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What a locust can teach us about how neuromodulators alter odor processing

When you walk into a bakery and smell fresh cookies, the enticing smell draws you in. After you eat a handful of cookies, though, the same smell likely doesn't send you back for more. Researchers in the McKelvey School of Engineering at Washington University in St. Louis sought to determine the biological mechanisms in the brain that controllably alters odor-evoked behavior by using an unlikely…

What a locust can teach us about how neuromodulators alter odor processing

Researchers from the McKelvey School of Engineering at Washington University in St. Louis investigated the biological mechanisms that control odor-evoked behavior in locusts, using the insect as a model. They focused on two neuromodulators, dopamine and octopamine, which have opposing effects on the brain's processing of odors. Dopamine, involved in the brain's reward system, made the locusts' olfactory neural networks highly sensitive to various scents, including grass, lemon, rose, almond, and a spicy floral aroma.

As a result, the locusts showed increased neural responses to all presented odors and exhibited appetitive behavior, such as opening sensory appendages near their mouth parts to grab or touch food. Conversely, when exposed to octopamine, the locusts' odor-related brain activity and behavioral responses decreased. The researchers discovered that dopamine suppressed a specific subset of inhibitory GABAergic local neurons, releasing the olfactory circuits from inhibition and boosting neural network output.

Octopamine, on the other hand, did not affect local neuron activity at all. This patterned increase and decrease in neural responses, while preserving the identity of the stimulus, suggests that different neuromodulators can control the level of inhibition in distinct groups of local neurons, ultimately modulating the overall activity of the antennal lobe neural network that processes sensory input from the insect's antenna.

Written by urgent.news from Phys.org's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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