Classifier and supporting files for "A novel automated approach for improving standardization of the marble burying test enables quantification of burying bouts and activity characteristics"

Lucas Wahl 7940444b8a 'datacite.yml' updaten 2 years ago
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datacite.yml 7940444b8a 'datacite.yml' updaten 2 years ago

README.md

Marble-burying-classifier-and-supporting-files

Classifier and supporting files for "A novel automated approach for improving standardization of the marble burying test enables quantification of burying bouts and activity characteristics"

In order to obtain maximum classification accuracy, we recommend training a custom classifier on newly acquired videos as the experimental conditions such as light, cage dimensions, mouse color and bedding can differ across laboratories. The classifier can then be used for all newly acquired videos.

datacite.yml
Title Marble burying classifier and supporting files
Authors Wahl,Lucas;Department of Neuroscience, Erasmus Medical Center Rotterdam, The Netherlands;ORCID:0000-0002-8078-5113
Punt,Mattijs;Department of Clinical Genetics, Erasmus Medical Center Rotterdam, The Netherlands;ORCID:0000-0002-5730-7666
Arbab,Tara;Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, Netherlands & Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands;ORCID:0000-0002-7294-7223
Willuhn,Ingo;Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, Netherlands & Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands;ORCID:0000-0001-6540-6894
Elgersma,Ype;Department of Clinical Genetics, Erasmus Medical Center Rotterdam, The Netherlands;ORCID:0000-0002-3758-1297
Badura,Aleksandra;Department of Neuroscience, Erasmus Medical Center Rotterdam, The Netherlands;ORCID:0000-0002-0119-5108
Description Classifier and supporting files for: A novel automated approach for improving standardization of the marble burying test enables quantification of burying bouts and activity characteristics
License Creative Commons CC0 1.0 Public Domain Dedication (https://creativecommons.org/publicdomain/zero/1.0/)
References A novel automated approach for improving standardization of the marble burying test enables quantification of burying bouts and activity characteristics, Lucas Wahl, A. Mattijs Punt, Tara Arbab, Ingo Willuhn, Ype Elgersma, Aleksandra Badura [doi::tba] (IsSupplementTo)
Funding NWO,VIDI/917.18.380,2018/ZonMw - AB
NWO,VIDI 864.14.010,2015/06367/ALW - IW
NWO,Gravitation program BRAINSCAPES 024.004.012 - IW
the Foundation for OCD Research, IW
Amsterdam Brain and Cognition (ABC), Project Grant 2021 - TA and IW
Keywords Neuroscience
Marble burying
Machine learning
Automated classification
Resource Type Dataset