Food Intake Monitoring
Overview
Automated food intake monitoring provides continuous, high-resolution measurement of feeding behavior by recording food hopper weight at frequent intervals (typically every second to every minute). This transforms gross daily food consumption into a detailed temporal microstructure of feeding — individual meals, meal duration, meal size, inter-meal intervals, and eating rate — revealing patterns that simple 24-hour food weighing cannot detect.
Feeding microstructure analysis is critical for dissociating the mechanisms of appetite-regulating drugs and genetic models: a compound might reduce total intake by decreasing meal size (satiety enhancement), decreasing meal number (hunger reduction), or slowing eating rate (palatability modulation). Similarly, orexigenic signals may increase meal size, meal frequency, or both. This level of analysis is essential for understanding hypothalamic feeding circuits, gut-brain signaling, and the pharmacology of obesity therapeutics.
ConductMaze interfaces with precision load cells mounted under food hoppers to capture weight changes in real time. The software applies validated meal-detection algorithms (defining meals by minimum intake threshold and minimum inter-meal interval), computes feeding bout parameters, generates circadian feeding pattern plots, and supports multi-cage simultaneous recording for cohort studies.
Trial Flow
Calibrate Hoppers
Tare and calibrate load cells under food hoppers
Begin Recording
Continuous weight sampling begins (1 Hz typical)
Feeding Detection
Weight decrease > threshold = feeding event
Meal Segmentation
Cluster feeding events into meals by IMI criterion
Circadian Analysis
Segment meals by light and dark phase
Daily Summary
Compute total intake, meal count, sizes, rates
Recording End
Export feeding microstructure data for analysis
Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
| Recording Duration | hours | 72 | Total monitoring period (24-72h typical) |
| Sampling Rate | Hz | 1 | Hopper weight measurement frequency |
| Meal Threshold | grams | 0.02 | Minimum weight change to count as feeding |
| Inter-Meal Interval | seconds | 300 | Minimum pause between feeding events to define meal boundary |
| Diet Type | enum | Standard chow | Food type (chow, HFD, liquid diet, palatable) |
| Number of Cages | integer | 16 | Simultaneous cages monitored |
Metrics
| Metric | Unit | Description |
|---|---|---|
| Total Daily Intake | g/day | Cumulative food consumed per 24-hour period |
| Meal Count | meals/day | Number of discrete meals per day |
| Mean Meal Size | grams | Average food consumed per meal — satiety index |
| Mean Meal Duration | seconds | Average duration of each meal |
| Eating Rate | mg/min | Rate of consumption within meals — palatability index |
| Inter-Meal Interval | minutes | Mean time between meals — hunger/satiety cycling |
| Light/Dark Intake Ratio | ratio | Dark-phase intake / Light-phase intake — circadian feeding |
Sample Data
| Subject | Group | Day | Total_Intake_g | Meals | Mean_Meal_g | Mean_IMI_min | Dark_Light_Ratio |
|---|
Representative data for illustration purposes. Actual values will vary by species, strain, and experimental conditions.
Applications
- 1Obesity pharmacology — distinguishing satiety enhancement from appetite suppression in drug screening
- 2Hypothalamic circuit dissection — optogenetic/chemogenetic effects on meal initiation and termination
- 3Gut-brain axis — GLP-1, CCK, and ghrelin effects on feeding microstructure
- 4Diet-induced obesity — palatability-driven overeating versus metabolic caloric compensation
- 5Eating disorder models — binge-like feeding pattern detection and quantification
Related Protocols
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