How can a mouse be identified by its sound? - briefly
By recording ultrasonic vocalizations with high‑frequency microphones and applying spectral analysis, researchers can extract distinctive frequency and temporal patterns that serve as acoustic signatures for individual mice. These unique sound profiles enable reliable identification without visual cues.
How can a mouse be identified by its sound? - in detail
Mice emit a wide spectrum of vocalizations that differ in frequency, duration, and modulation. Most communications occur above the human hearing range (20–100 kHz), while occasional audible squeaks (1–10 kHz) accompany aggressive or social interactions. By capturing these sounds with ultrasonic microphones and analyzing the recordings, researchers can distinguish individual rodents and infer behavioral states.
Signal acquisition
- Use a condenser microphone with a flat response up to at least 120 kHz.
- Position the sensor within 10 cm of the animal to ensure adequate signal‑to‑noise ratio.
- Sample at a minimum of 250 kHz to avoid aliasing of high‑frequency components.
Pre‑processing
- Apply a high‑pass filter (cut‑off ≈ 15 kHz) to remove low‑frequency background noise.
- Normalize amplitude across recordings to compensate for distance variations.
- Segment the continuous stream into discrete calls using an energy‑threshold detector.
Feature extraction
- Compute the spectrogram via short‑time Fourier transform (window ≈ 1 ms, 50 % overlap).
- Extract peak frequency, bandwidth, call duration, and frequency modulation slope.
- Calculate mel‑frequency cepstral coefficients (MFCCs) for fine‑grained timbral description.
Classification
- Train supervised models (e.g., support vector machines, random forests, convolutional neural networks) on labeled call sets.
- Validate performance with cross‑validation; typical accuracies for species‑level identification exceed 95 %, while individual discrimination reaches 80–90 % with sufficient training data.
- Deploy real‑time classifiers to flag specific call types (e.g., ultrasonic distress calls) for immediate behavioral interventions.
Practical considerations
- Ambient temperature influences sound velocity and thus frequency measurements; calibrate recordings at the experimental temperature.
- Cage materials can attenuate ultrasonic waves; use acrylic or glass enclosures to preserve signal integrity.
- Multiple microphones arranged in a triangulation array enable three‑dimensional localization of the vocalizing mouse, supporting further behavioral analysis.
By integrating high‑frequency recording hardware, rigorous signal processing, and machine‑learning classifiers, the acoustic signature of a mouse becomes a reliable identifier for both species and individual level studies. This methodology underpins research in neurobiology, ethology, and pest‑monitoring applications.