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Drosophila learn efficient paths to a food source

Rapeechai Navawongse, Deepak Choudhury, Marlena Raczkowska, James Charles Stewart, Terrence Lim, Mashiur Rahman, Alicia Guek Geok Toh, Zhiping Wang, Adam Claridge-Chang
doi: https://doi.org/10.1101/033969
Rapeechai Navawongse
aInstitute of Molecular and Cell Biology, 61 Biopolis Drive, Singapore 138673
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Deepak Choudhury
bSingapore Institute of Manufacturing Technology, 71 Nanyang Drive, Singapore 638075
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Marlena Raczkowska
aInstitute of Molecular and Cell Biology, 61 Biopolis Drive, Singapore 138673
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James Charles Stewart
aInstitute of Molecular and Cell Biology, 61 Biopolis Drive, Singapore 138673
eSieva Pte Ltd
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Terrence Lim
bSingapore Institute of Manufacturing Technology, 71 Nanyang Drive, Singapore 638075
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Mashiur Rahman
cDuke-NUS Medical School, 61 Biopolis Drive, Singapore 138673
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Alicia Guek Geok Toh
bSingapore Institute of Manufacturing Technology, 71 Nanyang Drive, Singapore 638075
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Zhiping Wang
bSingapore Institute of Manufacturing Technology, 71 Nanyang Drive, Singapore 638075
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Adam Claridge-Chang
aInstitute of Molecular and Cell Biology, 61 Biopolis Drive, Singapore 138673
cDuke-NUS Medical School, 61 Biopolis Drive, Singapore 138673
dDepartment of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 138673
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ABSTRACT

Elucidating the genetic, and neuronal bases for learned behavior is a central problem in neuroscience. A leading system for neurogenetic discovery is the vinegar fly Drosophila melanogaster; fly memory research has identified genes and circuits that mediate aversive and appetitive learning. However, methods to study adaptive food-seeking behavior in this animal have lagged decades behind rodent feeding analysis, largely due to the challenges presented by their small scale. There is currently no method to dynamically control flies’ access to food. In rodents, protocols that use dynamic food delivery are a central element of experimental paradigms that date back to the influential work of Skinner. This method is still commonly used in the analysis of learning, memory, addiction, feeding, and many other subjects in experimental psychology. The difficulty of microscale food delivery means this is not a technique used in fly behavior. In the present manuscript we describe a microfluidic chip integrated with machine vision and automation to dynamically control defined liquid food presentations and sensory stimuli. Strikingly, repeated presentations of food at a fixed location produced improvements in path efficiency during food approach. This indicates that improved path choice is a learned behavior; the other foraging metrics examined showed no evidence of learning. Active control of food availability using this microfluidic system is a valuable addition to the methods currently available for the analysis of learned feeding behavior in flies.

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  • ↵† Shared first authors

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted December 09, 2015.
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Drosophila learn efficient paths to a food source
Rapeechai Navawongse, Deepak Choudhury, Marlena Raczkowska, James Charles Stewart, Terrence Lim, Mashiur Rahman, Alicia Guek Geok Toh, Zhiping Wang, Adam Claridge-Chang
bioRxiv 033969; doi: https://doi.org/10.1101/033969
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Drosophila learn efficient paths to a food source
Rapeechai Navawongse, Deepak Choudhury, Marlena Raczkowska, James Charles Stewart, Terrence Lim, Mashiur Rahman, Alicia Guek Geok Toh, Zhiping Wang, Adam Claridge-Chang
bioRxiv 033969; doi: https://doi.org/10.1101/033969

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