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Precise quantification of behavioral individuality from 80 million decisions across 183,000 flies

de Bivort, Benjamin and Buchanan, Seaan and Skutt-Kakaria, Kyobi and Gajda, Erika and O'Leary, Chelsea and Reimers, Pablo and Akhund-Zade, Jamilla and Senft, Rebecca and Maloney, Ryan and Ho, Sandra and Werkhoven, Zachary and Smith, Matthew A.-Y. (2021) Precise quantification of behavioral individuality from 80 million decisions across 183,000 flies. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20211220-590074000

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Abstract

Individual animals behave differently from each other. This variability is a component of personality and arises even when genetics and environment are held constant. Discovering the biological mechanisms underlying behavioral variability depends on efficiently measuring individual behavioral bias, a requirement that is facilitated by automated, high-throughput experiments. We compiled a large data set of individual locomotor behavior measures, acquired from over 183,000 fruit flies walking in Y-shaped mazes. With this data set we first conducted a "computational ethology natural history" study to quantify the distribution of individual behavioral biases with unprecedented precision and examine correlations between behavioral measures with high power. We discovered a slight, but highly significant, left-bias in spontaneous locomotor decision-making. We then used the data to evaluate standing hypotheses about biological mechanisms affecting behavioral variability, specifically: the neuromodulator serotonin and its precursor transporter, heterogametic sex, and temperature. We found a variety of significant effects associated with each of these mechanisms that were behavior-dependent. This indicates that the relationship between biological mechanisms and behavioral variability may be highly context dependent. Going forward, automation of behavioral experiments will likely be essential in teasing out the complex causality of individuality.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
https://doi.org/10.1101/2021.12.15.472856DOIArticle
http://lab.debivort.org/precise-quantification-of-behavioral-individuality/Related ItemCode
https://zenodo.org/record/5784716Related ItemData
ORCID:
AuthorORCID
de Bivort, Benjamin0000-0001-6165-7696
Buchanan, Seaan0000-0002-0171-3382
Skutt-Kakaria, Kyobi0000-0002-7826-6736
O'Leary, Chelsea0000-0001-9621-8781
Reimers, Pablo0000-0003-0547-1349
Akhund-Zade, Jamilla0000-0001-5589-8258
Senft, Rebecca0000-0003-0081-4170
Maloney, Ryan0000-0002-6111-7822
Werkhoven, Zachary0000-0003-0611-5864
Smith, Matthew A.-Y.0000-0003-0913-1392
Additional Information: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-NC 4.0 International license. We thank Ed Soucy, Joel Greenwood, and Brett Graham of Harvard’s Neurotechnology Core for their help with instrument engineering. BdB was supported by a Sloan Research Fellowship, a Klingenstein-Simons Fellowship Award, a Smith Family Odyssey Award, a Harvard/MIT Basic Neuroscience Grant, National Science Foundation grant no. IOS-1557913, and NIH/NINDS grant no. 1R01NS121874-01. KSK and ZW were supported by NSF Graduate Research Fellowships #DGE2013170544 and #DGE1144152. JAZ and MAYS were supported by the Harvard Quantitative Biology Initiative. JAZ was supported by The NSF-Simons Center for Mathematical and Statistical Analysis of Biology at Harvard, award number #1764269. The authors have declared no competing interest.
Funders:
Funding AgencyGrant Number
Alfred P. Sloan FoundationUNSPECIFIED
Klingenstein-Simons FellowshipUNSPECIFIED
Smith Family FoundationUNSPECIFIED
Harvard UniversityUNSPECIFIED
Massachusetts Institute of Technology (MIT)UNSPECIFIED
NSFIOS-1557913
NIH1R01NS121874-01
NSF Graduate Research FellowshipDGE-2013170544
NSF Graduate Research FellowshipDGE-1144152
NSFDMS-1764269
Subject Keywords:handedness, fluctuating asymmetry, variability, high-throughput behavior, automation, ethology
DOI:10.1101/2021.12.15.472856
Record Number:CaltechAUTHORS:20211220-590740000
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20211220-590074000
Official Citation:Precise quantification of behavioral individuality from 80 million decisions across 183,000 flies Benjamin de Bivort, Sean Buchanan, Kyobi Skutt-Kakaria, Erika Gajda, Chelsea O’Leary, Pablo Reimers, Jamilla Akhund-Zade, Rebecca Senft, Ryan Maloney, Sandra Ho, Zach Werkhoven, Matthew A-Y Smith bioRxiv 2021.12.15.472856; doi: https://doi.org/10.1101/2021.12.15.472856
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:112553
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:20 Dec 2021 18:23
Last Modified:20 Dec 2021 18:23

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