Follow your nose
New insights reveal how fruit flies learn to associate smells with bad experiences.
We can learn a surprising amount about how the brain forms memories by studying the humble fruit fly. These insects can learn to associate odors with positive or negative experiences, allowing them to then seek out ‘rewarded’ odors and avoid ‘punished’ ones.
This association takes place in a brain region called the mushroom body, and it involves two types of neurons: Kenyon cells, which detect odors, and MBONs, which lead to approach or avoidance behaviors. When Kenyon cells detect an odor accompanying an unpleasant event, they weaken their connections with the MBONs that trigger approach behaviors. This prevents the fly from coming close to that odor in the future.
Kenyon cells exchange signals with other neurons using a chemical called acetylcholine, which attaches onto the cells through two types of receptors: nicotinic and muscarinic. Studies in fruit fly larvae suggest that muscarinic receptors are required in Kenyon cells for the insects to learn how to associate odors with unpleasant experiences.
Bielopolski et al. now show that this is also the case in adult flies. Surprisingly, while acetylcholine usually excites fly neurons, activating muscarinic receptors inhibits Kenyon cells rather than exciting them. Labeled muscarinic receptors revealed that the receptors act within the input region of Kenyon cells. Moreover, reducing the levels of muscarinic receptors inside the cells stops flies from associating an odor with a mild electric shock. This manipulation also prevents the learning experience from weakening connections from Kenyon cells onto an MBON that triggers approach behavior. This suggests that allowing these changes in connectivity might be why muscarinic receptors are important for memory.
Understanding how memory works in flies can reveal basic principles that apply to many species, including humans. Such knowledge could ultimately help us improve the memory of patients with dementia, but also inspire better algorithms for artificial intelligence.
Originally published at https://elifesciences.org/digests/48264.