Biophysical mechanisms underlying olfactory receptor neuron dynamics

Abstract

The responses of olfactory receptor neurons (ORNs) to odors have complex dynamics. Using genetics and pharmacology, we found that these dynamics in Drosophila ORNs could be separated into sequential steps, corresponding to transduction and spike generation. Each of these steps contributed distinct dynamics. Transduction dynamics could be largely explained by a simple kinetic model of ligand-receptor interactions, together with an adaptive feedback mechanism that slows transduction onset. Spiking dynamics were well described by a differentiating linear filter that was stereotyped across odors and cells. Genetic knock-down of sodium channels reshaped this filter, implying that it arises from the regulated balance of intrinsic conductances in ORNs. Complex responses can be understood as a consequence of how the stereotyped spike filter interacts with odor- and receptor-specific transduction dynamics. However, in the presence of rapidly fluctuating natural stimuli, spiking simply increases the speed and sensitivity of encoding.

Figure 1. Temporal patterns of ORN spiking are cell- and odor-dependent

Rasters and peristimulus-time histograms (PSTHs, mean ± s.d.) show ORN spiking responses to an odor pulse (1.7 s duration, odors diluted in paraffin oil as labeled). The time course of the odor pulse (top) is not square because it is slightly smoothed by our odor delivery device (see Supplementary Fig. 1). (a) An example of a response with a strong onset transient and offset inhibition. (b) In the same ORN type, a different stimulus drives a similar steady-state firing rate, but the onset transient is weaker and there is no offset inhibition. (c) This same stimulus drives a strong onset transient and offset inhibition in a different ORN type. (d) A more complex response, with an onset transient, then offset inhibition, then more excitation. (e) An example of inhibition followed by excitation. Each trace represents the mean of 5-6 sensillum recordings, each in a different fly.

Figure 2. Field potentials and spikes can be isolated from single ORNs

(a) Three sensillum types in the maxillary palp (de Bruyne et al., 1999; Goldman and Carlson, 2005). (b) A typical extracellular recording from a pb1 sensillum (stimulus is 2-butanone 0.1×). Enlarged segment at the peak of the response shows individual spikes (inset); taking the first derivative (inset lower trace) facilitates spike detection. (c) TTX (50 μM) injected into the palp abolishes spikes, leaving the LFP largely unaffected. We fit exponentials to the rising and falling phases of the LFP, and we also computed the overshoot after odor offset; none of these parameters changed significantly (data not shown). (d) In Or42a^–/– flies, this sensillum type no longer responds to this stimulus, although some spontaneous spikes persist. (e) Mean pb1 LFP responses to selected stimuli are largely unaffected by TTX but are abolished by mutating Or42a. This mutation does not affect responses to these stimuli in a different sensillum type (pb3, Supplementary Fig. 2). (f) In another sensillum type (pb2), responses to fenchone (0.25×) and cyclohexanone (1×) are abolished by ablating the A neuron in a genetic background where B is already ablated. In a background where A is ablated, 1-octen-1-ol (1×) elicits an inhibitory (upward) LFP which is abolished by killing the B neuron. (The small remaining downward response reflects activity in other sensilla.) (g) In pb3 sensilla, LFP responses to isoamyl acetate (1×) are abolished by a mutation in Or85d. Here, the A neuron has been ablated genetically. Data in (e-g) represent mean ± s.d., n = 4-7 recordings each.

Figure 3. Filter models describe transformations between stimulus, LFP, and spikes

(a) Time course of odor stimulus and neural response (pb1, stimulus is 2-butanone 0.01×). Note that spike rate is highest when the LFP is growing but suppressed when the LFP is recovering. (b) Linear filter describing the relationship between the stimulus and the LFP (pb1A, 2-butanone 0.01×, ± s.d.). Arrow indicates single filter lobe. (c) The prediction of the filter (blue) is simply an inverted and slightly smoothed version of the odor time course, as expected for a filter with a single lobe. Comparison to the recorded LFP (black, mean of 5 recordings in 5 flies) shows that the linear model is an adequate coarse description but underestimates onset rate and overestimates offset rate. (d) Actual versus predicted LFP for the stimulus segment shown in (c). Note that the model underestimates responses during onset (open arrow) and overestimates responses during offset (filled arrow). (e) Linear filter describing the relationship between LFP and spike rate. Arrows indicate two filter lobes. The biphasic filter means the spike rate increases when the LFP is growing more negative, and is inhibited when the LFP is recovering. Because the negative lobe is larger than the positive lobe, the spike rate remains elevated above baseline during a maintained negative LFP deflection. (f) The prediction of the filter (magenta) agrees well with the data (black). (g) Actual versus predicted spike rate.

Figure 4. Odor- and cell-dependence of transduction and spiking dynamics

(a) Linear filters describing the relationship between the stimulus and the LFP for five different stimulus/cell combinations. Note that the filter depends on both ligand and receptor. Mean ± s.d. across recordings, n = 5-6 each. Units of y-axes are mV per unit odor. (b) Mean LFP responses for these ligand/receptor combinations (black). Colored lines show the prediction of the linear model, obtained by convolving the corresponding filter in (A) with the stimulus waveform (shown at top). Mean correlation coefficient 0.93 ± 0.04. (c) Linear filters describing the relationship between the LFP and spike rate. Note that these filters have a relatively stereotyped shape, unlike the transduction filters. Units of y-axes are spikes/s per mV. (d) Mean spiking responses (black) in units of spikes/s. Colored lines show the prediction of the linear model, obtained by convolving the corresponding filter in (c) with the recorded LFP. Mean correlation coefficient 0.92 ± 0.06.

