 8 consecutive trials in which odorant is presented during 5 Hz inhalation
578 for 8 s per trial. Right, average responses of the three ROIs. For most analyses, average
579 responses were used in calculations. All scale bars = 100 m.
580 Figure 2. Odorant-evoked activity varies with inhalation frequency. A, Example trial-averaged
581 responses from five MC cell bodies, showing diverse responses to ethyl butyrate (0.1%) at three
582 different inhalation frequencies. B, Trial-averaged responses from five sTC cell bodies, showing
583 a relative lack of diversity in temporal responses among cells within a given preparation. In all
584 cells, fluorescence signals clearly follow 1 Hz inhalations (top rows for each cell), but this effect
585 disappears at higher frequencies. Scale bars for the maps in A and B = 100 m. C, Time-by-
586 activity plots for all MC cell-odor pairs, rank-ordered by time-to-peak activity at 1 Hz. MC
587 responses are diverse and prolonged, and activity patterns change substantially among cells at
588 higher inhalation frequency. D, Cell-response histograms for 6 MC experiments, showing
589 histograms of how many odorants each cell responded to, across all three inhalation frequencies.
590 For most experiments, more cells responded to higher numbers of odorants at elevated inhalation
26
591 frequencies (3 and 5 Hz). At 1 Hz (black bars), usually many more cells responded to fewer
592 numbers of odorants. E, Time-by-activity plot for sTC cell bodies. Note that, compared to C,
593 peak sTC activity tends to occur earlier than peak MC activity, and sTC responses generally
594 turned off quickly after odor presentation compared to MC responses. In both C and E, odorant
595 offset is at 8 sec. F, Cell-response histograms for 3 sTC experiments, similar to D, again
596 showing that more cells responded to greater number of odorants at higher inhalation
597 frequencies.
598 Figure 3. MC population responses evolve with repeated odorant sampling more than sTC
599 populations. A, Example MC cell body experiment, showing responsive cells during1 Hz and 5
600 Hz inhalation at different time-points. Time progresses horizontally in 2 s increments that
601 represent the response maps during odorant presentation, averaged over 1 s. A number of MC
602 cell bodies change their response strength or response polarity during 5 Hz inhalation, with fewer
603 changing during 1 Hz inhalation. Black arrows highlight cells whose response changes
604 substantially or switches polarity during odor presentation. B, Example sTC cell body
605 experiment, displayed as in A, showing a relative lack of changes in responses among individual
606 cells, regardless of inhalation frequency. C, Average MC population response to an odorant at a
607 given time point correlated to the population response at the first time point over the length of
608 odorant presentation. Correlations decreased faster at higher frequencies, though this difference
609 was not statistically significant. Left, all MC cell body data; middle, data from GCaMP6f
610 experiments; right, data from GCaMP6s experiments. D, Plot of same analysis for sTC
611 responses. Temporal decorrelation does not vary substantially across inhalation frequencies
612 among sTCs. Decorrelation values differed between MCs and sTCs (see text for details). In both
