Home Cage Monitoring
Overview
Home cage monitoring provides continuous, undisturbed observation of rodent behavior in the home environment using overhead video, side-view cameras, or multi-sensor arrays. Unlike traditional behavioral tests that measure responses in novel, experimenter-controlled environments, home cage monitoring captures the full repertoire of spontaneous behavior — locomotion, rearing, grooming, nesting, sleeping, feeding, drinking, and social interactions — in the environment where the animal spends its entire life.
This approach eliminates acute stress artifacts from handling, novel environment exposure, and transport that confound conventional testing. It is particularly valuable for detecting subtle behavioral changes that occur over hours or days, such as progressive motor decline in neurodegenerative models, sickness behavior following immune challenge, pain-related behavioral suppression, or circadian fragmentation. Machine learning-based pose estimation (DeepLabCut, SLEAP) and behavior classification now enable automated scoring of complex behavioral repertoires from home cage video.
ConductMaze integrates with overhead and side-view camera systems, IR illumination for dark-phase recording, and sensor arrays (food/water access, nest quality scoring) to provide continuous multimodal home cage data. The software performs automated behavior classification, generates ethograms, computes activity budgets (percentage of time in each behavioral state), and identifies behavioral transitions and bout structures.
Trial Flow
Install Cameras
Mount cameras and IR illumination above home cage
Acclimation
Allow 24h habituation to camera/sensor presence
Continuous Recording
Video and sensor data collected 24/7
Behavior Detection
ML classifiers identify behavioral states in real time
Bout Analysis
Segment continuous stream into behavioral bouts
Activity Budget
Compute time allocation across behavioral categories
Report Generation
Daily/weekly behavioral summaries and trend analysis
Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
| Recording Duration | days | 7 | Total monitoring period |
| Video Resolution | enum | 1080p | Camera resolution (720p, 1080p, 4K) |
| Frame Rate | fps | 30 | Video acquisition frame rate |
| IR Illumination | boolean | Yes | Infrared lighting for dark-phase recording |
| Behavior Categories | integer | 8 | Number of classified behavioral states |
| Housing Type | enum | Single | Single or group housed (affects tracking complexity) |
| Nest Monitoring | boolean | Yes | Include nest quality scoring via image analysis |
Metrics
| Metric | Unit | Description |
|---|---|---|
| Distance Traveled | cm/h | Hourly locomotion in home cage — general activity |
| Rearing Frequency | events/h | Number of vertical explorations per hour |
| Grooming Duration | min/h | Time spent grooming — stress or dermatological index |
| Sleep Duration | hours/day | Total immobility meeting sleep criteria per day |
| Nest Score | 0-5 scale | Daily nest quality rating — well-being and thermoregulation |
| Activity Budget | % | Percentage of time in each behavioral state |
| Behavioral Entropy | bits | Complexity of behavioral sequence — stereotypy detection |
| Dark/Light Activity | ratio | Activity ratio between dark and light phase |
Sample Data
| Subject | Group | Day | Distance_cm_h | Rearing_h | Grooming_min_h | Sleep_h_day | Nest_Score |
|---|
Representative data for illustration purposes. Actual values will vary by species, strain, and experimental conditions.
Applications
- 1Neurodegenerative disease — longitudinal behavior decline tracking in ALS, AD, HD models without handling stress
- 2Pain research — spontaneous pain behavior and activity suppression as non-evoked pain endpoints
- 3Sickness behavior — immune challenge effects on activity, grooming, nesting, and social behavior
- 4Drug safety — continuous behavioral monitoring for adverse CNS effects over days
- 5Animal welfare — automated welfare scoring (nest quality, activity, grooming) for 3Rs compliance
Related Protocols
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