Baseline spiking in PNs is caused by the tonic spiking of ORNs
Where does spontaneous activity arise? Our recordings from locusts showed that ORNs and PNs spiked tonically even in the absence of odorant delivery, suggesting spontaneous activity arises from early stages of olfactory processing. Unlike the ORNs and PNs, the KCs were nearly silent unless activated by an odor puff (; Laurent and Naraghi, 1994
; Perez-Orive et al. 2004
). We found we could reversibly silence the ORNs by placing the antenna in a stream of chilled air. A thermal barrier, through which we threaded the antenna, prevented chilled air from reaching the animal’s head (). shows an example of a sensilla recording in which baseline and odor-elicited spiking was nearly eliminated by cooling the antenna. Results from several such experiments are summarized in . We used this technique to test the impact of activity in ORNs on the responses of downstream neurons.
Figure 1 Spontaneous and odor-evoked spiking in olfactory neurons are nearly abolished by cooling the antenna. A) Olfactory receptor neurons (ORNs) and projection neurons (PNs) exhibit higher baseline activity than the Kenyon cells (KCs) (~5, ~2.5, and ~0 spikes/s, (more ...)
To test the origins of spontaneous activity we subjected the intact animal’s antenna to a sequence of treatments while making recordings with tetrodes from PNs. These treatments are numbered 1–5 and are keyed to a gray scale in . (1) First, we recorded spontaneous activity in PNs under control conditions; then we reversibly altered activity in the ORNs by (2) cooling and then (3) re-warming the antenna; then (4) we irreversibly isolated the antenna from the environment by covering all exposed sensilla with a viscous barrier (mixture of Vaseline and mineral oil); and finally (5), we removed the antenna by cutting through its base. Throughout these treatments we monitored the spike rates of the PNs, the temperature next to the antenna, and the temperature of the saline bathing the brain.
illustrates the spiking of PNs during the sequence of treatments. At first (1), an example PN () displayed a typical amount of spontaneous spiking (shown as rasters; Mazor and Laurent 2005
) before and after a puff of odor (vertical gray bar at 2–3 s). PNs characteristically respond to odors with sequences of excitation and inhibition (Laurent and Davidowitz, 1994
). Responding to the odor puff, this example PN was first inhibited, then fired a burst of spikes, and then was again briefly inhibited before returning to a background level of spiking. When we gradually cooled the antenna (2), baseline and odor-evoked spiking in the PN nearly ceased. In addition, the temporal structure of the PN’s response to odor (the successive epochs of inhibition, excitation, and inhibition) gradually changed with the temperature of the antenna (). Background and odor-elicited spiking returned to the baseline level as the antenna was warmed back to the control temperature (3). Covering the antenna (4) eliminated the PN’s responses to odorants. However, baseline spiking was barely affected, indicating spontaneous activity in ORNs can arise within the sensilla even when environmental odors were prevented from reaching the antenna. Finally, removing the antenna (5), like cooling the ORNs, completely silenced the PN, suggesting its baseline activity is inherited entirely from the ORNs. summarizes the results of this typical experiment. Results from 6 locusts (21 PNs) are summarized in ; circles and lines indicate results from each animal; gray bars indicate their means. Note in that odor presentations raised the average firing rates of PNs only slightly because odors generally elicit responses containing both excitatory and inhibitory components (see, for example, the PN in ; Laurent and Davidowitz, 1994
; Mazor and Laurent, 2005
). During the cooling phase, the temperature near the antenna decreased to a mean of 8.5°C () yet the temperature inside the head capsule remained nearly constant (21.5°C) throughout these experiments ().