613 C and D, shaded areas represent SEM.
27
614 Figure 4. MC and TC responses show high variance in response to changing inhalation
615 frequency. A, Change in signal amplitudes (ǻF/F) from the last second to the first second for all
616 three inhalation frequencies across both cell types. In both MCs and sTCs, responses late in the
617 odor presentation (final 1 s) are slightly greater than responses early in the odor presentation
618 (first 1 s), but mean changes are small relative to variance across cells. Boxplots represent means
619 and 25%-75% percentiles, and whiskers extend for 3 SDs. Outliers are plotted as individual
620 points outside of the whiskers. B, Change in strength of response magnitudes at 3 Hz and 5 Hz
621 compared to 1 Hz, for both MCs (left) and sTCs (right). For both cell types, the plot on the left
622 reflects change within the first second of odorant presentation, and the plot on the left shows
623 change within the last second of odorant presentation. Points in each plot are relative to
624 maximum value at 1 Hz. For both MCs and sTCs, higher- frequency inhalations lead to increased
625 excitation (means in each plot are greater than zero). For MCs, early amplitudes change less than
626 late amplitudes. The same holds for sTCs, though early amplitude changes are relatively much
627 higher compared to MCs. Activity within the same cells are joined by lines. Beside the
628 individual points, mean ± SEM is plotted for each case. C, Correlation-over-time (c.f. Fig. 3C)
629 for MCs, when a subpopulation of cells (as indicated by the titles of the figure panels) has been
630 removed. Removing any subpopulation of cells still produces a high level of decorrelation,
631 suggesting that no single group of cells dominates that population reformatting. * = p < 0.01 (see
632 text for specific values). D, Correlation-to-early values of the final time bins taken from C,
633 compared across all groups and inhalation-frequency conditions. No significant differences were
634 found within any inhalation frequency.
635 Figure 5. Glomerular signals from apical dendrites of MCs and sTCs show similar diversity in
636 responses and decorrelation patterns compared to MC and sTC cell cell bodies. A, Field of view
28
637 of one experimental preparation, showing how the same set of MC glomeruli respond to three
638 different inhalation frequencies of the same odorant. Right, example trial-averaged responses
639 from five glomeruli. Glomeruli have variable responses at differing inhalation frequencies.
640 Glomerulus 2, for example, shows a quick burst of activity at all three frequencies, but at 3 and 5
641 Hz, this initial burst is followed by a rapid decrease in activity below baseline, which is not seen
642 at 1 Hz. Glomerulus 4 shows slight excitation at 1 Hz, and gradual suppression at 3 and 5 Hz.
643 Scale bars = 100 m. B, Time-by-activity plots for all MC glomeruli, rank-ordered by time-to-
644 peak activity at 1 Hz. Similar to MC cell bodies, glomerular responses are diverse and prolonged.
645 MC glomeruli include a high proportion of suppressive responses. C, Correlation of the average
646 MC glomerular population response to an odorant at a given time point to the population
647 response at the first time point, over the length of odorant presentation. Top, all MC glomerular
648 data. Bottom left, data from GCaMP6f experiments; bottom right, data from GCaMP6s
649 experiments. MC glomerular responses decorrelate more strongly at 3 and 5 Hz compared to 1
650 Hz. The magnitude of decorrelation is lower than in MC cell body data (compare to Fig. 3A). D,
651 Field of view of one TC experimental preparation, showing the same set of glomeruli responding
652 to three different inhalation frequencies of the same odorant. Right, example trial-averaged
653 responses from five glomeruli. At low frequencies, fluorescence signals often follow inhalations,
654 which is not seen at 5 Hz. Glomeruli also show variable responses at differing inhalation
655 frequencies. Glomerulus 1, for example, shows inhalation-locked activity throughout 8 s odorant
656 presentation, but 3 and 5 Hz it instead shows a relatively quick burst of activity followed by slow
657 adaptation throughout the remaining 8 s, with a rapid drop-off when the odorant shuts off.
658 Glomerulus 2 shows similar behavior to glomerulus 1 at 1 Hz, but its response to 3 and 5 Hz
659 differs. At 3 Hz it responds with high amplitude throughout the full 8 s presentation, but its
29
660 response at 5 Hz instead shows a gradual adaptation. Scale bars = 100 m. E, Time-by-activity
661 plots for all TC glomeruli, rank-ordered by time-to-peak activity at 1 Hz. Signal follow
662 individual inhalations at 1 and 3 Hz. In general, responses last for the duration of odorant
663 presentation, though especially at 5 Hz some cells can be seen to excite rapidly and adapt within
664 the first 500 ms of odorant presentation. F, Correlation of the average TC glomerular population
665 response to an odorant at a given time point to the population response at the first time point,
666 over the length of odorant presentation. The pattern and strength of decorrelation is very similar
667 to that for sTC cell bodies (Fig. 3D).
