Bouts of rest and physical activity in C57BL/6J mice

Abstract

The objective was to exploit the raw data output from a scalable home cage (type IIL IVC) monitoring (HCM) system (DVC(R)), to characterize pattern of undisrupted rest and physical activity (PA) of C57BL/6J mice. The systems tracking algorithm show that mice in isolation spend 67% of the time in bouts of long rest ([&ge;]40s) and 59 % of the time was interpreted as sleep. Twenty percent is physical activity (PA), split equally between local movements and locomotion. Decomposition revealed that a day contains [~]6500 discrete bouts of short and long rest, local and locomotor movements. Mice travel [~]330m per day, mainly during the dark hours, while travelling speed is similar through the light-dark cycle. Locomotor bouts are usually <0.2m and <1% are >1m. Tracking revealed also fits of abnormal behaviour. The starting positions of the bouts showed no preference for the rear over the front of the cage floor, while there was a strong bias for the peripheral (75%) over the central floor area. The composition of bouts has a characteristic circadian pattern, however, intrusive husbandry routines increased bout fragmentation by [~]40%. Extracting electrode activations density (EAD) from the raw data yielded results close to those obtained with the tracking algorithm, with 59% of time in long rest (<1 EAD s-1) and 20% in PA. We confirm that EAD correlates closely with movement distance (rs >0.95) and the data agreed in [~]96% of the file time. Thus, albeit EAD being less informative it may serve as a proxy for PA and rest, enabling monitoring group housed mice. The data show that a change in housing density from one to two, and up to three mice had the same effect size on EAD ([~]2) with no difference between sexes. The EAD deviated significantly from this stepwise increase with 4 mice per cage, suggesting a crowdedness stress inducing sex specific adaptations. We conclude that informative metrics on rest and PA can be automatically extracted from the raw data flow in near-real time (< 1 hrs). These metrics relay useful longitudinal information to those that use or care for the animals.