Flying insects rapidly stabilize after perturbations using both visual and mechanosensory inputs for active control. Insect halteres are mechanosensory organs that encode inertial forces to aid rapid course correction during flight but serve no aerodynamic role and are specific to two orders of insects (Diptera and Strepsiptera). Aside from the literature on halteres and recent work on the antennae of the hawkmoth Manduca sexta, it is unclear how other flying insects use mechanosensory information to control body dynamics. The mechanosensory structures found on the halteres, campaniform sensilla, are also present on wings, suggesting that the wings can encode information about flight dynamics. We show that the neurons innervating these sensilla on the forewings of M. sexta exhibit spiketiming precision comparable to that seen in previous reports of campaniform sensilla, including haltere neurons. In addition, by attaching magnets to the wings of moths and subjecting these animals to a simulated pitch stimulus via a rotating magnetic field during tethered flight, we elicited the same vertical abdominal flexion reflex these animals exhibit in response to visual or inertial pitch stimuli. Our results indicate that, in addition to their role as actuators during locomotion, insect wings serve as sensors that initiate reflexes that control body dynamics.

What is the meaning associated with a single action potential in a neural spike train? The answer depends on the way the question is formulated. One general approach toward formulating this question involves estimating the average stimulus waveform preceding spikes in a spike train. Many different algorithms have been used to obtain such estimates, ranging from spike-triggered averaging of stimuli to correlation-based extraction of "stimulus-reconstruction" kernels or spatiotemporal receptive fields. We demonstrate that all of these approaches miscalculate the stimulus feature selectivity of a neuron. Their errors arise from the manner in which the stimulus waveforms are aligned to one another during the calculations. Specifically, the waveform segments are locked to the precise time of spike occurrence, ignoring the intrinsic "jitter" in the stimulus-to-spike latency. We present an algorithm that takes this jitter into account. "Dejittered" estimates of the feature selectivity of a neuron are more accurate (i.e., provide a better estimate of the mean waveform eliciting a spike) and more precise (i.e., have smaller variance around that waveform) than estimates obtained using standard techniques. Moreover, this approach yields an explicit measure of spike-timing precision. We applied this technique to study feature selectivity and spike-timing precision in two types of sensory interneurons in the cricket cercal system. The dejittered estimates of the mean stimulus waveforms preceding spikes were up to three times larger than estimates based on the standard techniques used in previous studies and had power that extended into higher-frequency ranges. Spike timing precision was ϳ5 ms.

Summary Sensory inputs are often fluctuating and intermittent, yet animals reliably utilize them to direct behavior. Here we ask how natural stimulus fluctuations influence the dynamic neural encoding of odors. Using the locust olfactory system, we isolated two main causes of odor intermittency: chaotic odor plumes and active sampling behaviors. Despite their irregularity, chaotic odor plumes still drove dynamic neural response features including the synchronization, temporal patterning, and short-term plasticity of spiking in projection neurons, enabling classifier-based stimulus identification and activating downstream decoders (Kenyon cells). Locusts can also impose odor intermittency through active sampling movements with their unrestrained antennae. Odors triggered immediate, spatially-targeted antennal scanning that, paradoxically, weakened individual neural responses. However, these frequent but weaker responses were highly informative about stimulus location. Thus, not only are odor-elicited dynamic neural responses compatible with natural stimulus fluctuations and important for stimulus identification, but locusts actively increase intermittency, possibly to improve stimulus localization.