668 Figure 6. Odor representations become more distinct over time at high inhalation frequencies in
669 MCs but not in sTCs. A, Example MC experiment, showing a rapid increase in distances at the
670 beginning of odorant presentation (especially at 3 and 5 Hz), followed by a slow rise/plateauing
671 of Euclidean distance for the bulk of the odorant presentation. B, Example sTC experiment,
672 showing that one of the dominant longer-term signals is that sTC responses closely follow
673 inhalation, at least at low frequencies. Odorant trajectories do not spread out as much at high
674 frequencies as compared to the MC case, and a major feature is the oscillatory nature of the
675 PCA, reflecting the inhalation-linked responses of sTCs. C, Summed Euclidean distances across
676 MC and sTC preparations at 1 Hz inhalation frequency, showing that the distances parallel each
677 other in both cell types. D, Euclidean distance at 3 Hz exhibit different trends between MCs and
678 TCs, diverging midway through the 8 s odor presentation. E, At 5 Hz inhalation, distances
679 diverge between MCs and sTCs after roughly 3 seconds of odorant presentation. In C-E, shaded
680 areas represent SEM. A gray dashed line has been added in each plot that corresponds to the time
681 point at which decorrelation analyses in previous figures/text results begins.
30
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809
36 A 16x
OB
Inhalation
1 Hz Inhalation { 3 Hz (vacuum) 5 Hz Time 1 s 1 s B sTC somas MC somasTC glomeruli MC glomeruli
Resting Fluorescence ΔF/F Activity Map C D 100%
1 2 1 2
3 3
-20%
Eodor odor 1
2
3 100 % 100 % 20 s 5 s CD
Cell-odor pair Cell-odor pair Cell-odor pair A 600 500 400 300 200 100 600 500 400 300 200 100 600 500 400 300 200 100 015 10 5 0 15 10 5 0 15 10 5 0 5 3 1
H H H Time relativetostartofodor(s) Time relative tostartofodor(s) Time relativetostartofodor(s) 5 Hz 1Hz 3 Hz 1 Hz z z z MCs 4 4 4 C sTCs MCs 3 3 3 5 5 5 2 2 2 1 1 1 1 -15% 70% 5 Hz 3 Hz 1 Hz -max max -max max -max max 100% Normalized dF/F Normalized dF/F Normalized dF/F Cell 5 Cell 4 Cell 3 Cell 2 Cell 1 5 s
Count Count 20 Count Count 10 10 20 10 20 30 40 Count10 15 20 40 60 Count 0 3 6 9 0 0 0 5 0 0 Number ofodorants Number ofodorants Number ofodorants Number ofodorants Number ofodorants Number ofodorants odor 012345 0123 0123 0123 0123 012 MCs 5 Hz 3 Hz 1 Hz B 1 1 1 5 3 1 EF
Cell-odor pair Cell-odor pair Cell-odor pair H H H 400 300 200 100 400 300 200 100 400 300 200 100 z z z 5 Hz 3 Hz 015 10 5 0 15 10 5 0 15 10 5 0 5 5 5 sTCs Time relative tostartofodor(s) Time relativetostartofodor(s) Time relativetostartofodor(s) 2 2 2 3 3 3 4 4 4 -50% 200%
