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Sweet Choices - On the Value of Fruit Fly Foraging Decisions

Research output: Book/anthology/dissertation/reportPh.D. thesisResearch

  • Sophie Seidenbecher
Foraging, or searching for food, is a fundamental behavior exhibited by all moving
animals throughout evolution. For that reason it is valid to hypothesize that
certain behaviors of foraging and their genetic basis are conserved between different
species. Drosophila melanogaster is an advantageous model system due to the
well-established genetic tools available to manipulate their nervous systems. With
a properly defined behavior and those genetic tools, it should be possible to dissect
aspects of the genetic basis of foraging decisions. In order to lay the foundation for
understanding the link between the genes and behavior, I used quantitative analyses
and computational models to describe their foraging behavior. I used a simple linear
track arena under an operant conditioning scheme, where the flies were foraging
for an optogenetic sugar receptor neuron stimulation. The flies exhibited a range
of altered behaviors upon the stimulation and I could show that they experienced
the stimulation as rewarding. Furthermore, I found that a reinforcement learning
model with forgetting as best describing several aspects of the animals’ behavior.
Reinforcement learning models are widely used in neuroscience and describe how
an agent learns to produce profitable actions, by updating a value of the available
actions through a reward prediction error. The flies appear to be using such an update
process to decide whether to return to a previously rewarded area in the arena
in a way that they forget this value if they didn’t make the choice to return. This
will be the starting point to perform a screen for genes assumed to be involved in
foraging-choice and value update behavior and to relate gene knock-down induced
behavioral changes to the reinforcement learning model parameters.
Original languageEnglish
PublisherAarhus Universitet
Publication statusPublished - Jul 2019

Note re. dissertation

Termination date: 01.07.2019

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ID: 151659106