An integrated workflow for 2D and 3D posture analysis during vestibular system testing in mice.

Area of Science:

• Neuroscience
• Biomechanical Engineering
• Animal Behavior

Background:

• Posture extraction from videos is crucial for health screenings and understanding motor functions.
• The balance beam test is a standard protocol for assessing balance and motor coordination in mice.

Purpose of the Study:

• To develop an advanced workflow for analyzing mouse postures during balance beam locomotion.
• To enhance the utility and specificity of balance beam testing for motor coordination assessment.

Main Methods:

• Utilized FluoRender architecture and Python scripts to interact with DeepLabCut (DLC) for posture analysis.
• Processed twenty videos, categorizing feature points and optimizing camera angles (90° for 2D, 45° for 3D pose estimation).
• Extracted standard walk cycles (SWCs) based on foot movements and weighted correlations for refined analysis.

Main Results:

• Camera angles significantly improved 2D and 3D pose estimation accuracy.
• Identified a consistent 2-3-3 foot placement pattern on the beam, with individual variations.
• Observed subtle phase shifts in foot movement and posture anomalies correlated with speed and environmental factors.

Conclusions:

• The developed posture analysis workflow refines traditional behavioral testing.
• Enables sensitive detection of subtle changes in vestibular function and motor coordination in mice.
• Provides a foundation for further investigation into environmental influences on mouse gait and posture.