Unbiased classification of spatial strategies in the Barnes maze

• DOI: 10.1093/bioinformatics/btw376
• Publication Date: 2016-07-05T01:59:34Z
• Authors: Tomer Illouz; Ravit Madar; Charlotte Clague; Kathleen J. Griff...; Yoram Louzoun; Eitan Okun
• Keywords: Barnes maze; Water maze

Abstract Motivation: Spatial learning is one of the most widely studied cognitive domains in neuroscience. The Morris water maze and Barnes are commonly used techniques to assess spatial memory rodents. Despite fact that these tasks well-validated paradigms for testing abilities, manual categorization performance into behavioral strategies subject individual interpretation, thus bias. We have previously described an unbiased machine-learning algorithm classify maze. Results: Here, we offer a support vector machine—based, automated, Barnes-maze strategy (BUNS) classification algorithm, as well score scale can be acquisition, reversal training probe trials. BUNS greatly benefit users it provides standardized method scoring scale, which cannot derived from typical data analysis. Availability Implementation: Freely available on web at http://okunlab.wix.com/okunlab MATLAB application. Contact: [e-mail] Supplementary information: Bioinformatics online.