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

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 soc

SUBMITTER: Yamamoto K 

PROVIDER: S-EPMC6125369 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature