Σφακιανάκης Αλέξανδρος
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Τρίτη 5 Δεκεμβρίου 2017

3-D motion capture for long-term tracking of spontaneous locomotor behaviors and circadian sleep/wake rhythms in mouse

Publication date: 1 February 2018
Source:Journal of Neuroscience Methods, Volume 295
Author(s): Melissa Sourioux, Emma Bestaven, Etienne Guillaud, Sandrine Bertrand, Magali Cabanas, Lea Milan, Willy Mayo, Maurice Garret, Jean-René Cazalets
BackgroundLocomotor activity provides an index of an animal's behavioral state. Here, we report a reliable and cost-effective method that allows long-term (days to months) simultaneous tracking of locomotion in mouse cohorts (here consisting of 24 animals).New methodThe technique is based on a motion capture system used mainly for human movement study. A reflective marker was placed on the head of each mouse using a surgical procedure and labeled animals were returned to their individual home cages. Camera-recorded data of marker displacement resulting from locomotor movements were then analyzed with custom built software. To avoid any data loss, data files were saved every hour and automatically concatenated. Long-term recordings (up to 3 months) with high spatial (<1mm) and temporal (up to 100Hz) resolution of animal movements were obtained.ResultsThe system was validated by analyzing the spontaneous activity of mice from post-natal day 30–90. Daily motor activity increased up to 70days in correspondence with maturational changes in locomotor performance. The recorded actigrams also permitted analysis of circadian and ultradian rhythms in cohort sleep/wake behavior.Comparison with existing method(s)In contrast to traditional session-based experimental approaches, our technique allows locomotor activity to be recorded with minimal experimenter manipulation, thereby minimizing animal stress.ConclusionsOur method enables the continuous long-term (up to several months) monitoring of tens of animals, generating manageable amounts of data at minimal costs without requiring individual dedicated devices. The actigraphic data collected allows circadian and ultradian analysis of sleep/wake behaviors to be performed.

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