A robust automated system elucidates mouse home cage behavioral structure

Abstract

Patterns of behavior exhibited by mice in their home cages reflect the function and interaction of numerous behavioral and physiological systems. Detailed assessment of these patterns thus has the potential to provide a powerful tool for understanding basic aspects of behavioral regulation and their perturbation by disease processes. However, the capacity to identify and examine these patterns in terms of their discrete levels of organization across diverse behaviors has been difficult to achieve and automate. Here, we describe an automated approach for the quantitative characterization of fundamental behavioral elements and their patterns in the freely behaving mouse. We demonstrate the utility of this approach by identifying unique features of home cage behavioral structure and changes in distinct levels of behavioral organization in mice with single gene mutations altering energy balance. The robust, automated, reproducible quantification of mouse home cage behavioral structure detailed here should have wide applicability for the study of mammalian physiology, behavior, and disease.circadian ͉ ingestion ͉ obesity ͉ phenotyping M olecular genetic approaches for manipulating gene expression and neural activity in mice, combined with the elucidation of the mouse genome, provide unprecedented opportunities for the investigation of diverse behavioral processes in the context of a mammalian system. While substantial insights have been gained through the application of existing behavioral assays, many of these examine behavior over a limited time window and focus on a single behavioral domain (1, 2). To complement such approaches, we developed an automated, readily-standardized quantitative approach for elucidating the complex organization of diverse behaviors exhibited by mice in their home cages.We focused on mice in their home cages because the organization of behavior in freely acting animals provides a window into the central integration of numerous behavioral and physiological systems (e.g., energy balance, thermal status, osmotic/volume status, sleep, reproduction, defense, and environmental entrainment). The functions and interactions of these systems result in the coordinated organization of multiple behaviors (3-5). Although several sophisticated approaches for automated behavioral data collection and home cage monitoring exist, they do not employ algorithms that quantitatively capture the rich temporal and spatial structure of diverse behaviors that occur over multiple time scales (1,(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19).As a first step in examining this structure, we made use of the observation that in natural environments animals typically alternate between two major discrete states, active and inactive (20)(21)(22). During active states (ASs), animals engage in behaviors such as foraging and patrolling within a regularly traversed home range. During inactive states (ISs), animals return to a refuge (nest, burrow, or home base) and engage in behaviors such as rest and sleep (23-26). These...

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“…In ASs, animals engage in bouts of feeding, drinking, locomotion, and other behaviors. In ISs, animals engage in prolonged episodes of low physical activity (including sleep and resting) occurring exclusively in the nest (Goulding et al, 2008). We then analyzed these active state behaviors and calculated the active state probability (ASP) in both the dark cycle (DC) and light cycle (LC), a measure which is highly sensitive to circadian rhythm.…”

“…A detailed description of the HCM hardware has been reported elsewhere (Goulding et al, 2008). Briefly, all animals were acclimated to the HCM cages for 1 week, and then baseline data (days 8-15) were collected.…”

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“…Tecott has also used his monitoring system on two lines of mice genetically engineered for obesity: ob/ob mice, which lack the gene to make one of the hormones that regulates appetite; and htr2c mutant mice, which lack a receptor for the neurotransmitter serotonin 12 . The mice act like couch potatoes and midnight snackers respectively, says Tecott.…”

“…Tecott, working with colleagues Evan Goulding and Katrin Schenk, has developed an inexpensive system that can monitor animals around the clock 12 . A cage sits on a weightdetecting platform that measures an animal's location 50 times a second.…”