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Rigor and reproducibility in rodent behavioral research
Journal article   Peer reviewed

Rigor and reproducibility in rodent behavioral research

Maria Gulinello, Heather A Mitchell, Qiang Chang, W Timothy O'Brien, Zhaolan Zhou, Ted Abel, Li Wang, Joshua G Corbin, Surabi Veeraragavan, Rodney C Samaco, …
Neurobiology of learning and memory, Vol.165, pp.106780-106780
11/2019
DOI: 10.1016/j.nlm.2018.01.001
PMID: 29307548
url
https://www.ncbi.nlm.nih.gov/pmc/articles/6034984View
Open Access

Abstract

•Strategies to maximize rigor and reproducibility in rodent behavioral assays.•Replicability of translational rodent models as preclinical research tools.•Key methods for one example, the novel object recognition cognitive test.•Extensive literature cited will refer the reader to detailed appropriate methods. Behavioral neuroscience research incorporates the identical high level of meticulous methodologies and exacting attention to detail as all other scientific disciplines. To achieve maximal rigor and reproducibility of findings, well-trained investigators employ a variety of established best practices. Here we explicate some of the requirements for rigorous experimental design and accurate data analysis in conducting mouse and rat behavioral tests. Novel object recognition is used as an example of a cognitive assay which has been conducted successfully with a range of methods, all based on common principles of appropriate procedures, controls, and statistics. Directors of Rodent Core facilities within Intellectual and Developmental Disabilities Research Centers contribute key aspects of their own novel object recognition protocols, offering insights into essential similarities and less-critical differences. Literature cited in this review article will lead the interested reader to source papers that provide step-by-step protocols which illustrate optimized methods for many standard rodent behavioral assays. Adhering to best practices in behavioral neuroscience will enhance the value of animal models for the multiple goals of understanding biological mechanisms, evaluating consequences of genetic mutations, and discovering efficacious therapeutics.
Experimental Design Statistical analysis Behavioral assays Reproducibility Rigor Rats Replication Mice Cognitive Behavior Novel object recognition Best practices

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