data science and larva behavior

I had the great pleasure of being on the oral qualifying exam for Rui Wu (NYU), who is looking at the behavior and neural computation of fruit-fly larvae. She told us about her research so far (in preparation for her PhD project), in which she has built a fully data-driven model of larval behavior, classifying multiple different behaviors in an unsupervised model. She can also show that behavioral changes are correlated with changes to larval stimulus. She did all this by dimensionality-reducing video data with a set of clever techniques.

I learned an immense amount in her seminar. One is that they can genetically modify the larvae so that their olfactory senses can be stimulated with light! That's crazy but makes for better experimental techniques. Another is that they can read from individual neurons simultaneously with monitoring large-scale behavior. The fly is a model neural system that does complex things but with very few neurons, so there is a hope of reverse engineering the full computation. A truly out-there idea is that if the computation and behavior is understood, the larvae could be controlled or driven like an engineering system.

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