Figure 5. Knocking down DmNa_v makes the LFP-to-spiking transformation more differentiating

(a) Firing rates in ORNs with reduced expression of voltage-dependent Na⁺ channels (pb1A, stimulus is 2-butanone 0.1×). Thin lines are trial-averaged responses from different recordings (n = 20-22 sensilla in 10-11 flies of each genotype); thick lines indicate the mean. Mean firing rate during the odor is significantly reduced (p<0.01, t-test). (b) Spontaneous spike rate is also significantly reduced by Na⁺ channel knockdown (p<0.01, t-test). (c) Rate of decay from the peak odor-evoked firing rate was speeded by Na⁺ channel knockdown, measured here by fitting an exponential to the trace from peak to 200 ms after odor offset (p<0.01, t-test). (d) The ratio of peak to steady-state rate firing rate is significantly increased by Na⁺ channel knockdown (p<0.01, t-test). (e) Knockdown has no effect on the time course of the LFP response, although the amplitude is slightly reduced. (f) Filters describing the LFP-to-spiking transformation (mean ± s.d., n = 4). Note that knockdown produces more symmetrical positive and negative lobes, indicating a more differentiating transformation. (g) Filters describing the stimulus-to-LFP transformation were unaffected by Na⁺ channel knockdown, as expected.

Figure 6. Dynamics of transduction and adaptation

(a) LFP recordings from pb1A ORNs illustrate how transduction dynamics depend on odor concentration. Top is 2-butanone (dilutions of 0.1×, 0.02, 0.004, 0.0008, 0.00016, 0.000032). Bottom is isoamyl acetate (1×, 0.2, 0.04, 0.008, 0.0016). Traces are means of 5-6 recordings. Traces at right are normalized to the same maximum negative deflection. Dashed blue line shows one exponential fit to response offset; note that only the initial segment was fit and no attempt was made to fit the overshooting later portion. (b) On- and off-rates as a function of odor concentration, mean ± s.d. across recordings. Rates were calculated by fitting exponential curves to the onset and offset phases of the normalized mean LFP. (c) A typical recording showing that a long adapting pulse of 2-butanone (0.1×) reduced the amplitude and onset slope of the LFP response to a weak test odor pulse (2-butanone 0.004×, green) but not the response to a strong test odor pulse (2-butanone 0.2×, orange). (d) Mean responses to test pulse 1 (solid) and test pulse 2 (dashed) for the two test odors shown in (c), n = 6 recordings. Inset shows the onset phase of these traces normalized to the same amplitude. (e) Mean response amplitude (± s.d.) as a function of concentration for test pulse 1 (filled) and test pulse 2 (open). Arrows indicate the two concentrations shown in (c) and (d). (f) Onset slope as a function of concentration for initial (filled) and adapted (open) responses.

Figure 7. Cross-adaptation between co-expressed odorant receptors

(a) A typical recording showing that a long pulse of 2-butanone (0.1×) acting on OR42a adapts the LFP response to a test pulse of another odor (pentyl acetate, 0.02×) acting on OR47a. Group data (right) shows that both the amplitude and the onset rate of the second test pulse response are significantly reduced compared to the first test pulse response (p<0.01 , n=6 , paired t-test). (b) Same experiment, but in reverse: a long pulse of pentyl acetate (0.02×) adapts the response to a test pulse of 2-butanone (0.004×). The amplitude of the test pulse response is significantly reduced (p<0.01 , n=5, paired t-test). The onset rate is reduced but not significantly (p=0.14, paired t-test). (c) A long pulse of 1-octanol (0.1×) acting on OR47b de-adapts the response to a test pulse of 2-butanone (0.1×) acting on OR42a. Both the amplitude and the onset rate of the test pulse response are significantly increased (p<0.01 , n=9, paired t-test). (d) A long pulse of 2-butanone (0.1×) adapts the response to a test pulse of 1-octanol (0.1×). The amplitude of the test pulse response is significantly reduced (p<0.01 , n=8, paired t-test).

Figure 8. Encoding the dynamics of natural odor plumes

(a) Plume dynamics depend on windspeed and odor location. Cartoon schematizes upwind distance (y) and crosswind distance (x). Traces are LFP recordings from a pb1A ORN responding to 2-butanone (0.1×). (b) Simultaneous recordings from a PID and a pb1A ORN (1.5 mm from the PID). Note spontaneous spikes (arrow); odor-evoked spikes are not visible at this scale. (c) Responses from the same sensillum in the same configuration, now with different odors. (d) Power spectra of simultaneously-measured PID signals (solid lines) and LFP responses (dashed lines). Spectra are normalized to have the same total power. ORN is pb1A, stimuli are color-coded as above (y = 5 cm, x = 0 cm). (e) LFP events sorted and averaged by amplitude (inverted here for display). The range of rise times (time from 10% to 90% of peak) was 28-32 ms. Stimulus is 2-butanone 0.1×. Same configuration as in (b,c). (f) Average spike rates corresponding to the LFP events in (e). Dashed trace represents the largest average LFP response, normalized to the same amplitude as the largest average spike rate. (g) Peak LFP amplitude versus peak spike rate for the data in (e) and (f), ± s.e.m. Open symbol is baseline (defined as the 30 ms starting 100 ms before event onset); dashed line is a linear extrapolation from this to the largest response. (h) Power spectra of LFP (dashed line) and spike rate (dotted line) for responses shown in (c). Stimulus is 2-butanone 0.1×.