Aggression Bouts
Number of aggression bouts in the session
Time aggression bouts between two animals and see which one attacked.
Metrics automatically extracted by ConductVision.
Number of aggression bouts in the session
Time from the start of the session to the first bout
Length of each bout, in seconds
Sum of all bout durations in the session
Which of the two animals attacked in each bout, with the model confidence
Start and end of every bout, in seconds and in video frames
Behavior label and model probability for every video frame
9 body points on each animal: head, shoulder, two spine points, four paws, and tail base
Body-point coordinates for both animals in DeepLabCut-format CSV
Example output
A five-minute resident-intruder session with two animals. The model labels every frame, the clean-up rules turn those labels into bouts, and each bout gets an attacker.
The same 13 seconds at each step.
Each bout sits in the row of the animal that attacked. Select a bout for its details.
| Bout | Start | End | Duration | Attacker | Confidence |
|---|---|---|---|---|---|
| 1 | 42.0 s | 45.8 s | 3.8 s | Animal 1 | 92% |
| 2 | 61.3 s | 63.0 s | 1.7 s | Animal 1 | 88% |
| 3 | 88.0 s | 97.4 s | 9.4 s | Animal 1 | 90% |
| 4 | 131.5 s | 133.1 s | 1.6 s | Animal 1 | 79% |
| 5 | 170.2 s | 176.9 s | 6.7 s | Animal 2 | 86% |
| 6 | 214.0 s | 219.6 s | 5.6 s | Animal 1 | 86% |
| 7 | 262.4 s | 264.3 s | 1.9 s | Animal 1 | 82% |
The download uses the column names of the ConductVision bout table. The animal scored as attacking is in the intruder column and the other animal is in resident.
Aggression in rodents is usually studied with the resident-intruder test. An unfamiliar animal is placed in a resident's home cage, and attacks are scored over a short session. Attack latency, the number of attacks, and time spent fighting measure territorial aggression. Repeated defeat in the same setup is also used as a model of social stress.
ConductVision finds both animals in each video frame and tracks 9 body points on each. After the session, a trained neural network (an LSTM) reads how both animals move over time and marks the frames that belong to an aggression bout. Frames where either animal is out of view are not scored. Short gaps inside a bout, including brief dropouts, are joined so one fight is not split into several, and detections shorter than 30 frames (1 second at 30 fps) are dropped. For each bout you get its start, end, and duration, and which animal attacked.
Two model sets are included: one for lab rodents and one for hamsters. Results export as CSV, with one row per bout and a frame-by-frame file that holds the behavior label and model probability for each frame.
| Parameter | Description | Default |
|---|---|---|
| Animals per Recording | Animals found and tracked in each video | 2 |
| Body Points | Points tracked on each animal | 9 |
| Species Models | Choose the model that matches your animals | Lab rodent or hamster |
| Minimum Bout Length | Shorter detections are dropped | 30 frames (1 s at 30 fps) |
| Gap Bridging | Gaps this short inside a bout are joined | 10 frames (0.33 s at 30 fps) |
| Frame Rate | Read from the camera or video file; the bout rules count frames | 30 fps if not reported |
| Session Length | Set by your protocol | 10 min is common for resident-intruder |
Frames where either animal is out of view are not scored. Only dropouts of 10 frames or less inside a bout are joined back in.
Choose the lab rodent or hamster model to match the animals you record.
The bout rules count frames: at least 30 frames per bout, and gaps of up to 10 frames joined. That is 1 s and 0.33 s at 30 fps, or 0.5 s and 0.17 s at 60 fps.
The analysis finds and tracks two animals in each video.
Light without glare or flicker helps the software find both animals in every frame.
A starting paragraph for your methods section. Fill in the bracketed values from your study.
Aggressive behavior was scored automatically with ConductVision (ConductScience, version [version]) using the [lab rodent or hamster] model. Both animals were detected in every video frame and tracked with nine body points each (head, shoulder, two spine points, four paws, and tail base). A trained LSTM classifier labeled the behavior in each frame. Frames in which either animal was not detected were not scored, gaps of 10 frames or fewer within a bout were joined, and runs shorter than 30 frames were discarded ([frame rate] fps video). For each aggression bout, the start time, end time, duration, and attacking animal were recorded.
Higher territorial aggression. Longer isolation housing and some genetic lines raise attack frequency.
The resident attacks sooner, a common sign of heightened aggression.
Reduced aggression, or reduced activity. Sedation also delays attacks, so check locomotion before calling a drug anti-aggressive.
More sustained fighting within each encounter.
In a standard resident-intruder test one animal does most of the attacking. Attacks from both animals suggest the roles were not set up, for example an intruder larger than the resident.
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