Our model predicts that raising the firing threshold of PNs to the extent that they no longer fire spontaneously would impair signal detection in the KCs
Baseline input from the ORNs tonically depolarizes PNs, LNs, and KCs
What effect does the ongoing barrage of activity in ORNs have upon follower neurons in the AL? To examine subthreshold and spiking responses of follower neurons, we recorded from PNs and LNs in whole-cell current-clamp mode while varying the temperature of the antenna. Cooling the antenna to 6°C had two main, reversible effects on PNs. First, consistent with results from our tetrode recordings (), spontaneous and odor-evoked spiking diminished and in most cases ceased completely (). Second, the resting membrane potential of the PNs decreased by 6.9 +/− 0.6 mV (mean +/− sem, starting from an average of −54.3mV, n = 11). Despite the presence of the thermal barrier, in these experiments cooling the antenna also slightly cooled the saline bathing the brain by <2°C. To determine whether cooling the brain would affect PN properties, we lowered the temperature of the saline bath 2°C by adding drops of chilled saline. Directly cooling the saline bath had no significant effect upon the membrane potential of the PNs (open circles in ). Thus, changes in PN responses were not caused by changes in the temperature of the saline bath.
We also examined LNs, the interneurons within the AL (). While LNs do not exhibit sodium spikes, their responses when the antenna was cooled were otherwise like those of the PNs: odor-evoked responses in LNs were eliminated and, on average, the resting membrane potential decreased by 13.1+/−1.0 mV (starting from an average of −58.3mV, n = 8). As we had observed in PNs, the change in membrane potential was not due to small shifts in the temperature of the saline bath (open circles in ).
Figure 4 Local neurons were tonically depolarized by spontaneous activity in ORNs. Cooling the antenna hyperpolarized the resting membrane potential of LNs recorded under whole-cell current clamp. A–E) Results from an example LN. All conventions are the (more ...)
These results show that the constant barrage of spikes from ORNs caused the PNs and LNs to tonically depolarize even in the absence of deliberate odor stimulation. Despite the significant and tonic depolarization of PNs caused by ORN spikes, PNs did not spike continuously, but rather fired at ~2.5 spikes/sec. The modest firing rate of PNs, given the barrage of input they receive, characterizes the spiking threshold of PNs.
What effect does the ongoing excitatory barrage originating in ORNs have further downstream, upon the KCs? Compared to PNs, KCs are nearly silent when no odor is applied. Our patch recordings revealed that, as we found in PNs and LNs, cooling the antenna reduced subthreshold baseline activity in KCs and eliminated their spiking responses to odor presentations (). Cooling the antenna caused the KCs to hyperpolarize by 7.4 +/− 0.7 mV (starting from an average of −60.7mV, n = 17). Directly cooling the saline bath 2°C actually depolarized the resting membrane potential slightly, by 1.6mV (open circles in ).
Taken together, these results indicate the KCs are tonically depolarized by spikes from PNs which, in turn, are driven by spikes originating in ORNs. Furthermore, variance in the membrane potentials of both PNs and KCs changed in proportion to the changes in resting membrane potential, as would be expected from a reduction in synaptic input as the antenna is cooled (data not shown).
High firing threshold after maximal convergence of information optimizes odor detection
We found that tonic baseline spiking in ORNs propagates to and tonically elevates the membrane potentials and firing rates of LNs and PNs in the AL, and the resulting baseline spiking in PNs tonically elevates the membrane potentials of KCs. Yet, despite this tonic input, KCs rarely spike; for several reasons (Perez-Orive et al 2002
; Demmer and Kloppenburg, 2009
; Papadopoulou et al, 2011
), KCs have firing thresholds higher than the level of input provided by convergent PNs driven by spontaneous activity in ORNs.
Several lines of evidence suggest that the olfactory system benefits from the sparse representation of odorants in KCs (Laurent, 2002
). In principle, a higher response threshold could be set earlier in the olfactory pathway, perhaps in PNs rather than in KCs, leading to greater overall sparseness in the olfactory system. Does the arrangement of different firing thresholds at different stages along the olfactory pathway confer specific advantages for odor encoding? To explore this question we investigated the potential consequences of other possible configurations by simulating the statistics of ORN spiking and its effects upon second and third order neurons in the olfactory pathway (; see Methods). In vivo
, a given KC receives input from more types of receptors than does a given PN, allowing KCs to accurately determine the presence and identity of odors. Reflecting this, our simulation explored parameters including a range of response strength to odors, varying degrees of convergence from ORNs to PNs to KCs, and a range of thresholds for allowing spikes, originating in ORNs, to influence KCs. To determine how combinations of these parameters would affect the abilities of a KC to detect signal amid noise, we simulated trials that included odor-evoked responses (signal) or just spontaneous activity (noise). Then, with a standard receiver operator characteristic (ROC) model we evaluated how well the KC could distinguish between signal and noise trials.
