Differential navigational strategies during spatial learning in a new modified version of the Oasis maze.

Behav Brain Res

Department of Neuroscience, Faculty of Medicine, Universidad de Chile, Chile; Biomedical Neuroscience Institute (BNI), Faculty of Medicine, Universidad de Chile, Chile. Electronic address:

Published: May 2020

During spatial navigation, some typical parameters of learning have been observed, such as latency or path length. However, these parameters are sensitive to patterns of navigation and orientation that are not easily measurable. In the present study, we used a modified version of the Oasis maze and evaluated different parameters of learning, navigation, and orientation in different animal groups. Through a PCA (Principal component analysis) we found different factors such as learning, navigation, speediness, anxiety, orientation, path variability, and turning behavior. Each factor gathers different groups of behavioral variables. ANOVA analysis of those factors demonstrates that some of them are more strongly modulated by trial progression, while others by animal group differences, indicating that each group of variables is better reflecting one of these dimensions. To understand the nature of these navigation differences, we studied orientation strategies between animal conditions and across trials. We found that the main navigational strategy used by the animals consist of locating the target and directing their behaviors towards this area. When testing how this strategy changed after cognitive impairment or enhancement, we found that AβOs treated animals (Amyloid β Oligomers, Alzheimer animal model) have strong orientation difficulties at locating the target at longer distances. While animals with learning enhancement (exercised rat) do not show changes in orientation behaviors. These analyses highlight that experimental manipulations affect learning, but also induced changes in the navigational strategies. We concluded that both dimensions can explain the differences observed in typical learning variables, such as latency or path length, motivating the development of new tools that asses this two-dimension as a separate but, interacting phenomenon.

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http://dx.doi.org/10.1016/j.bbr.2020.112555DOI Listing

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