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Stereotyped connectivity and computations in higher-order olfactory neurons

Nature Neuroscience volume 17, pages 280–288 (2014)Cite this article

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Abstract

In the first brain relay of the olfactory system, odors are encoded by combinations of glomeruli, but it is not known how glomerular signals are ultimately integrated. In Drosophila melanogaster, the majority of glomerular projections target the lateral horn. Here we show that lateral horn neurons (LHNs) receive input from sparse and stereotyped combinations of glomeruli that are coactivated by odors, and certain combinations of glomeruli are over-represented. One morphological LHN type is broadly tuned and sums input from multiple glomeruli. These neurons have a broader dynamic range than their individual glomerular inputs do. By contrast, a second morphological type is narrowly tuned and receives prominent odor-selective inhibition through both direct and indirect pathways. We show that this wiring scheme confers increased selectivity. The biased stereotyped connectivity of the lateral horn contrasts with the probabilistic wiring of the mushroom body, reflecting the distinct roles of these regions in innate as compared to learned behaviors.

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Figure 1: Morphological types of lateral horn projection neurons.
Figure 2: Odor selectivity in type I and type II neurons.
Figure 3: Paired recordings identify convergent glomerular inputs.
Figure 4: Summing excitatory input from multiple glomeruli.
Figure 5: LHN odor responses are sensitive to single glomeruli.
Figure 6: Paired recordings identify excitation from one glomerulus.
Figure 7: Odor-selective inhibition gates excitation from glomerulus DP1m.
Figure 8: Circuit origin of inhibition.

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Acknowledgements

We are grateful to G. Technau (Johannes Gutenberg University Mainz) for the gift of Mz671-Gal4, J. Simpson (Janelia Farm Research Campus) for c315a-Gal4, G. Rubin and B. Pfeiffer (Janelia Farm Research Campus) for pJFRC7-20XUAS-IVS-mCD8∷GFP(attp40) and S.R. Datta (Harvard Medical School) for UAS-C3PA-GFP and UAS-SPA-GFP. We thank members of the Wilson laboratory for comments on the manuscript. This work was supported by a research project grant from the US National Institutes of Health (R01DC008174). R.I.W. is a Howard Hughes Medical Institute Investigator. M.F. was supported in part by a Howard Hughes Medical Institute International Student Research Fellowship.

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Authors and Affiliations

  1. Department of Neurobiology, Harvard Medical School, Boston, Massachusetts, USA

    Mehmet Fişek & Rachel I Wilson

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  1. Mehmet Fişek
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  2. Rachel I Wilson
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Contributions

M.F. and R.I.W. designed the experiments. M.F. performed the experiments and analyzed the data. M.F. and R.I.W. wrote the manuscript.

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Correspondence to Rachel I Wilson.

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Integrated supplementary information

Supplementary Figure 1 Spontaneous activity modulates excitability in Mz671 neurons.

The spike counts recorded in Mz671 neurons in triple recording experiments were substantially lower than those obtained in recordings from the same neurons with olfactory stimulation (compare Figs. 4 and 5), even when the PNs were firing at similar rates. This discrepancy may be attributable to several causes. First, glomeruli other than DM4 may be recruited by low concentrations of the odor (methyl acetate), and these glomeruli might be presynaptic to these LHNs. If so, then the LHN would fire at a higher rate than we would expect based on the activity of DM4 alone. There is evidence that methyl acetate is specific for DM4 at these concentrations (ref. 43), but this idea is still difficult to completely exclude. Second, there could be more than one DM4 PN. If so, we would be stimulating more PNs with odor versus with current injection. This is unlikely, because when we expressed PAGFP pan-neuronally and photoactivated the DM4 glomerulus, we found only one DM4 PN (data not shown). Third, LHNs may exhibit different excitability in the two types of experiments. In support of this idea, there was a systematic difference in the stimulus-evoked change in LHN spike rate for a given change in LHN membrane potential (panel a). Moreover, both spontaneous EPSPs and spikes were systematically reduced in the triple recordings versus (panels b and c; each point in panel b is a different experiment). In the triple recordings, we hyperpolarized the two PNs below their normal resting potential, thereby preventing them from spiking outside the stimulation window. In any given triple recording, we are thereby silencing two of the four known PN inputs to the LHN. This likely explains why spontaneous EPSPs are suppressed. In sum, we conclude that the LHN dendrites are likely somewhat hyperpolarized in the triple recordings, due in part to reduced spontaneous PN input, which diminishes the recruitment of voltage-dependent conductances in LHNs, thereby decreasing postsynaptic depolarization in response to PN spikes, and inhibiting postsynaptic spike generation. Methods for analysis in panel a: LHN spikes were detected and then the LHN membrane potential was low-pass filtered to remove spikes. Trials were then sorted according to LHN spike count, binned into groups of 10, and averaged within each bin. Using these trial-averaged traces, we measured the membrane potential over a window of time. For the triple recordings, this was a 400-ms window starting 100 ms after the onset of current injection in the PN. In odor delivery experiments, there is a variable response delay, so we used a variable window. To find this window, we set a threshold (equal to 3 SDs above the baseline) for each trial-averaged trace, and we defined a 500 ms window starting at the first threshold crossing. Each point in panel a plots the average spike count and average membrane potential for a single bin.

