Protocol for non-invasive assessment of spontaneous movements of group-housed animals using remote video monitoring

High quality, high throughput, and low-cost simultaneous video recording of 60 animals in operant chambers using PiRATeMC

BACKGROUND

The development of Raspberry Pi-based recording devices for video analyses of drug self-administration studies has been shown to be promising in terms of affordability, customizability, and capacity to extract in-depth behavioral patterns. Yet, most video recording systems are limited to a few cameras making them incompatible with large-scale studies.

NEW METHOD

We expanded the PiRATeMC (Pi-based Remote Acquisition Technology for Motion Capture) recording system by increasing its scale, modifying its code, and adding equipment to accommodate large-scale video acquisition, accompanied by data on throughput capabilities, video fidelity, synchronicity of devices, and comparisons between Raspberry Pi 3B+ and 4B models.

RESULTS

Using PiRATeMC default recording parameters resulted in minimal storage (∼350MB/h), high throughput (< ∼120 seconds/Pi), high video fidelity, and synchronicity within ∼0.02 seconds, affording the ability to simultaneously record 60 animals in individual self-administration chambers for various session lengths at a fraction of commercial costs. No consequential differences were found between Raspberry Pi models.

COMPARISON WITH EXISTING METHOD(S)

This system allows greater acquisition of video data simultaneously than other video recording systems by an order of magnitude with less storage needs and lower costs. Additionally, we report in-depth quantitative assessments of throughput, fidelity, and synchronicity, displaying real-time system capabilities.

CONCLUSIONS

The system presented is able to be fully installed in a month's time by a single technician and provides a scalable, low cost, and quality-assured procedure with a high-degree of customization and synchronicity between recording devices, capable of recording a large number of subjects and timeframes with high turnover in a variety of species and settings.

Hidden variables in stress neurobiology research

Among the central goals of stress neurobiology research is to understand the mechanisms by which stressors change neural circuit function to precipitate or exacerbate psychiatric symptoms. Yet despite decades of effort, psychiatric medications that target the biological substrates of the stress response are largely lacking. We propose that the clinical advancement of stress response-based therapeutics for psychiatric disorders may be hindered by 'hidden variables' in stress research, including considerations of behavioral study design (stressors and outcome measures), individual variability, sex differences, and the interaction of the body's stress hormone system with endogenous circadian and ultradian rhythms. We highlight key issues and suggest ways forward in stress neurobiology research that may improve the ability to assess stress mechanisms and translate preclinical findings.

High quality, high throughput, and low-cost simultaneous video recording of 60 animals in operant chambers using PiRATeMC

Background

The development of Raspberry Pi-based recording devices for video analyses of drug self-administration studies has shown to be promising in terms of affordability, customizability, and capacity to extract in-depth behavioral patterns. Yet, most video recording systems are limited to a few cameras making them incompatible with large-scale studies.

New Method

We expanded the PiRATeMC (Pi-based Remote Acquisition Technology for Motion Capture) recording system by increasing its scale, modifying its code, and adding equipment to accommodate large-scale video acquisition, accompanied by data on the throughput capabilities, video fidelity, synchronicity of devices, and comparisons between the Raspberry Pi 3B+ and 4B models.

Results

Using PiRATeMC default recording parameters resulted in minimal storage (~350MB/h), high throughput (< ~120 seconds/Pi), high video fidelity, and synchronicity within ~0.02 seconds, affording the ability to simultaneously record 60 animals in individual self-administration chambers at a fraction of current commercial costs. No consequential differences were found between Raspberry Pi 3B+ and 4B models.

Comparison with Existing Methods

This system allows greater acquisition of video data simultaneously than other video recording systems by an order of magnitude with less storage needs and lower costs. Additionally, we report in-depth quantitative assessments of throughput, fidelity, and synchronicity, displaying real-time system capabilities.

Conclusions

The system presented is able to be fully installed in a month's time by a single technician and provides a scalable, low cost, and quality-assured procedure with a high-degree of customization and synchronicity between recording devices, capable of recording a large number of subjects with high turnover in a variety of species and settings.

Towards substitution of invasive telemetry: An integrated home cage concept for unobtrusive monitoring of objective physiological parameters in rodents

This study presents a novel concept for a smart home cage design, tools, and software used to monitor the physiological parameters of mice and rats in animal-based experiments. The proposed system focuses on monitoring key clinical parameters, including heart rate, respiratory rate, and body temperature, and can also assess activity and circadian rhythm. As the basis of the smart home cage system, an in-depth analysis of the requirements was performed, including camera positioning, imaging system types, resolution, frame rates, external illumination, video acquisition, data storage, and synchronization. Two different camera perspectives were considered, and specific camera models, including two near-infrared and two thermal cameras, were selected to meet the requirements. The developed specifications, hardware models, and software are freely available via GitHub. During the first testing phase, the system demonstrated the potential of extracting vital parameters such as respiratory and heart rate. This technology has the potential to reduce the need for implantable sensors while providing reliable and accurate physiological data, leading to refinement and improvement in laboratory animal care.

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

The objective was to exploit the raw data output from a scalable home cage (type IIL IVC) monitoring (HCM) system (DVC®), to characterize pattern of undisrupted rest and physical activity (PA) of C57BL/6J mice. The system's tracking algorithm show that mice in isolation spend 67% of the time in bouts of long rest (≥40s). Sixteen percent is physical activity (PA), split between local movements (6%) and locomotion (10%). Decomposition revealed that a day contains ˜7100 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 81% of time in rest (<1 EAD s-1) and 19% in PA. Periods ≥40 s of file when no movement occurs and there is no EAD may correspond to periods of sleep (˜59% of file time). We confirm that EAD correlates closely with movement distance (rs>0.95) and the data agreed in ˜97% 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 increasing density from one female to two males, and further to three male or female mice had the same effect size on EAD (˜2). In contrast, 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). As discussed, these metrics relay useful longitudinal information to those that use or care for the animals.

A two-choice assay for noxious light avoidance with temporal distribution analysis in Drosophila melanogaster larvae

Two-choice assays allow assessing of different behaviors including light avoidance in Drosophila larvae. Typically, the readout is limited to a preference index at a specific end point. We provide a detailed protocol to set up light avoidance assays and map the temporal distribution of larvae based on analysis of larval intensities. We describe the assay setup and implementation of scripts for analysis, which can be easily adapted to other two-choice assays and different model organisms.

For complete details on the use and execution of this protocol, please refer to Imambocus et al. (2022).

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Preparation and staging of Drosophila larvae for behavioral analysis

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Video-based recording of larval behavior in two-choice light avoidance assays

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Script-based video processing and extraction of larval distribution

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Quantitative analysis of temporal distribution of animals during light avoidance

Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.