Effects of home-cage elevation on behavioral tests in mice

BACKGROUND

Research reproducibility is a common problem in preclinical behavioral science. Mice are an important animal model for studying human behavioral disorders. Experimenters, processing methods, and rearing environments are the main causes of data variability in behavioral neuroscience. It is likely that mice adapt their behavior according to the environment outside the breeding cage. We speculated that mice housed on elevated shelves and mice housed on low shelves might have differently altered anxiety-like behavior toward heights.

PURPOSE

The purpose of this study was to investigate potential behavioral changes in mice raised at different heights for 3 weeks. Changes in behavior were examined using various experimental tests.

RESULTS

Mice housed on elevated shelves showed reduced anxiety-like behavior in a light/dark traffic test compared with mice housed on low shelves. There were no significant differences between the two groups in terms of activity, exploratory behavior, muscle strength, or depression-like behavior.

CONCLUSIONS

Our results indicate that different cage heights and corresponding light exposure may alter the anxiety-like behavior of mice in response to brightness. Researchers need to carefully control the cage height and light intensity experienced by the mice to produce reproducible test results.

Measuring Locomotor Activity and Behavioral Aspects of Rodents Living in the Home-Cage

Automatization and technological advances have led to a larger number of methods and systems to monitor and measure locomotor activity and more specific behavior of a wide variety of animal species in various environmental conditions in laboratory settings. In rodents, the majority of these systems require the animals to be temporarily taken away from their home-cage into separate observation cage environments which requires manual handling and consequently evokes distress for the animal and may alter behavioral responses. An automated high-throughput approach can overcome this problem. Therefore, this review describes existing automated methods and technologies which enable the measurement of locomotor activity and behavioral aspects of rodents in their most meaningful and stress-free laboratory environment: the home-cage. In line with the Directive 2010/63/EU and the 3R principles (replacement, reduction, refinement), this review furthermore assesses their suitability and potential for group-housed conditions as a refinement strategy, highlighting their current technological and practical limitations. It covers electrical capacitance technology and radio-frequency identification (RFID), which focus mainly on voluntary locomotor activity in both single and multiple rodents, respectively. Infrared beams and force plates expand the detection beyond locomotor activity toward basic behavioral traits but discover their full potential in individually housed rodents only. Despite the great premises of these approaches in terms of behavioral pattern recognition, more sophisticated methods, such as (RFID-assisted) video tracking technology need to be applied to enable the automated analysis of advanced behavioral aspects of individual animals in social housing conditions.

Measuring Behavior in the Home Cage: Study Design, Applications, Challenges, and Perspectives

The reproducibility crisis (or replication crisis) in biomedical research is a particularly existential and under-addressed issue in the field of behavioral neuroscience, where, in spite of efforts to standardize testing and assay protocols, several known and unknown sources of confounding environmental factors add to variance. Human interference is a major contributor to variability both within and across laboratories, as well as novelty-induced anxiety. Attempts to reduce human interference and to measure more "natural" behaviors in subjects has led to the development of automated home-cage monitoring systems. These systems enable prolonged and longitudinal recordings, and provide large continuous measures of spontaneous behavior that can be analyzed across multiple time scales. In this review, a diverse team of neuroscientists and product developers share their experiences using such an automated monitoring system that combines Noldus PhenoTyper® home-cages and the video-based tracking software, EthoVision® XT, to extract digital biomarkers of motor, emotional, social and cognitive behavior. After presenting our working definition of a "home-cage", we compare home-cage testing with more conventional out-of-cage tests (e.g., the open field) and outline the various advantages of the former, including opportunities for within-subject analyses and assessments of circadian and ultradian activity. Next, we address technical issues pertaining to the acquisition of behavioral data, such as the fine-tuning of the tracking software and the potential for integration with biotelemetry and optogenetics. Finally, we provide guidance on which behavioral measures to emphasize, how to filter, segment, and analyze behavior, and how to use analysis scripts. We summarize how the PhenoTyper has applications to study neuropharmacology as well as animal models of neurodegenerative and neuropsychiatric illness. Looking forward, we examine current challenges and the impact of new developments. Examples include the automated recognition of specific behaviors, unambiguous tracking of individuals in a social context, the development of more animal-centered measures of behavior and ways of dealing with large datasets. Together, we advocate that by embracing standardized home-cage monitoring platforms like the PhenoTyper, we are poised to directly assess issues pertaining to reproducibility, and more importantly, measure features of rodent behavior under more ethologically relevant scenarios.

Automated Analysis of Stroke Mouse Trajectory Data With Traja

Quantitative characterization of mouse activity, locomotion and walking patterns requires the monitoring of position and activity over long periods of time. Manual behavioral phenotyping, however, is time and skill-intensive, vulnerable to researcher bias and often stressful for the animals. We present examples for using a platform-independent open source trajectory analysis software, Traja, for semi-automated analysis of high throughput mouse home-cage data for neurobehavioral research. Our software quantifies numerous parameters of movement including traveled distance, velocity, turnings, and laterality which are demonstrated for application to neurobehavioral analysis. In this study, the open source software for trajectory analysis Traja is applied to movement and walking pattern observations of transient stroke induced female C57BL/6 mice (30 min middle cerebral artery occlusion) on an acute multinutrient diet intervention (Fortasyn). After stroke induction mice were single housed in Digital Ventilated Cages [DVC, GM500, Tecniplast S.p.A., Buguggiate (VA), Italy] and activity was recorded 24/7, every 250 ms using a DVC board. Significant changes in activity, velocity, and distance walked are computed with Traja. Traja identified increased walked distance and velocity in Control and Fortasyn animals over time. No diet effect was found in preference of turning direction (laterality) and distance traveled. As open source software for trajectory analysis, Traja supports independent development and validation of numerical methods and provides a useful tool for computational analysis of 24/7 mouse locomotion in home-cage environment for application in behavioral research or movement disorders.

An Automated Home-Cage System to Assess Learning and Performance of a Skilled Motor Task in a Mouse Model of Huntington's Disease

Behavioral testing is a critical step in assessing the validity of rodent models of neurodegenerative disease, as well as evaluating the efficacy of pharmacological interventions. In models of Huntington's disease (HD), a gradual progression of impairments is observed across ages, increasing the need for sensitive, high-throughput and longitudinal assessments. Recently, a number of automated systems have been developed to perform behavioral profiling of animals within their own home-cage, allowing for 24-h monitoring and minimizing experimenter interaction. However, as of yet, few of these have had functionality for the assessment of skilled motor learning, a relevant behavior for movement disorders such as HD. To address this, we assess a lever positioning task within the mouse home-cage. Animals first acquire a simple operant response, before moving to a second phase where they must learn to hold the lever for progressively longer in a rewarded position range. Testing with this paradigm has revealed the presence of distinct phenotypes in the YAC128 mouse model of HD at three early symptomatic time points. YAC128 mice at two months old, but not older, had a motor learning deficit when required to adapt their response to changes in task requirements. In contrast, six-month-old YAC128 mice had disruptions of normal circadian activity and displayed kinematic abnormalities during performance of the task, suggesting an impairment in motor control. This system holds promise for facilitating high throughput behavioral assessment of HD mouse models for preclinical therapeutic screening.