Supplementary Figure 2 Inhibition in NP6099 neurons does not depend on total network activity.

a, This panel contains the same data as in Fig. 7a (top, magenta symbols), but with stimuli color-coded. The smooth curve reproduces the fitted line from Fig. 7a (bottom). b, The total amount of olfactory receptor neuron activity for each stimulus, obtained by summing across the firing rates for all receptor types measured by ref. 23. Color codes are the same as in panel a. (For the four numbered stimuli in black from panel a, olfactory receptor neuron data are not available.) Note that the largest relative suppression in the LHN response (relative to the DP1m response) is observed for E2-hexenal (10-2), valeraldehyde (10-2), and 2-butanone (10-2). By comparison, relatively little suppression is observed for 1-penten-3-ol (10-2) and 1-octen-3-ol (10-2), There is no systematic relationship between the amount of suppression and the amount of total activity elicited in ORNs. Thus, the inhibition which suppresses these responses must be selective for the chemical composition of an odor (presumably therefore reflecting input from a small number of glomeruli), and is not simply driven by total network activity.

Supplementary Figure 3 GABAergic local neurons in the lateral horn.

Single confocal sections through the lateral horn of a brain triple immunostained for neuropil (nc82), CD8, and GABA. Dorsal is up, lateral is right. Expression of CD8:GFP is driven by a Gal4 line with a restricted expression pattern (GMR23F06-Gal4). Single-cell dye fills from this Gal4 line demonstrate that these neurons are local to the lateral horn (Figure 8). Their somata lie in a cluster just lateral and slightly ventral to the lateral horn neuropil (arrowhead), and all these somata are GABA-positive, although not all GABA-positive somata in this cluster express CD8:GFP. In the overlay, a magenta circle indicates the approximate boundary of the lateral horn (as in Figures 1 and 8). Similar results were obtained in three brains.

Supplementary Figure 4 Type II LHNs, but not type I LHNs, receive prominent odor-evoked inhibition.

a, Responses of a typical NP6099 neuron to a stimulus that elicits prominent hyperpolarization. In different trials, we manipulated the membrane potential of the LHN by injecting different amounts of current via the patch pipette. Note that odor-evoked hyperpolarization increases at more depolarized holding potentials, indicating that inhibition is at least partly postsynaptic.`b, In a single case, we observed odor-evoked hyperpolarization in a type I LHN. This was noted as part of our general survey of type I LHNs labeled by GMR48F03-Gal4 and GMR73B12-Gal4 (Figs. 1b and 2a). In addition to the core odor set shown in Fig. 2a, we used 26 additional odors in various recordings in the course of this survey, in order to determine if any of them elicited hyperpolarization. We held cells at a depolarized potential during these trials (-40 to -30 mV) to better reveal any inhibition that might be present. Shown here are responses to these 26 odors, only the last of which elicited any hyperpolarization. This example shows that type I cells can receive odor-evoked inhibition, but is still consistent with the conclusion this inhibition is much less prominent than in type II cells. (Odors are : 2,3-butanedione, 2-heptanone, 2-octanone, 3-octanol, α-pinene, benzaldehyde, butyric acid, cis-3-hexen-1-ol, beta-citronellal, cyclohexanone, ethyl butyrate, ethyl caproate, ethyl cinnamate, ethyl lactate, ethyl propionate, fenchone, γ-octalactone, ginger oil, hexyl acetate, linalool, nerol, phenethyl acetate, pyrrolidine, triethylamine, valeraldehyde, isoamylamine; all dilutions are 10-2; horizontal bar in first panel shows 500 ms odor stimulus period.)

Supplementary Figure 5 Spike detection in LHNs.

Action potentials recorded from LHN somata tend to be unusually small. In order to verify that the fastest events we observe in the voltage trace are indeed action potentials, we confirmed that these small rapid events can be elicited with depolarizing current injection, and that they are sensitive to TTX (panel a). We also noted that the rate of these events grows with increasing depolarizing current injection, as expected. In order to detect and count these events, we used a two-threshold algorithm. We identified the events that were both the fastest the rise and the fastest to decay, using an algorithm that thresholded the second and first derivatives of the voltage trace with positive and negative thresholds, respectively (see traces below panels b and c). Thresholds were determined on a cell-by-cell basis. Spikes that were automatically detected are marked with vertical bars. Automated detection was robust at low firing rates (panel b, left). However, at high firing rates, action potential height decreased. Therefore, thresholds were adjusted at high firing rates, and each trace was also individually inspected, and missed spikes were corrected (panel c). Arrows point to missed spikes that were missed by the algorithm and then subsequently corrected. For comparison, arrowheads point to fluctuations in the voltage that were not subsequently marked as spikes. These examples show that there was a clear separation between spikes and non-spikes based on the rates of change in the voltage traces. In order to ensure that the subjectivity of this process does not bias our results in Fig. 5b, we blinded the person performing the analysis to stimulus concentrations.

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Fişek, M., Wilson, R. Stereotyped connectivity and computations in higher-order olfactory neurons. Nat Neurosci 17, 280–288 (2014). https://doi.org/10.1038/nn.3613

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