Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

Computer Animation Technology in Behavioral Sciences: A Sequential, Automatic, and High-Throughput roach to Quantifying Personality in Zebrafish

Simple item page
dc.contributor.authorFangmeier, Melissa L.
dc.contributor.authorNoble, Daniel W. A.
dc.contributor.authorO'Dea, Rose E.
dc.contributor.authorUsui, Takuji
dc.contributor.authorLagisz, M.
dc.contributor.authorHesselson, Daniel
dc.contributor.authorNakagawa, Shinichi
dc.date.accessioned2021-08-09T05:27:10Z
dc.date.issued2018-04-01
dc.description.abstractAn emergent field of animal personality necessitates a method for repeated high-throughput quantification of behavioral traits across contexts. In this study, we have developed an automated video stimulus approach to sequentially present different contexts relevant to five "personality" traits (exploration, boldness, neophobia, aggression, and sociability), successfully quantifying repeatable trait measurements in multiple individuals simultaneously. Although our method is designed to quantify personality traits in zebrafish, our approach can accommodate the quantification of other behaviors, and could be customized for other species. All digital materials and detailed protocols are publicly available online for researchers to freely use and modify.en_AU
dc.description.sponsorshipSN is supported by Future Fellowship (FT130100268). DN was supported by an ARC Discovery Early Career Research Award (DE150101774) and a UNSW VC Research Fellowship. DH was supported by NHMRC Project Grants (GNT1063981 and GNT1130222).en_AU
dc.identifier.citationMelissa L. Fangmeier, Daniel W.A. Noble, Rose E. O'Dea, Takuji Usui, Malgorzata Lagisz, Daniel Hesselson, and Shinichi Nakagawa.Zebrafish.Apr 2018.206-210.http://doi.org/10.1089/zeb.2017.1532en_AU
dc.identifier.issn1545-8547en_AU
dc.identifier.urihttp://hdl.handle.net/1885/243294
dc.publisherMary Ann Liebert Inc.en_AU
dc.relationhttp://purl.org/au-research/grants/arc/DE150101774en_AU
dc.relationhttp://purl.org/au-research/grants/arc/FT130100268en_AU
dc.relationhttp://purl.org/au-research/grants/nhmrc/1063981en_AU
dc.relationhttp://purl.org/au-research/grants/nhmrc/1130222en_AU
dc.rights© 2018 Mary Ann Liebert, Inc.en_AU
dc.sourceZebrafishen_AU
dc.subjectbehavioral phenotypingen_AU
dc.subjectautomationen_AU
dc.subjectanimal personalityen_AU
dc.subjectconsistencyen_AU
dc.titleComputer Animation Technology in Behavioral Sciences: A Sequential, Automatic, and High-Throughput roach to Quantifying Personality in Zebrafishen_AU
dc.typeJournal articleen_AU
local.bibliographicCitation.issue2en_AU
local.bibliographicCitation.lastpage210en_AU
local.bibliographicCitation.startpage206en_AU
local.contributor.affiliationFangmeier, Melissa L., University of New South Walesen_AU
local.contributor.affiliationNoble, Daniel, College of Science, ANUen_AU
local.contributor.affiliationO'Dea, Rose E., University of New South Walesen_AU
local.contributor.affiliationUsui, Takuji, University of New South Walesen_AU
local.contributor.affiliationLagisz, M., University of New South Walesen_AU
local.contributor.affiliationHesselson, Daniel, Garvan Institute of Medical Researchen_AU
local.contributor.affiliationNakagawa, Shinichi, University of New South Walesen_AU
local.contributor.authoruidNoble, Daniel, u5062688en_AU
local.description.embargo2099-12-31
local.description.notesAdded manually as didn't import from ARIESen_AU
local.identifier.absfor310400en_AU
local.identifier.ariespublicationu3102795xPUB791en_AU
local.identifier.citationvolume15en_AU
local.identifier.doi10.1089/zeb.2017.1532en_AU
local.publisher.urlhttps://www.liebertpub.com/en_AU
local.type.statusPublished Versionen_AU

Downloads

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
zeb.2017.1532.pdf
Size:
191.92 KB
Format:
Adobe Portable Document Format
Description:
Download

Collections

ANU Research Publications

DSpace software copyright © 2002-2026 LYRASIS