Unified behavioral scoring for preclinical models

Harrison, David J., Creeth, Hugo D. J., Tyson, Hannah R., Boque-Sastre, Raquel ORCID: https://orcid.org/0000-0002-0214-8848, Isles, Anthony R. ORCID: https://orcid.org/0000-0002-7587-5712, Palme, Rupert, Touma, Chadi and John, Rosalind M. ORCID: https://orcid.org/0000-0002-3827-7617 2020. Unified behavioral scoring for preclinical models. Frontiers in Neuroscience 14 , 313. 10.3389/fnins.2020.00313

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Abstract

Preclinical mental health research relies upon animal models, and whilst many encouraging advances are being made, reproducibility and translational relevance may be limited by sub-optimal testing or model choices. Animal behaviors are complex and test batteries should be designed to include their multifaceted nature. However, multiple behavioral testing is often avoided due to cost, availability or statistical rigor. Additionally, despite the disparity in the incidence of mental health problems between the sexes, a move toward reducing animal numbers could be a deterrent to including both male and female animals. The current study introduces a unified scoring system for specific behavioral traits with the aim of maximizing the use of all data generated whilst reducing the incidence of statistical errors. Female and male mice from two common background strains were tested on behavior batteries designed to probe multiple aspects of anxiety-related and social behavioral traits. Results for every outcome measure were normalized to generate scores for each test and combined to give each mouse a single unified score for each behavioral trait. The unified behavioral scores revealed clear differences in the anxiety and stress-related, and sociability traits of mice. Principle component analysis of data demonstrated significant clustering of animals into their experimental groups. In contrast, individual tests returned an ambiguous mixture of non-significant trends and significant effects for various outcome measures. Utilizing a range of behavioral measures and combining all outcome measure data to produce unified scores provides a useful tool for detecting subtle behavioral traits in preclinical models.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Medicine Biosciences
Publisher:	Frontiers Media
ISSN:	1662-4548
Funders:	BBSRC
Date of First Compliant Deposit:	16 April 2020
Date of Acceptance:	17 March 2020
Last Modified:	05 Jan 2024 08:07
URI:	https://orca.cardiff.ac.uk/id/eprint/131041

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