100% 5 Hz 3 Hz 1 Hz Cell 5 Cell 4 Cell 3 Cell 2 Cell 1 5 s -max max -max max -max max
Normalized dF/F Normalized dF/F Normalized dF/F Count odor Count Count 14 18 0 2 4 6 8 0 7 0 9 Number ofodorants Number ofodorants Number ofodorants 01234 0123 0123 sTCs 5 Hz 3 Hz 1 Hz A MC Cell Bodies 2 s 4 s 6 s 8 s 5%
1 Hz
-5% 10%
5 Hz
-10% B sTC Cell Bodies 2 s 4 s 6 s 8 s 5%
1 Hz
-5% 10%
5 Hz
-10% C MC Cell Bodies D sTC Cell Bodies All MCs GCaMP6f 1 GCaMP6s All sTCs 1 1 1 0.8 0.8 0.8 0.8 0.6 0.6 0.6 0.6 0.4 0.4 0.4 0.4 1 Hz 1 Hz 1 Hz 1 Hz 0.2 3 Hz 0.2 3 Hz 0.2 3 Hz
0.2 3 Hz (r) coeff. Corr. Corr. coeff. (r) coeff. Corr. Corr. coeff. (r) coeff. Corr. Corr. coeff. (r) coeff. Corr. 5 Hz 5 Hz 5 Hz 5 Hz 0 0 0 0 12345678 12345678 12345678 12345678 TIme relative to start TIme relative to start TIme relative to start TIme relative to start of odor (s) of odor (s) of odor (s) of odor (s) A MCs sTCs B MCs sTCs ns Change in MC Amplitude Change in MC Amplitude Change in sTC Amplitude Change in sTC Amplitude 250 * 250 Relative to 1 Hz, Early Relative to 1 Hz, Late Relative to 1 Hz, Early Relative to 1 Hz, Late
150 150 * 150 * 150 * 200 * 200 * * * * * 100 * * * 100 * 100 100 * 150 150
* 50 50 50 50 100 100
0 0 0 0 50 50
-50 -50 -50 -50 0 0
-100 -100 -100 -100 % Change in ΔF/F (relative to max at 1 Hz) % Change in % Change in ΔF/F (relative to max at 1 Hz) % Change in % Change in ΔF/F (relative to max at 1 Hz) % Change in -50 -50 ΔF/F (relative to max at 1 Hz) % Change in % Change in ΔF/F (last second relative to first second) % Change in ΔF/F (last second relative to first second) % Change in -150 -150 -150 -150 -100 -100 1 Hz 3 Hz 5 Hz 1 Hz 3 Hz 5 Hz 3 Hz 5 Hz 3 Hz 5 Hz 3 Hz 5 Hz 3 Hz 5 Hz Inhalation frequency Inhalation frequency Inhalation frequency Inhalation frequency Inhalation frequency Inhalation frequency C Minus Strongly- Minus Weakly- Minus All D Correlations in Final Correlations in Final Correlations in Final Excitatory Cells Excitatory Cells Suppressive Cells 1 Time Bin, 1 Hz 1 Time Bin, 3 Hz 1 Time Bin, 5 Hz 1 1 1 0.8 0.8 0.8 ) ) ) ) ) ) r r r r 0.8 r 0.8 0.8 r 0.6 0.6 0.6 0.6 0.6 0.6 0.4 0.4 0.4 0.4 0.4 0.4 0.2 0.2 0.2 1 Hz 1 Hz 1 Hz 0 0 0 0.2 3 Hz 0.2 3 Hz 0.2 3 Hz Corr. Coef. ( Corr. 5 Hz Coef. ( Corr. 5 Hz Coef. ( Corr. 5 Hz Coef. ( -0.2Corr. -0.2 Coef. ( Corr. Coef. ( -0.2Corr. 0 0 0 12345678 12345678 12345678 TIme relative to start TIme relative to start TIme relative to start Full No No Full No No Full No No Strong WeakNo Sup- Strong WeakNo Sup- Strong WeakNo Sup- of odor (s) of odor (s) of odor (s) pressed pressed pressed Cell population