Spontaneous olfactory receptor neuron activity determines follower cell response properties.

Noisy or spontaneous activity is common in neural systems and poses a challenge to detecting and discriminating signals. Here we use the locust to answer fundamental questions about noise in the olfactory system: Where does spontaneous activity originate? How is this activity propagated or reduced throughout multiple stages of neural processing? What mechanisms favor the detection of signals despite the presence of spontaneous activity? We found that spontaneous activity long observed in the secondary projection neurons (PNs) originates almost entirely from the primary olfactory receptor neurons (ORNs) rather than from spontaneous circuit interactions in the antennal lobe, and that spontaneous activity in ORNs tonically depolarizes the resting membrane potentials of their target PNs and local neurons (LNs) and indirectly tonically depolarizes tertiary Kenyon cells (KCs). However, because these neurons have different response thresholds, in the absence of odor stimulation, ORNs and PNs display a high spontaneous firing rate but KCs are nearly silent. Finally, we used a simulation of the olfactory network to show that discrimination of signal and noise in the KCs is best when threshold levels are set so that baseline activity in PNs persists. Our results show how the olfactory system benefits from making a signal detection decision after a point of maximal information convergence, e.g., after KCs pool inputs from many PNs.