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Sweet Choices - On the Value of Fruit Fly Foraging Decisions

Publikation: Bog/antologi/afhandling/rapportPh.d.-afhandlingForskning

Standard

Sweet Choices - On the Value of Fruit Fly Foraging Decisions. / Seidenbecher, Sophie.

Aarhus Universitet, 2019.

Publikation: Bog/antologi/afhandling/rapportPh.d.-afhandlingForskning

Harvard

Seidenbecher, S 2019, Sweet Choices - On the Value of Fruit Fly Foraging Decisions. Aarhus Universitet.

APA

Seidenbecher, S. (2019). Sweet Choices - On the Value of Fruit Fly Foraging Decisions. Aarhus Universitet.

CBE

Seidenbecher S 2019. Sweet Choices - On the Value of Fruit Fly Foraging Decisions. Aarhus Universitet.

MLA

Seidenbecher, Sophie Sweet Choices - On the Value of Fruit Fly Foraging Decisions Aarhus Universitet. 2019.

Vancouver

Seidenbecher S. Sweet Choices - On the Value of Fruit Fly Foraging Decisions. Aarhus Universitet, 2019.

Author

Seidenbecher, Sophie. / Sweet Choices - On the Value of Fruit Fly Foraging Decisions. Aarhus Universitet, 2019.

Bibtex

@phdthesis{296ed63ac41044a08266abf508b0f963,
title = "Sweet Choices - On the Value of Fruit Fly Foraging Decisions",
abstract = "Foraging, or searching for food, is a fundamental behavior exhibited by all movinganimals throughout evolution. For that reason it is valid to hypothesize thatcertain behaviors of foraging and their genetic basis are conserved between differentspecies. Drosophila melanogaster is an advantageous model system due to thewell-established genetic tools available to manipulate their nervous systems. Witha properly defined behavior and those genetic tools, it should be possible to dissectaspects of the genetic basis of foraging decisions. In order to lay the foundation forunderstanding the link between the genes and behavior, I used quantitative analysesand computational models to describe their foraging behavior. I used a simple lineartrack arena under an operant conditioning scheme, where the flies were foragingfor an optogenetic sugar receptor neuron stimulation. The flies exhibited a rangeof altered behaviors upon the stimulation and I could show that they experiencedthe stimulation as rewarding. Furthermore, I found that a reinforcement learningmodel with forgetting as best describing several aspects of the animals{\textquoteright} behavior.Reinforcement learning models are widely used in neuroscience and describe howan agent learns to produce profitable actions, by updating a value of the availableactions through a reward prediction error. The flies appear to be using such an updateprocess to decide whether to return to a previously rewarded area in the arenain a way that they forget this value if they didn{\textquoteright}t make the choice to return. Thiswill be the starting point to perform a screen for genes assumed to be involved inforaging-choice and value update behavior and to relate gene knock-down inducedbehavioral changes to the reinforcement learning model parameters.",
author = "Sophie Seidenbecher",
year = "2019",
month = jul,
language = "English",
publisher = "Aarhus Universitet",

}

RIS

TY - BOOK

T1 - Sweet Choices - On the Value of Fruit Fly Foraging Decisions

AU - Seidenbecher, Sophie

PY - 2019/7

Y1 - 2019/7

N2 - Foraging, or searching for food, is a fundamental behavior exhibited by all movinganimals throughout evolution. For that reason it is valid to hypothesize thatcertain behaviors of foraging and their genetic basis are conserved between differentspecies. Drosophila melanogaster is an advantageous model system due to thewell-established genetic tools available to manipulate their nervous systems. Witha properly defined behavior and those genetic tools, it should be possible to dissectaspects of the genetic basis of foraging decisions. In order to lay the foundation forunderstanding the link between the genes and behavior, I used quantitative analysesand computational models to describe their foraging behavior. I used a simple lineartrack arena under an operant conditioning scheme, where the flies were foragingfor an optogenetic sugar receptor neuron stimulation. The flies exhibited a rangeof altered behaviors upon the stimulation and I could show that they experiencedthe stimulation as rewarding. Furthermore, I found that a reinforcement learningmodel with forgetting as best describing several aspects of the animals’ behavior.Reinforcement learning models are widely used in neuroscience and describe howan agent learns to produce profitable actions, by updating a value of the availableactions through a reward prediction error. The flies appear to be using such an updateprocess to decide whether to return to a previously rewarded area in the arenain a way that they forget this value if they didn’t make the choice to return. Thiswill be the starting point to perform a screen for genes assumed to be involved inforaging-choice and value update behavior and to relate gene knock-down inducedbehavioral changes to the reinforcement learning model parameters.

AB - Foraging, or searching for food, is a fundamental behavior exhibited by all movinganimals throughout evolution. For that reason it is valid to hypothesize thatcertain behaviors of foraging and their genetic basis are conserved between differentspecies. Drosophila melanogaster is an advantageous model system due to thewell-established genetic tools available to manipulate their nervous systems. Witha properly defined behavior and those genetic tools, it should be possible to dissectaspects of the genetic basis of foraging decisions. In order to lay the foundation forunderstanding the link between the genes and behavior, I used quantitative analysesand computational models to describe their foraging behavior. I used a simple lineartrack arena under an operant conditioning scheme, where the flies were foragingfor an optogenetic sugar receptor neuron stimulation. The flies exhibited a rangeof altered behaviors upon the stimulation and I could show that they experiencedthe stimulation as rewarding. Furthermore, I found that a reinforcement learningmodel with forgetting as best describing several aspects of the animals’ behavior.Reinforcement learning models are widely used in neuroscience and describe howan agent learns to produce profitable actions, by updating a value of the availableactions through a reward prediction error. The flies appear to be using such an updateprocess to decide whether to return to a previously rewarded area in the arenain a way that they forget this value if they didn’t make the choice to return. Thiswill be the starting point to perform a screen for genes assumed to be involved inforaging-choice and value update behavior and to relate gene knock-down inducedbehavioral changes to the reinforcement learning model parameters.

M3 - Ph.D. thesis

BT - Sweet Choices - On the Value of Fruit Fly Foraging Decisions

PB - Aarhus Universitet

ER -