What Has the Brain Evolved to Know About the Natural Olfactory World?
Most sensory stimuli in the natural world exhibit strong statistical regularities. For example, if a given pixel in a visual scene is dark, there is a high chance that adjacent pixels will also be dark. A proposed general principle of sensory neuroscience is that the brain’s circuitry is designed to take advantage of these statistical regularities. In particular, stimuli with natural statistics appear to be unusually good at recruiting mutually antagonistic interactions between nearby neurons. Mutual antagonism (or “lateral inhibition”) is thought to increase the efficiency by which natural stimuli are encoded by neural populations. Historically, these ideas have been explored mostly in the context of the visual system. In this talk, I will re-examine these ideas in the context of a much less well-studied sensory modality – namely, the sense of smell. I ask whether the olfactory world exhibits statistical regularities, and if so, what these “natural odor statistics” might look like. I will also critically explore the idea that the circuitry of the brain’s olfactory processing centers could be adapted to exploit such natural statistics.
Suggested Reading:
Odor plumes and how insects use them.pdf
The odor coding system of Drosophila.pdf
About the Speaker:
Rachel Wilson is an HHMI Early Career Scientist at Harvard Medical School. Rachel Wilson is using Drosophila to study how neural circuits transform sensory signals, with a special emphasis on the olfactory system.
Insects, Rachel Wilson says, may be closer cousins than we imagine, at least in terms of their brain power. “Of course they’re not terribly smart. But unlike simpler invertebrates like slugs or worms, the way they interact with the world is relatively flexible. They can play a lot of games with only about a hundred thousand brain cells.” This balance between simplicity and complexity is what attracted Wilson to studying the fruit fly Drosophila as a model for investigating neural circuit function.
