Traner, M. | Search bioRxiv

bioRxiv2023

Dynamic walking behavior during odor trail-following in locusts

One of the important subsets of odor sources used in olfactory navigation is surface-bound sources, which can broadly take the form of point sources or trails. Odor trails, in particular, have been observed to be highly relevant components of olfactory-based navigation for species as broadly distributed as dogs and ants. Here, we present an automated treadmill setup capable of dynamically printing odor trails of arbitrary lengths and configurations, and with closed-loop control of speed based on the subjects movement. We used this setup to characterize trail-following behavior in locusts (Schistocerca americana). The free-moving behavior of the locusts is more naturalistic and is richer in plumbable data than many traditional assays. We reveal broad classes of behavioral walking motifs and their dynamic transitions as locusts pursue or avoid an odor trail. Furthermore, we show how these motifs vary across individuals, with the identity of the odorant and with respect to the sex of the organism. Our dataset and analyses provide a first demonstration that this model organism is capable of robust odor trail following, and provides a comprehensive analysis of the dynamic motifs that underlie this behavioral capability.

animal behavior and cognition↗

bioRxiv2020

Explosive sensing with insect-based biorobots

Stand-off chemical sensing is an important capability with applications in several domains including homeland security. Engineered devices for this task, popularly referred to as electronic noses, have limited capacity compared to the broad-spectrum abilities of the biological olfactory system. Therefore, we propose a hybrid bio-electronic solution that directly takes advantage of the rich repertoire of olfactory sensors and sophisticated neural computational framework available in an insect olfactory system. We show that select subsets of neurons in the locust (Schistocerca americana) brain were activated upon exposure to various explosive chemical species (such as DNT and TNT). Responses from an ensemble of neurons provided a unique, multivariate fingerprint that allowed discrimination of explosive vapors from non-explosive chemical species and from each other. Notably, target chemical recognition could be achieved within a few hundred milliseconds of exposure. Finally, we developed a minimally-invasive surgical approach and mobile multi-unit electrophysiological recording system to tap into the neural signals in a locust brain and realize a biorobotic explosive sensing system. In sum, our study provides the first demonstration of how biological olfactory systems (sensors and computations) can be hijacked to develop a cyborg chemical sensing approach. SUMMARYWe demonstrate a bio-robotic chemical sensing approach where signals from an insect brain are directly utilized to detect and distinguish various explosive chemical vapors.

bioengineering↗