Our analysis included a condition that is challenging for signal detection: when the responses of ORNs to an odor were only slightly different from their spontaneous activity. shows, for each type of neuron in our model, an example of the cumulative probability of firing rates for varying inputs, given different amounts of spontaneous (blue) or odor-evoked (red) firing in the ORNs. The characteristics of the input to PNs, originating from small subsets of the ORNs, are similar to those of the ORNs: both spontaneous and odor-evoked responses largely overlap. But the characteristics of the input to KCs, originating from larger subsets of ORNs by indirect convergence via PNs, are quite different for spontaneous and evoked activity. ROC curves are useful for illustrating signal detection performance under a range of conditions. shows an ROC curve of stimulus detection performance in the KC simulated in panel 6B. Here, the diagonal indicates detection at chance; blue dots indicate detection performance for three levels of input (thresholds a–c in 6B) to this KC. Because odor-evoked and spontaneous inputs were well-separated in this example, the KC’s true positive rate exceeded the false positive rate for all three example thresholds. To quantify detection performance in each such test condition we measured the maximal distance (dashed green line) between a model KC’s ROC curve (blue line) and the diagonal line of chance. We used this value of maximal distance as a measure of optimal detection.
To investigate the relationship between signal detection performance of KCs and firing thresholds in PNs, we analyzed ROC curves obtained under a wide range of threshold levels. shows an example of both optimal detection performance (green) and the corresponding baseline PN firing rate (blue) as a function of varying threshold levels between ORNs and the PN. As the PN’s firing threshold increased, its rate of spontaneous firing decreased. This example shows the KC’s optimal detection performance was high over a broad range of PN thresholds. Notably, though, the KC’s signal detection performance precipitately worsened when the PN’s rate of spontaneous activity approached zero.
As shown in we next used the approach illustrated in to examine signal detection in KCs over a broad range of ORN-PN convergence ratios (rows) and ORN response intensities (columns). Signal detection by the KCs was poor when the ORN response to odors was only a small increment above the spontaneous spiking rate, regardless of the convergence ratio (left column, δ=0.01). Signal detection was best when more ORNs converged upon each PN, and when ORNs responded with more spikes to the odor stimulus (bottom right corner of the matrix). Consistent across all these cases is that KC detection was optimal (tan areas in each plot) when the level of spontaneous activity in PNs exceeded zero; that is, when the firing threshold for PNs was set to be relatively low. These simulations demonstrate the relationship between spike threshold levels in PN and optimal detection performance in KCs: the PN threshold must be low enough that PNs inherit some baseline spiking from ORNs because higher PN thresholds reduce signal along with noise. Thus, given a challenging signal detection task and a background of noisy input, our model suggests that the KCs provide the first location along the olfactory pathway where odor signals can be encoded sparsely, on a near-silent background, without a loss of information.
Our model predicts that raising the firing threshold of PNs to the extent that they no longer fire spontaneously would impair signal detection in the KCs. An observation we subsequently made in vivo is consistent with this prediction. Gradually cooling the antenna hyperpolarizes PNs (), effectively raising the threshold above its rest level. shows that at intermediate temperatures, the spontaneous firing of PNs is silenced while responses to odors persist. With simultaneously recorded pairs of PNs and KCs under these conditions, we found that the odor responses of KCs vanished when the PN threshold was raised. Other factors may also contribute to the elimination of odor-evoked responses in KCs, such as temperature-dependent changes in the temporal patterns of responses evoked by odors in the PNs.