Cell population Cell population A Glomeruli (MCs)B Glomeruli (MCs) C Glomeruli (MCs) glom 1 1 Hz All Glomeruli 1 1 Hz max ) 1 Hz r 4 3 Hz 200 0.8 400 5 Hz 0.6 600 2 0.4 glom 2 800 0.2 1 Hz glom-odor pair 5 1 1000 normalized dF/F 3 Hz 5 Hz 3 0 1200 -max 12345678 0 5 10 15 Time from odor onset (s) Time relative to start of odor (s) 250% 3 Hz GCaMP6f 3 Hz 1 max ) ( Correlation coefficient 4 r 200 0.8 400 2 0.6 glom 3 600 0.4 800
1 glom-odor pair 5 0.2 1 Hz 3 1000 normalized dF/F 3 Hz 5 Hz Correlation coefficient ( Correlation coefficient 1200 0 -max 12345678 glom 4 0 5 10 15 -50% Time relative to start of odor (s) Time from odor onset (s) 5 Hz 5 Hz GCaMP6s 4 max 1 ) 200 r 0.8 400 2 0.6 glom 5 600 0.4 5 1 800 glom-odor pair 3 normalized dF/F 0.2 1 Hz 1000 3 Hz 5 Hz 1200 ( Correlation coefficient 0 50% -max 0 5 10 15 12345678 5 s Time relative to start of odor (s) Time from odor onset (s) E F D Glomeruli (TCs) Glomeruli (TCs) Glomeruli (TCs) odor 1 Hz 1
glom 1 ) 4 5 max r 1 Hz 50 0.8 100 0.6 3 3 Hz 150 0.4 2 1 Hz 200 0.2 3 Hz glom-odor pair normalized dF/F 5 Hz
250 ( Correlation coefficient 0 1 12345678 5 Hz -max 0 5 10 15 Time from odor onset (s) Time relative to start of odor (s) 350% glom 2 3 Hz 4 5 max 50
100 3 2 150
glom-odor pair 200 normalized dF/F 1 250 -max glom 3 0 5 10 15 -50% Time relative to start of odor (s) 5 Hz 4 5 max 50 glom 4 3 100 2 150 200 glom-odor pair glom 5 normalized dF/F 1 250 -max 0 5 10 15 200% 5 s Time relative to start of odor (s) A MC ExampleB sTC Example 1 Hz 1 Hz Hexanoic Acid 1 2-Hexanone Ethyl Butyrate 0
1 Benzaldehyde PC 3 Butyl Acetate -1 Methyl Valerate 0 2 -1 PC 3 Acetophenone -1 0 Ethyl Butyrate 0 PC 1 1 -2 2 -2 -2 PC 2 3 0.4 0.6 -1 0 1 2 3 -0.6 -0.4 -0.2 0 0.2 PC 1 PC 2 3 Hz 1 3 Hz Hexanoic Acid Ethyl Butyrate 0 2-Hexanone 1 PC 3 Benzaldehyde -1 Methyl Valerate 0 2 Butyl Acetate -1 PC 3 -1 0 0 Acetophenone PC 1 1 Ethyl Butyrate -2 2 -2 -2 PC 2 3 -0.2 0 0.2 0.4 0.6 -1 0 1 2 3 -0.6 -0.4 PC 1 PC 2
5 Hz 1 5 Hz
Hexanoic Acid 0 2-Hexanone 1 Ethyl Butyrate PC 3 -1 2 Benzaldehyde Methyl Valerate 0 -1
PC 3 -1 Butyl Acetate 0 0 PC 1 1 Ethyl Butyrate -2 Acetophenone 2 -2 -2 PC 2 3 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 -1 0 1 2 3 PC 1 PC 2 CDE1 Hz 3 Hz 5 Hz Mean Euclidean Distance vs Time Mean Euclidean Distance vs Time Mean Euclidean Distance vs Time 3.5 3.5 3.5 3 3 MCs 3 MCs 2.5 MCs 2.5 2.5 2 2 2 sTCs 1.5 1.5 1.5 1 1 1 Euclidean distance Euclidean distance Euclidean distance 0.5 0.5 sTCs 0.5 sTCs 0 0 0 12345678 12345678 12345678 Time relative to start of odor (s) Time relative to start of odor (s) Time relative to start of odor (s)