Our results demonstrate that the olfactory system of Drosophila
, like those of taxonomically distant locusts and honeybees, as well as many vertebrates, can respond with oscillatory neural synchrony when presented with odorants. The great and growing diversity of species demonstrating odor-elicited oscillations implies this response may be of fundamental significance. Indeed, in honeybees, pharmacologically abolishing oscillations has been shown to impair fine odor discrimination (Stopfer et al., 1997
). Our results show that the mechanisms underlying the oscillations are remarkably similar to those characterized in the locust: antennal afference drives neural circuitry consisting of reciprocally connected excitatory PNs and inhibitory LNs to oscillate, leading to transiently synchronized spiking in PNs that transmit regular, sinusoidal waves of excitation to the MBs. Our use of genetic techniques in Drosophila
allowed us to confirm the importance of inhibition from specific LNs of the AL for generating oscillations, and to characterize this mechanism with unprecedented precision.
During odor presentations, Drosophila
AL neurons fired at reliable phase positions with respect to the LFP oscillations recorded in the MB, as also observed in the locust. However, the spike phase positions in Drosophila
were somewhat different from those characterized in locust, likely because of species-specific differences in neural pathway length and in the firing properties of LNs in the two species. In Drosophila
, where LNs generate fast sodium spikes, PNs led LNs by about 20° each cycle. However, in locusts, where LNs generate slow-to-rise, graded calcium spikelets, PNs led LNs by 180° (MacLeod and Laurent, 1996
). The phase relationships we observed in Drosophila
are similar to those recently noted in odor-elicited oscillations in the moth Manduca sexta
(Ito et al., 2006
), where both LNs and PNs generate fast sodium spikes.
Interestingly, the air speed we found most effective for eliciting robust oscillations (~0.4 m/s) closely matches that at which flying Drosophila
most effectively localize odor sources (Budick and Dickinson, 2006
). In fact, Drosophila
’s ability to orient toward odor sources was compromised when they encountered odors in air moving at other velocities (Budick and Dickinson, 2006
) with a response profile matching our measurements of oscillatory power in the LFP (supplementary Fig. 2
). This match between physiological and behavioral results indicates that the odor-elicited oscillations we observed occurred under conditions in which Drosophila
successfully perform an olfactory task. This encourages us to speculate that mechanisms underlying LFP oscillations and flight chemotaxis may share common features. Other workers presenting brief pulses of odors to Drosophila
in faster-moving air have not observed odor-elicited LFP oscillations (Wilson et al., 2004
; Turner et al., 2008
). Our results suggest that, as in other animals, oscillations elicited by lengthier exposures or stronger concentrations of odors are more easily detected.
We found oscillations could begin at odorant-dependent times relative to the initial deflection in the LFP that indicates the arrival of odorant at the antenna (up to 500 ms delay in the fly, compared to a typical 200 ms delay in locust). In a single fly, for example, oscillations evoked by hexanol were reliably delayed 300 ms longer than those evoked by ethyl acetate (supplementary Fig. 8
). The relatively delayed onset suggests oscillations might not be essential for the earliest stages of odor recognition in Drosophila
. Flies can perform simple odor detection and response behaviors within 300 ms of encountering the odorants (Budick and Dickinson, 2006
), a time generally before we detected the onset of oscillatory activity. It will be interesting to determine whether flies require more time to perform difficult odor discrimination tasks, as has been observed in other species (Rinberg et al., 2006
). If so, information processing tasks facilitated by neural oscillations may contribute to the successful completion of challenging or prolonged olfactory tasks.
In locusts, each PN branches very widely and diffusely throughout the MB calyx, and connectivity between PNs and Kenyon cells (KCs) is extensive (Jortner et al., 2007
). The rhythmic shutter-like inhibition provided by odor-elicited oscillations is thought to contribute significantly in the locust to the sparsening of neural representations of odors in the KCs (Perez-Orive et al., 2002
). In Drosophila
, though, PNs generally branch far less broadly than they do in locusts (Wong et al., 2002
). Thus, the contributions of oscillations toward the sparsening of odor representations may be less in the fly than in the locust.
Here, we demonstrated that common odors evoke neural oscillations in Drosophila
, and found these oscillations originate in the AL and are transmitted to the MB. Using a genetic strategy, we identified two classes of inhibitory LNs in Drosophila
. In terms of their connectivity patterns, these LNs appear similar to inhibitory neurons in the vertebrate olfactory bulb: LN2 cells appear to associate directly with both ORNs and PNs as do periglomerular cells with ORNs and mitral cells, while LN1 cells appear to associate directly only with PNs, as do granule cells with mitral cells (Shepherd and Greer, 1998
). Interestingly, Drosophila
LN2 cells are necessary for oscillations, while in vertebrates granule cells are important for oscillations (Schoppa, 2006
), likely because these neurons provide similar connective patterns among glomeruli. Both LN2 and granule cells have wide branching patterns suggesting that global inhibition of glomerular activity by each neuron may be necessary to cause oscillations.
By virtue of its amenability to genetic manipulation, Drosophila has become a leading experimental model for the study of olfaction. We have shown that Drosophila shares prominent features of olfactory processing with other insects and vertebrates. Applying genetic tools will allow dissecting the mechanisms and functions of neural oscillations with unprecedented precision.