Exhaustive Multi-Parametric Assessment of the Behavioral Array of Daily Activities of Mice Using Cluster and Factor Analysis

Frontiers in Behavioral Neuroscience
Kenzo YamamotoDenis Gris

Abstract

Using automated supervised behavioral assessment software, we recorded and analyzed 24 h non-interrupted recordings of mice for a duration of 11 days. With the assistance of free R programming, we used correlation matrix-based hierarchical clustering and factor analysis to separate the 33 activities into meaningful clusters and groups without losing the exhaustive nature of the findings. These groups represent novel meaningful behavioral patterns exhibited by mice in home cage. Thirty-three activities were separated into 5 clusters based on dissimilarity between activities and 6 factors based on statistical modeling. Using these two methods, we describe and compare behavioral arrays of two groups of animals: 1. Continuously recorded for 11 days in social isolation and 2. Intermittently socially isolated for recording on days 1, 3, 5, 8, and 10, while socializing on the other days. This is the first work to our knowledge that interprets mouse home cage activities throughout a 24 h period and proposes a base line of a daily routine of a healthy C57Bl/6J mouse that can be used for various experimental paradigms, including disease, neuroinflammation, or drug testing to trace behavioral changes that follow intervention. In this work...Continue Reading

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Citations

Feb 10, 2020·Journal of Insect Physiology·Newmar Pinto MarliéreAlessandra Aparecida Guarneri
Oct 2, 2021·Frontiers in Neuroscience·Marjan GharagozlooDenis Gris

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Software Mentioned

nFactorspsych
reshape2
devtools
R programming
Any Video Converter
PerformanceAnalytics
ggplot2
Visual Basic
Rmisc
R

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